Photovoltaic (PV) modules play an important role in modern distribution networks; however, from the beginning, PV modules have mostly been used in order to produce clean, green energy and to make a profit. Working effectively during the day, PV systems tend to achieve a maximum power point accomplished by inverters with built-in Maximum Power Point Tracking (MPPT) algorithms. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS), as a method for predicting an MPP based on data on solar exposure and the surrounding temperature. The advantages of the proposed method are a fast response, non-invasive sampling, total harmonic distortion reduction, more efficient usage of PV modules and a simple training of the ANFIS algorithm. To demonstrate the effectiveness and accuracy of the ANFIS in relation to the MPPT algorithm, a practical sample case of 10 kW PV system and its measurements are used as a model for simulation. Modelling and simulations are performed using all available components provided by technical data. The results obtained from the simulations point to the more efficient usage of the ANFIS model proposed as an MPPT algorithm for PV modules in comparison to other existing methods.
Comprehensive Review on Maximum Power Point Tracking Methods for SPV SystemIRJET Journal
This document reviews over 30 maximum power point tracking (MPPT) methods for solar photovoltaic systems. It provides an overview of various conventional and advanced MPPT techniques, including perturb and observe, incremental conductance, fuzzy logic control, and evolutionary algorithms. The document analyzes and compares the performance of these methods in terms of tracking speed, efficiency under changing weather conditions, ability to handle partial shading, and complexity of implementation. It aims to help researchers select the most suitable MPPT technique for their application.
Controllers are used in renewable energy systems like electric vehicles, wind turbines, and solar power plants to regulate various functions. Modern controllers for electric vehicles use pulse width modulation to smoothly control motor speed and acceleration. Advanced controllers for wind turbines and solar plants employ strategies like variable pitch control, maximum power point tracking, and fuzzy logic to optimize power capture despite changing environmental conditions. Controllers are critical for integrating renewable sources into smart grids and ensuring stable, efficient system operation as use of intermittent renewables increases.
This document summarizes a research paper that presents an output feedback nonlinear control strategy for a three-phase grid-connected photovoltaic (PV) power generation system. The control objectives are to ensure global stability of the system, achieve maximum power point tracking for the PV array, and ensure a unity power factor grid connection. A nonlinear controller is developed using Lyapunov stability analysis. Simulation results confirm the controller meets the objectives despite changing climatic conditions such as temperature and radiation. The paper models the three-phase grid-connected PV system and develops the output feedback controller and analysis to prove the control objectives are achieved.
This document describes a study that uses artificial neural networks (ANN) and genetic algorithms (GA) to model and control a grid-connected photovoltaic (PV) system. 390 sets of temperature and irradiance data were optimized using GA to obtain corresponding maximum power point (MPP) voltages. These optimized data were then used to train an ANN for MPPT control. Simulation results in Matlab/Simulink showed that the ANN-GA controller had less fluctuation around the MPP and faster convergence than conventional methods. A P-Q controller was also used to control grid voltage/current and allow both active and reactive power exchange.
Enhancement of On-grid PV System under Irradiance and Temperature Variations ...IJECEIAES
Solar Energy is one of the key solutions to future electrical power generation. Photovoltaic Plants (PV) are fast growing to satisfy electrical power demand. Different maximum power point tracking techniques (MPPT) are used to maximize PV systems generated power. In this paper, on grid PV system model in MATLAB SIMULINK is tested under sudden irradiance and cell temperature variations. Incremental Conductance MPPT is used to maximize generated power from the PV system with the help of new adaptive controller to withstand these heavy disturbances. The new adaptive controller is tuned for optimal operation using two different optimization techniques (Invasive weed and Harmony search).Optimization results for the two techniques are compared. .A robustness test is made to check system stability to withstand different random irradiance and cell temperature patterns without failure to track the maximum power point. Finally, a brief comparison is made with a previous literature and the new adaptive controller gives better results.
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques IJECEIAES
DC Microgrid is one feasible and effective solution to integrate renewable energy sources as well as to supply electricity. This paper proposes a DC microgrid with enhanced Maximum Power Point Tracking (MPPT) techniques for wind and solar energy systems. In this paper, the PV system power generation is enhanced by introducing a two-model MPPT technique that combines incremental conductance and constant voltage MPPT algorithms. Also, for the Wind Energy Conversion System (WECS) with pitch angle controlling technique, an Optimal Power Control MPPT technique is added. The Space Vector Pulse Width Modulation technique is introduced on grid side converter to improve the supply to the grid. The performance of proposed system is analyzed and the efficiency obtained with these methods is enhanced as compared with the previous methods.
IRJET- A Review on Solar based Multilevel Inverter with Three Phase Grid SupplyIRJET Journal
- The document discusses solar-powered multilevel inverters that can supply three-phase grid power. Multilevel inverters have advantages over single-level inverters like lower harmonic distortion, reduced electromagnetic interference, and the ability to operate at several voltage levels.
- The literature review covers prior research on different multilevel inverter topologies for photovoltaic systems, including the flying capacitor, neutral point clamped, and cascaded H-bridge inverters. It also discusses control methods like maximum power point tracking and modulation techniques.
- The goal is to develop a multilevel inverter powered by PV panels that can supply three-phase grid power with minimum harmonic distortion and reduced component requirements compared to
This document compares the performance of an artificial neural network trained with genetic algorithm (ANN-GA) data and a fuzzy logic controller for maximum power point tracking (MPPT) in a grid-connected photovoltaic system. The ANN-GA method uses a genetic algorithm to optimize training data for an artificial neural network controller. Simulation results in Matlab/Simulink show that the ANN-GA controller produces power with fewer fluctuations around the maximum power point and extra power compared to the fuzzy logic controller under different irradiance and temperature conditions. The ANN-GA method also regulates the PV output power well with the grid-connected inverter.
Comprehensive Review on Maximum Power Point Tracking Methods for SPV SystemIRJET Journal
This document reviews over 30 maximum power point tracking (MPPT) methods for solar photovoltaic systems. It provides an overview of various conventional and advanced MPPT techniques, including perturb and observe, incremental conductance, fuzzy logic control, and evolutionary algorithms. The document analyzes and compares the performance of these methods in terms of tracking speed, efficiency under changing weather conditions, ability to handle partial shading, and complexity of implementation. It aims to help researchers select the most suitable MPPT technique for their application.
Controllers are used in renewable energy systems like electric vehicles, wind turbines, and solar power plants to regulate various functions. Modern controllers for electric vehicles use pulse width modulation to smoothly control motor speed and acceleration. Advanced controllers for wind turbines and solar plants employ strategies like variable pitch control, maximum power point tracking, and fuzzy logic to optimize power capture despite changing environmental conditions. Controllers are critical for integrating renewable sources into smart grids and ensuring stable, efficient system operation as use of intermittent renewables increases.
This document summarizes a research paper that presents an output feedback nonlinear control strategy for a three-phase grid-connected photovoltaic (PV) power generation system. The control objectives are to ensure global stability of the system, achieve maximum power point tracking for the PV array, and ensure a unity power factor grid connection. A nonlinear controller is developed using Lyapunov stability analysis. Simulation results confirm the controller meets the objectives despite changing climatic conditions such as temperature and radiation. The paper models the three-phase grid-connected PV system and develops the output feedback controller and analysis to prove the control objectives are achieved.
This document describes a study that uses artificial neural networks (ANN) and genetic algorithms (GA) to model and control a grid-connected photovoltaic (PV) system. 390 sets of temperature and irradiance data were optimized using GA to obtain corresponding maximum power point (MPP) voltages. These optimized data were then used to train an ANN for MPPT control. Simulation results in Matlab/Simulink showed that the ANN-GA controller had less fluctuation around the MPP and faster convergence than conventional methods. A P-Q controller was also used to control grid voltage/current and allow both active and reactive power exchange.
Enhancement of On-grid PV System under Irradiance and Temperature Variations ...IJECEIAES
Solar Energy is one of the key solutions to future electrical power generation. Photovoltaic Plants (PV) are fast growing to satisfy electrical power demand. Different maximum power point tracking techniques (MPPT) are used to maximize PV systems generated power. In this paper, on grid PV system model in MATLAB SIMULINK is tested under sudden irradiance and cell temperature variations. Incremental Conductance MPPT is used to maximize generated power from the PV system with the help of new adaptive controller to withstand these heavy disturbances. The new adaptive controller is tuned for optimal operation using two different optimization techniques (Invasive weed and Harmony search).Optimization results for the two techniques are compared. .A robustness test is made to check system stability to withstand different random irradiance and cell temperature patterns without failure to track the maximum power point. Finally, a brief comparison is made with a previous literature and the new adaptive controller gives better results.
Design of Hybrid Solar Wind Energy System in a Microgrid with MPPT Techniques IJECEIAES
DC Microgrid is one feasible and effective solution to integrate renewable energy sources as well as to supply electricity. This paper proposes a DC microgrid with enhanced Maximum Power Point Tracking (MPPT) techniques for wind and solar energy systems. In this paper, the PV system power generation is enhanced by introducing a two-model MPPT technique that combines incremental conductance and constant voltage MPPT algorithms. Also, for the Wind Energy Conversion System (WECS) with pitch angle controlling technique, an Optimal Power Control MPPT technique is added. The Space Vector Pulse Width Modulation technique is introduced on grid side converter to improve the supply to the grid. The performance of proposed system is analyzed and the efficiency obtained with these methods is enhanced as compared with the previous methods.
IRJET- A Review on Solar based Multilevel Inverter with Three Phase Grid SupplyIRJET Journal
- The document discusses solar-powered multilevel inverters that can supply three-phase grid power. Multilevel inverters have advantages over single-level inverters like lower harmonic distortion, reduced electromagnetic interference, and the ability to operate at several voltage levels.
- The literature review covers prior research on different multilevel inverter topologies for photovoltaic systems, including the flying capacitor, neutral point clamped, and cascaded H-bridge inverters. It also discusses control methods like maximum power point tracking and modulation techniques.
- The goal is to develop a multilevel inverter powered by PV panels that can supply three-phase grid power with minimum harmonic distortion and reduced component requirements compared to
This document compares the performance of an artificial neural network trained with genetic algorithm (ANN-GA) data and a fuzzy logic controller for maximum power point tracking (MPPT) in a grid-connected photovoltaic system. The ANN-GA method uses a genetic algorithm to optimize training data for an artificial neural network controller. Simulation results in Matlab/Simulink show that the ANN-GA controller produces power with fewer fluctuations around the maximum power point and extra power compared to the fuzzy logic controller under different irradiance and temperature conditions. The ANN-GA method also regulates the PV output power well with the grid-connected inverter.
Performance assessment of an optimization strategy proposed for power systemsTELKOMNIKA JOURNAL
In the present article, the selection process of the topology of an artificial neural network (ANN) as well as its configuration are exposed. The ANN was adapted to work with the Newton Raphson (NR) method for the calculation of power flow and voltage optimization in the PQ nodes of a 10-node power system represented by the IEEE 1250 standard system. The purpose is to assess and compare its results with the ones obtained by implementing ant colony and genetic algorithms in the optimization of the same system. As a result, it is stated that the voltages in all system nodes surpass 0,99 p.u., thus representing a 20% increase in the optimal scenario, where the algorithm took 30 seconds, of which 9 seconds were used in the training and validation processes of the ANN.
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...IRJET Journal
This document describes a proposed system to control distributed wind and solar generators using an artificial neuro fuzzy interface system (ANFIS) within an energy control center (ECC) architecture based on a multi-agent system. The system would use ANFIS within the ECC to monitor voltages from the distributed generators and control circuit breakers connecting the generators to loads or energy storage like batteries. This would allow the system to optimize energy distribution based on generator output. The multi-agent system would include software agents running on different computers to manage each distributed generator and exchange information through the ECC. MATLAB/Simulink would be used to simulate the system and test ANFIS control of connecting generators to loads.
Artificial Neural Network for Solar Photovoltaic System Modeling and Simulationijtsrd
This paper presented neural network based maximum power point tracking on the design of photovoltaic power input to a DC DC boot converter to the load. Simulink model of photovoltaic array tested the neural network with different temperature and irradiance for maximum power point of a photovoltaic system. DC DC boot converter is used in load when an average output voltage is stable required which can be lower than the input voltage. At the end, the different temperature and irradiance of the data collected from the photovoltaic array system is used to train the neutral network and output efficiency of the designed DC DC boot converter with MPPT control strategy is accepted the maximum power amount to show the result voltage, current and power output for each different have been presented. And also demonstrated that the neural network based MPPT tracking require less time and more accurate results than the other algorithm based MPPT. Myint Thuzar | Cho Hnin Moh Moh Aung "Artificial Neural Network for Solar Photovoltaic System Modeling and Simulation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27867.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/27867/artificial-neural-network-for-solar-photovoltaic-system-modeling-and-simulation/myint-thuzar
In this paper, an optimization of PV grid connected system is investigated. This is achieved by considering the application of artificial intelligence in the DC side to realize maximal power extraction, and using a sine-band hysteresis control in the AC side of the system, to generate a sine current/voltage suitable for grid connection IEEE929-2000 standards. The overall system has been simulated taking into account environmental effects and standards constraints in order to achieve best performance. The choice of sine band hysteresis control was selected considering its implementation simplicity. The algorithm runs fast on a low-cost microcontroller allowing to avoid any delay that can cause a phase shift in the system. An experimental setup has been realized for tests and validation purposes. Both simulation and experimental results lead to satisfactory results which are conform to the IEEE929-2000 standards.
This document describes a hybrid maximum power point tracking (MPPT) algorithm for photovoltaic systems. It begins by discussing existing MPPT methods like fractional open circuit voltage, perturb and observe, and incremental MPPT with variable step size. It then proposes a new hybrid algorithm that combines advantages of these methods. The hybrid algorithm initializes the PV array voltage to 78% of open circuit voltage. It then uses perturb and observe with a variable step size and selects between two tracking schemes based on how rapidly irradiation is changing. Simulation results in MATLAB and PSIM showed improved starting performance and tracking effects over earlier MPPT methods.
This document summarizes a research paper that proposes using a STATCOM (Static Synchronous Compensator) to improve power quality when connecting renewable energy sources like wind turbines to the electric grid. The STATCOM provides reactive power support and helps maintain unity power factor at the source. MATLAB simulations show that with the STATCOM, source current is improved and additional load demand can be met dynamically. Charts of source current, load current, and STATCOM output demonstrate the STATCOM's ability to regulate power from the source and compensate for reactive power demands and harmonics.
This research presents tracking the maximum power of a photovoltaic to control a five-level inverter, a cascade type connecting a single-phase grid-connected system with a fuzzy logic control model. Maximum power tracking control In this research, the principle of controlling the maximum current amplitude of the photovoltaic multiplied by the sine signal per unit that used as a reference current compared to the grid current. Signal comparison with the PID controller allows the creation of five levels of PWM of cascade control of five-level inverter connects single-phase grids. The results of the simulation test using the program MATLAB/Simulink to compare with the generated prototype found that the fuzzy logic principle was used to control the maximum power tracking conditions of the P&O method, when the amount of radiation light intensity decreases suddenly, making it possible to track the maximum power of the photovoltaic. Also, when the inverter connected to the grid by controlling the power angle to compare results between the simulation and the prototype — found that the current flowing into the grid increases according to the power angle control. Resulting in a nearby waveform, sine wave and an out of phase angle to the grid voltage because the system is in the inverter mode, and the harmonic spectrum of the grid currently has total harmonic distortion (THD) is reduced as an indication of the proposed system can be developed and applications.
In a distributed generation system, divers renewable agents are connected to the low voltage 3 phase utility grid by an inverter which is used as power condition and must assurance the higher efficiency of the renewable agent. To achieve this level of efficiency, a unitary power factor between the utility grid voltages and the inverter currents is necessary, and a synchronization algorithm is required for the perfect synchronization between the 3-phase utility grid and the renewable agent. The aim of this paper is to present the optimization of the performance of a Synchronization controller for a 3-phase photovoltaic grid-connected system, assessing its accuracy under different conditions and studying their drawbacks and advantages. A grid connected photovoltaic system with a nominal power of 5 kW is used so as to assess the behavior of the synchronization algorithm when the 3 phase utility grid is affected by some disturbances such as voltage unbalances.
Development and Analysis of Fuzzy Control for MPPT Based Photovoltaic SystemIJERD Editor
This document presents a study on developing and analyzing a fuzzy control system for maximum power point tracking (MPPT) in a photovoltaic system. It proposes using a modified perturb and observe (P&O) MPPT algorithm with a fuzzy controller to track the maximum power point under varying conditions. The system is modeled and simulated in MATLAB/Simulink. Simulation results show that the fuzzy controlled P&O method produces smoother output power with less fluctuation compared to the conventional P&O method.
This article proposes using an adaptive neuro-fuzzy inference system (ANFIS) optimized by a genetic algorithm (GA) to track the maximum power point (MPP) of a grid-connected photovoltaic (PV) system under changing temperature and irradiance conditions. 360 data points of temperature and irradiance were optimized by GA and then used to train the ANFIS controller. Simulation results showed the ANFIS-GA controller could track the MPP with less fluctuation and faster convergence compared to conventional methods. A P/Q controller was also used to regulate both voltage and current for grid connection.
In photovoltaic (PV) systems, maximum power point tracking (MPPT) techniques are used to track the maximum power from the PV array under the change in irradiance and temperature conditions. The perturb and observe (P&O) is one of the most widely used MPPT techniques in recent times due to its simple implementation and improved performance. However, the P&O has limitations such as oscillation around the MPP during which time the P&O algorithm will become confused due to rapidly changing atmospheric conditions. To overcome the above limitation, this paper uses the fuzzy logic controller (FLC) to track the maximum power from the PV system under different irradiance, integrates it with a DC-DC boost converter as a tracker. The result of the FLC performance is compared with the traditional P&O method and shows the MPPT algorithm based on FLC ensures continuous tracking of the maximum power within a short period compared with the traditional P&O method. Besides that, the proposed method (FLC) has a faster dynamic response and low oscillations at the operating point around the MPP under steady-state conditions and dynamic change in irradiance.
Nonlinear Current Controller for a Single Phase Grid Connected Photovoltaic S...IRJET Journal
This document presents a nonlinear current control method for a single-phase grid-connected photovoltaic (PV) system. Partial feedback linearization is used to design the controller, which linearizes the system partially and enables controller design. The controller regulates the inverter switches to track the reference current from the maximum power point tracking system. Simulation results show the proposed controller performs well under changing conditions like atmospheric changes and faults, regulating the grid current better than hysteresis control. Experimental validation of the control scheme is also presented.
Grid Connected Photovoltaic System with Energy Management SchemeIRJET Journal
This document describes a grid-connected photovoltaic system with an energy management scheme. The system includes solar panels, a boost converter, single-phase inverter, loads, and an energy management module. The energy management module monitors energy usage and controls the inverter to maintain power balance. It allows excess solar energy to be exported to the grid and draws power from the grid when solar cannot meet local load demand, enabling bidirectional power flow. The system aims to deliver stable power output regardless of solar variations through this energy management scheme.
When the irradiance distribution over the photovoltaic panels is uniform, the pursuit of the maximum power point is not reached, which has allowed several researchers to use traditional MPPT techniques to solve this problem Among these techniques a PSO algorithm is used to have the maximum global power point (GMPPT) under partial shading. On the other hand, this one is not reliable vis-à-vis the pursuit of the MPPT. Therefore, in this paper we have treated another technique based on a new modified PSO algorithm so that the power can reach its maximum point. The PSO algorithm is based on the heuristic method which guarantees not only the obtaining of MPPT but also the simplicity of control and less expensive of the system. The results are obtained using MATLAB show that the proposed modified PSO algorithm performs better than conventional PSO and is robust to different partial shading models.
Maximum Power Point Tracking Technologies for Photovoltaic Efficiency Improve...IRJET Journal
This document discusses maximum power point tracking (MPPT) technologies used to improve the efficiency of photovoltaic systems. It begins by introducing the need for MPPT to extract maximum available power from solar panels given varying light and temperature conditions. It then describes modeling of solar cells and modules, and the use of DC-DC boost converters connected to MPPT controllers to vary output voltage for optimal power. The document simulates and evaluates the performance of a perturb and observe MPPT algorithm under changing light levels, showing it successfully tracks maximum power points.
Single Phase PV Grid-Connected in Smart Household Energy System with Anticipa...IJPEDS-IAES
This paper proposes an algorithm of Smart household energy systems to anticipate fault conditions in power system grid. Single phase PV grid- connected in smart household energy system is a smart system that determines electrical supply conditions to the load in residential electrical system. The smart system is consisted of two voltage source, conventional electricity system from national electricity provider as preferred source and photovoltaic as the alternative source. In smart system, fault conditions can be anticipated by selecting the appropriate voltage sources to supply the load. The condition of smart system can be described in power flow regulation to the load by detection and identification of amplitude, phase angle, and frequency of the voltage source compared to the system reference. The system mechanism is based on detection of voltage source using static transfer switch (STS) with phase locked loop (PLL) as voltage detection algorithm which output is used to determine decision logic algorithm for switching conditions. The results show that conditions of smart power system flow can be obtained based on voltage source selection in decision logic when fault condition occurs.
A new SOGI-PLL method based on fuzzy logic for grid connected PV inverterIJECEIAES
Phase angle detection of the grid voltage is an imperative part of control in most applications, especially for the synchronization of the current injected by the grid-connected photovoltaic inverters. Consequently, fast and accurate detection of the phase angle, frequency and amplitude of the grid voltage are indispensable data to ensure a correct generation of reference signals and operation of the grid connected inverters. We present in this work a new phase-locked loop (PLL) method for single-phase systems. The novelty is to generate an orthogonal voltage system using a second-order generalized integrator (SOGI), followed by a Park transformation, whose quadrature component is forced to zero by the fuzzy logic, in order to obtain rapid detection and a more accurate picture of the phase angle. Furthermore, simulation results with PSIM software will be submitted to verify the performance and effectiveness of the proposed method strategy. Finally, the experimental test will be used to extract the result and discuss the validity of the proposed algorithm.
Control of Grid Connected PV Inverter using LMF Adaptive MethodIRJET Journal
This document summarizes a research paper that proposes a least mean square fourth (LMF) adaptive filtering technique for controlling a single-stage, three-phase grid-connected photovoltaic (PV) inverter system. The LMF-based control algorithm is compared to existing algorithms like SRFT and IRPT, and is found to involve simpler computation, be easier to implement, more stable, faster settling time, and more reliable. Simulations in MATLAB/Simulink show the LMF approach effectively extracts maximum power from the PV system and regulates the DC link voltage even under unbalanced and nonlinear loads. The results demonstrate the efficiency and consistency of the proposed LMF-based control system compared to conventional techniques.
1. The document describes a hybrid wind and photovoltaic (PV) system connected to the main grid. It proposes using an adaptive neuro-fuzzy inference system (ANFIS) for maximum power point tracking (MPPT) of the PV array and a fuzzy logic controller for pitch angle control of the wind turbine.
2. Simulation results show that the ANFIS MPPT controller can track the maximum power point with less fluctuation and faster convergence compared to traditional MPPT methods. The fuzzy logic pitch controller provides faster response for high wind speeds, improving dynamic performance and preventing damage.
3. The complete hybrid system model is implemented in Matlab/Simulink, including the PV and wind systems, power converters
The performance of PV panel is very much dependent on the amount of sun light as well as the temperature of the surrounding environment which normally hard to be predicted. The use of PV emulator in the investigation of solar inverter especially at a lab scale platform helps to mitigate the inconsistency factors due to this uncontrollable variation. This work discussed on the design and development of a PV emulator for the grid-connected quasi-Z-source inverter which has different topology and control method compared to the conventional voltage source inverter. The I-V characteristics of the PV panel is modelled from the commercially available product and through circuit analysis the relation between capacitor voltage control and the PV terminal voltage is established, thus realizing the MPPT operation. Results from both simulation and experimental verification demonstrated that the PV emulator successfully able to produce power for the inverter according to the requirement.
Several algorithms have been offered to track the Maximum Power Point when we have one maximum power point. Moreover, fuzzy control and neural was utilized to track the Maximum Power Point when we have multi-peaks power points. In this paper, we will propose an improved Maximum Power Point tracking method for the photovoltaic system utilizing a modified PSO algorithm. The main advantage of the method is the decreasing of the steady state oscillation (to practically zero) once the Maximum Power Point is located. moreover, the proposed method has the ability to track the Maximum Power Point for the extreme environmental condition that cause the presence of maximum multi-power points, for example, partial shading condition and large fluctuations of insolation. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out under very challenging circumstance, namely step changes in irradiance, step changes in load, and partial shading of the Photovoltaic array. Finally, its performance is compared with the perturbation and observation” and fuzzy logic results for the single peak, and the neural-fuzzy control results for the multi-peaks.
Improvement of grid connected photovoltaic system using artificial neural net...ijscmcj
Photovoltaic (PV) systems have one of the highest potentials and operating ways for generating electrical power by converting solar irradiation directly into the electrical energy. In order to control maximum output power, using maximum power point tracking (MPPT) system is highly recommended. This paper simulates and controls the photovoltaic source by using artificial neural network (ANN) and genetic algorithm (GA) controller. Also, for tracking the maximum point the ANN and GA are used. Data are optimized by GA and then these optimum values are used in neural network training. The simulation results are presented by using Matlab/Simulink and show that the neural network-GA controller of grid-connected mode can meet the need of load easily and have fewer fluctuations around the maximum power point, also it can increase convergence speed to achieve the maximum power point (MPP) rather than conventional method. Moreover, to control both line voltage and current, a grid side p-q controller has been applied.
Performance assessment of an optimization strategy proposed for power systemsTELKOMNIKA JOURNAL
In the present article, the selection process of the topology of an artificial neural network (ANN) as well as its configuration are exposed. The ANN was adapted to work with the Newton Raphson (NR) method for the calculation of power flow and voltage optimization in the PQ nodes of a 10-node power system represented by the IEEE 1250 standard system. The purpose is to assess and compare its results with the ones obtained by implementing ant colony and genetic algorithms in the optimization of the same system. As a result, it is stated that the voltages in all system nodes surpass 0,99 p.u., thus representing a 20% increase in the optimal scenario, where the algorithm took 30 seconds, of which 9 seconds were used in the training and validation processes of the ANN.
ANFIS Control of Energy Control Center for Distributed Wind and Solar Generat...IRJET Journal
This document describes a proposed system to control distributed wind and solar generators using an artificial neuro fuzzy interface system (ANFIS) within an energy control center (ECC) architecture based on a multi-agent system. The system would use ANFIS within the ECC to monitor voltages from the distributed generators and control circuit breakers connecting the generators to loads or energy storage like batteries. This would allow the system to optimize energy distribution based on generator output. The multi-agent system would include software agents running on different computers to manage each distributed generator and exchange information through the ECC. MATLAB/Simulink would be used to simulate the system and test ANFIS control of connecting generators to loads.
Artificial Neural Network for Solar Photovoltaic System Modeling and Simulationijtsrd
This paper presented neural network based maximum power point tracking on the design of photovoltaic power input to a DC DC boot converter to the load. Simulink model of photovoltaic array tested the neural network with different temperature and irradiance for maximum power point of a photovoltaic system. DC DC boot converter is used in load when an average output voltage is stable required which can be lower than the input voltage. At the end, the different temperature and irradiance of the data collected from the photovoltaic array system is used to train the neutral network and output efficiency of the designed DC DC boot converter with MPPT control strategy is accepted the maximum power amount to show the result voltage, current and power output for each different have been presented. And also demonstrated that the neural network based MPPT tracking require less time and more accurate results than the other algorithm based MPPT. Myint Thuzar | Cho Hnin Moh Moh Aung "Artificial Neural Network for Solar Photovoltaic System Modeling and Simulation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27867.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/27867/artificial-neural-network-for-solar-photovoltaic-system-modeling-and-simulation/myint-thuzar
In this paper, an optimization of PV grid connected system is investigated. This is achieved by considering the application of artificial intelligence in the DC side to realize maximal power extraction, and using a sine-band hysteresis control in the AC side of the system, to generate a sine current/voltage suitable for grid connection IEEE929-2000 standards. The overall system has been simulated taking into account environmental effects and standards constraints in order to achieve best performance. The choice of sine band hysteresis control was selected considering its implementation simplicity. The algorithm runs fast on a low-cost microcontroller allowing to avoid any delay that can cause a phase shift in the system. An experimental setup has been realized for tests and validation purposes. Both simulation and experimental results lead to satisfactory results which are conform to the IEEE929-2000 standards.
This document describes a hybrid maximum power point tracking (MPPT) algorithm for photovoltaic systems. It begins by discussing existing MPPT methods like fractional open circuit voltage, perturb and observe, and incremental MPPT with variable step size. It then proposes a new hybrid algorithm that combines advantages of these methods. The hybrid algorithm initializes the PV array voltage to 78% of open circuit voltage. It then uses perturb and observe with a variable step size and selects between two tracking schemes based on how rapidly irradiation is changing. Simulation results in MATLAB and PSIM showed improved starting performance and tracking effects over earlier MPPT methods.
This document summarizes a research paper that proposes using a STATCOM (Static Synchronous Compensator) to improve power quality when connecting renewable energy sources like wind turbines to the electric grid. The STATCOM provides reactive power support and helps maintain unity power factor at the source. MATLAB simulations show that with the STATCOM, source current is improved and additional load demand can be met dynamically. Charts of source current, load current, and STATCOM output demonstrate the STATCOM's ability to regulate power from the source and compensate for reactive power demands and harmonics.
This research presents tracking the maximum power of a photovoltaic to control a five-level inverter, a cascade type connecting a single-phase grid-connected system with a fuzzy logic control model. Maximum power tracking control In this research, the principle of controlling the maximum current amplitude of the photovoltaic multiplied by the sine signal per unit that used as a reference current compared to the grid current. Signal comparison with the PID controller allows the creation of five levels of PWM of cascade control of five-level inverter connects single-phase grids. The results of the simulation test using the program MATLAB/Simulink to compare with the generated prototype found that the fuzzy logic principle was used to control the maximum power tracking conditions of the P&O method, when the amount of radiation light intensity decreases suddenly, making it possible to track the maximum power of the photovoltaic. Also, when the inverter connected to the grid by controlling the power angle to compare results between the simulation and the prototype — found that the current flowing into the grid increases according to the power angle control. Resulting in a nearby waveform, sine wave and an out of phase angle to the grid voltage because the system is in the inverter mode, and the harmonic spectrum of the grid currently has total harmonic distortion (THD) is reduced as an indication of the proposed system can be developed and applications.
In a distributed generation system, divers renewable agents are connected to the low voltage 3 phase utility grid by an inverter which is used as power condition and must assurance the higher efficiency of the renewable agent. To achieve this level of efficiency, a unitary power factor between the utility grid voltages and the inverter currents is necessary, and a synchronization algorithm is required for the perfect synchronization between the 3-phase utility grid and the renewable agent. The aim of this paper is to present the optimization of the performance of a Synchronization controller for a 3-phase photovoltaic grid-connected system, assessing its accuracy under different conditions and studying their drawbacks and advantages. A grid connected photovoltaic system with a nominal power of 5 kW is used so as to assess the behavior of the synchronization algorithm when the 3 phase utility grid is affected by some disturbances such as voltage unbalances.
Development and Analysis of Fuzzy Control for MPPT Based Photovoltaic SystemIJERD Editor
This document presents a study on developing and analyzing a fuzzy control system for maximum power point tracking (MPPT) in a photovoltaic system. It proposes using a modified perturb and observe (P&O) MPPT algorithm with a fuzzy controller to track the maximum power point under varying conditions. The system is modeled and simulated in MATLAB/Simulink. Simulation results show that the fuzzy controlled P&O method produces smoother output power with less fluctuation compared to the conventional P&O method.
This article proposes using an adaptive neuro-fuzzy inference system (ANFIS) optimized by a genetic algorithm (GA) to track the maximum power point (MPP) of a grid-connected photovoltaic (PV) system under changing temperature and irradiance conditions. 360 data points of temperature and irradiance were optimized by GA and then used to train the ANFIS controller. Simulation results showed the ANFIS-GA controller could track the MPP with less fluctuation and faster convergence compared to conventional methods. A P/Q controller was also used to regulate both voltage and current for grid connection.
In photovoltaic (PV) systems, maximum power point tracking (MPPT) techniques are used to track the maximum power from the PV array under the change in irradiance and temperature conditions. The perturb and observe (P&O) is one of the most widely used MPPT techniques in recent times due to its simple implementation and improved performance. However, the P&O has limitations such as oscillation around the MPP during which time the P&O algorithm will become confused due to rapidly changing atmospheric conditions. To overcome the above limitation, this paper uses the fuzzy logic controller (FLC) to track the maximum power from the PV system under different irradiance, integrates it with a DC-DC boost converter as a tracker. The result of the FLC performance is compared with the traditional P&O method and shows the MPPT algorithm based on FLC ensures continuous tracking of the maximum power within a short period compared with the traditional P&O method. Besides that, the proposed method (FLC) has a faster dynamic response and low oscillations at the operating point around the MPP under steady-state conditions and dynamic change in irradiance.
Nonlinear Current Controller for a Single Phase Grid Connected Photovoltaic S...IRJET Journal
This document presents a nonlinear current control method for a single-phase grid-connected photovoltaic (PV) system. Partial feedback linearization is used to design the controller, which linearizes the system partially and enables controller design. The controller regulates the inverter switches to track the reference current from the maximum power point tracking system. Simulation results show the proposed controller performs well under changing conditions like atmospheric changes and faults, regulating the grid current better than hysteresis control. Experimental validation of the control scheme is also presented.
Grid Connected Photovoltaic System with Energy Management SchemeIRJET Journal
This document describes a grid-connected photovoltaic system with an energy management scheme. The system includes solar panels, a boost converter, single-phase inverter, loads, and an energy management module. The energy management module monitors energy usage and controls the inverter to maintain power balance. It allows excess solar energy to be exported to the grid and draws power from the grid when solar cannot meet local load demand, enabling bidirectional power flow. The system aims to deliver stable power output regardless of solar variations through this energy management scheme.
When the irradiance distribution over the photovoltaic panels is uniform, the pursuit of the maximum power point is not reached, which has allowed several researchers to use traditional MPPT techniques to solve this problem Among these techniques a PSO algorithm is used to have the maximum global power point (GMPPT) under partial shading. On the other hand, this one is not reliable vis-à-vis the pursuit of the MPPT. Therefore, in this paper we have treated another technique based on a new modified PSO algorithm so that the power can reach its maximum point. The PSO algorithm is based on the heuristic method which guarantees not only the obtaining of MPPT but also the simplicity of control and less expensive of the system. The results are obtained using MATLAB show that the proposed modified PSO algorithm performs better than conventional PSO and is robust to different partial shading models.
Maximum Power Point Tracking Technologies for Photovoltaic Efficiency Improve...IRJET Journal
This document discusses maximum power point tracking (MPPT) technologies used to improve the efficiency of photovoltaic systems. It begins by introducing the need for MPPT to extract maximum available power from solar panels given varying light and temperature conditions. It then describes modeling of solar cells and modules, and the use of DC-DC boost converters connected to MPPT controllers to vary output voltage for optimal power. The document simulates and evaluates the performance of a perturb and observe MPPT algorithm under changing light levels, showing it successfully tracks maximum power points.
Single Phase PV Grid-Connected in Smart Household Energy System with Anticipa...IJPEDS-IAES
This paper proposes an algorithm of Smart household energy systems to anticipate fault conditions in power system grid. Single phase PV grid- connected in smart household energy system is a smart system that determines electrical supply conditions to the load in residential electrical system. The smart system is consisted of two voltage source, conventional electricity system from national electricity provider as preferred source and photovoltaic as the alternative source. In smart system, fault conditions can be anticipated by selecting the appropriate voltage sources to supply the load. The condition of smart system can be described in power flow regulation to the load by detection and identification of amplitude, phase angle, and frequency of the voltage source compared to the system reference. The system mechanism is based on detection of voltage source using static transfer switch (STS) with phase locked loop (PLL) as voltage detection algorithm which output is used to determine decision logic algorithm for switching conditions. The results show that conditions of smart power system flow can be obtained based on voltage source selection in decision logic when fault condition occurs.
A new SOGI-PLL method based on fuzzy logic for grid connected PV inverterIJECEIAES
Phase angle detection of the grid voltage is an imperative part of control in most applications, especially for the synchronization of the current injected by the grid-connected photovoltaic inverters. Consequently, fast and accurate detection of the phase angle, frequency and amplitude of the grid voltage are indispensable data to ensure a correct generation of reference signals and operation of the grid connected inverters. We present in this work a new phase-locked loop (PLL) method for single-phase systems. The novelty is to generate an orthogonal voltage system using a second-order generalized integrator (SOGI), followed by a Park transformation, whose quadrature component is forced to zero by the fuzzy logic, in order to obtain rapid detection and a more accurate picture of the phase angle. Furthermore, simulation results with PSIM software will be submitted to verify the performance and effectiveness of the proposed method strategy. Finally, the experimental test will be used to extract the result and discuss the validity of the proposed algorithm.
Control of Grid Connected PV Inverter using LMF Adaptive MethodIRJET Journal
This document summarizes a research paper that proposes a least mean square fourth (LMF) adaptive filtering technique for controlling a single-stage, three-phase grid-connected photovoltaic (PV) inverter system. The LMF-based control algorithm is compared to existing algorithms like SRFT and IRPT, and is found to involve simpler computation, be easier to implement, more stable, faster settling time, and more reliable. Simulations in MATLAB/Simulink show the LMF approach effectively extracts maximum power from the PV system and regulates the DC link voltage even under unbalanced and nonlinear loads. The results demonstrate the efficiency and consistency of the proposed LMF-based control system compared to conventional techniques.
1. The document describes a hybrid wind and photovoltaic (PV) system connected to the main grid. It proposes using an adaptive neuro-fuzzy inference system (ANFIS) for maximum power point tracking (MPPT) of the PV array and a fuzzy logic controller for pitch angle control of the wind turbine.
2. Simulation results show that the ANFIS MPPT controller can track the maximum power point with less fluctuation and faster convergence compared to traditional MPPT methods. The fuzzy logic pitch controller provides faster response for high wind speeds, improving dynamic performance and preventing damage.
3. The complete hybrid system model is implemented in Matlab/Simulink, including the PV and wind systems, power converters
The performance of PV panel is very much dependent on the amount of sun light as well as the temperature of the surrounding environment which normally hard to be predicted. The use of PV emulator in the investigation of solar inverter especially at a lab scale platform helps to mitigate the inconsistency factors due to this uncontrollable variation. This work discussed on the design and development of a PV emulator for the grid-connected quasi-Z-source inverter which has different topology and control method compared to the conventional voltage source inverter. The I-V characteristics of the PV panel is modelled from the commercially available product and through circuit analysis the relation between capacitor voltage control and the PV terminal voltage is established, thus realizing the MPPT operation. Results from both simulation and experimental verification demonstrated that the PV emulator successfully able to produce power for the inverter according to the requirement.
Several algorithms have been offered to track the Maximum Power Point when we have one maximum power point. Moreover, fuzzy control and neural was utilized to track the Maximum Power Point when we have multi-peaks power points. In this paper, we will propose an improved Maximum Power Point tracking method for the photovoltaic system utilizing a modified PSO algorithm. The main advantage of the method is the decreasing of the steady state oscillation (to practically zero) once the Maximum Power Point is located. moreover, the proposed method has the ability to track the Maximum Power Point for the extreme environmental condition that cause the presence of maximum multi-power points, for example, partial shading condition and large fluctuations of insolation. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out under very challenging circumstance, namely step changes in irradiance, step changes in load, and partial shading of the Photovoltaic array. Finally, its performance is compared with the perturbation and observation” and fuzzy logic results for the single peak, and the neural-fuzzy control results for the multi-peaks.
Improvement of grid connected photovoltaic system using artificial neural net...ijscmcj
Photovoltaic (PV) systems have one of the highest potentials and operating ways for generating electrical power by converting solar irradiation directly into the electrical energy. In order to control maximum output power, using maximum power point tracking (MPPT) system is highly recommended. This paper simulates and controls the photovoltaic source by using artificial neural network (ANN) and genetic algorithm (GA) controller. Also, for tracking the maximum point the ANN and GA are used. Data are optimized by GA and then these optimum values are used in neural network training. The simulation results are presented by using Matlab/Simulink and show that the neural network-GA controller of grid-connected mode can meet the need of load easily and have fewer fluctuations around the maximum power point, also it can increase convergence speed to achieve the maximum power point (MPP) rather than conventional method. Moreover, to control both line voltage and current, a grid side p-q controller has been applied.
This document presents a study that uses artificial neural networks (ANN) and genetic algorithms (GA) to improve the maximum power point tracking (MPPT) of a grid-connected photovoltaic system under different operating conditions. GA is used to optimize the data and determine the optimal voltage corresponding to the maximum power point. This optimized data is then used to train the ANN. The trained ANN is able to track the maximum power point with fewer fluctuations compared to conventional MPPT methods. A grid side p-q controller is also implemented to control both the line voltage and current and allow active and reactive power exchange with the grid. Simulation results in Matlab/Simulink demonstrate the effectiveness of the ANN-GA controller
We introduce in this paper a new FPGA-based Maximum Power Tracker for photovoltaic systems. The developed approach targets to modify the perturb and observe in view of reaching rapid tracking and achieving excellent accuracy, while keeping the stability performance and the reduced complexity. To perform this improvement, an automatic and smart two steps switcher is integrated, in addition inputs FIR filters are incorporated. Therefore, a high sampling frequency is attained, and consequently the tracking speed is improved. MATLAB simulations and the Xilinx FPGA implementation results show that the improved approach reaches a performance very close to the recently published MPPT methods, with lesser complexity.
A Reliable Tool Based on the Fuzzy Logic Control Method Applying to the DC/DC...phthanh04
Solar energy performs an important role in electric energy based on renewable energy generation systems when referring to
clear energy. Systems for harvesting renewable energy frequently use DC/DC converters, especially solar photovoltaic systems. The
DC/DC boost converter has been used for converting the output voltage from the solar PV system to the required voltage rating of the
utility grid under the disturbance in the photovoltaic temperature and irradiation level. Because of that, a new maximum power point
tracking based on the fuzzy logic controller (MPPT-FLC) algorithm applying the DC/DC boost converter is developed. The proposed
approach aims toward improving the PV system's performance and tracking effectiveness. This aim can be achieved by adjusting the
DC/DC boost converter's duty cycle to ensure that the PV system operates close to its MPP under varying environmental conditions. The
effectiveness of the proposed method is verified in the off-grid PV system under conditions of the change of irradiation and temperature,
and the comparison of between the proposed method, the incremental conductance (INC), perturb and observe (P&O), and modified P&O
methods is also made. The obtained simulation results show that the MPPT capability significantly improved and achieved the highest
MPPT efficiency of 99.999% and an average efficiency of 99.98% in total when applying the proposed method.
This document summarizes a simulation study comparing the performance of three maximum power point tracking (MPPT) algorithms - incremental conductance, perturb and observe, and fuzzy logic control - for a 100 kW photovoltaic system connected to the electrical grid. The system was simulated in MATLAB/Simulink under varying irradiance conditions. Graphs of solar irradiance, PV voltage, duty cycle, modulation index, DC link voltage, grid voltage, grid current, and output power are presented for each MPPT algorithm to analyze and compare their performance.
A novel efficient adaptive-neuro fuzzy inference system control based smart ...IJECEIAES
This document presents a novel adaptive-neuro fuzzy inference system (ANFIS) control algorithm for a smart grid integrating solar, wind, and grid power sources. The proposed ANFIS controller is used to improve the steady-state and transient response of the hybrid power system. Fuzzy logic maximum power point tracking algorithms are used to extract maximum power from solar photovoltaic panels and a permanent magnet synchronous generator is used for wind power generation. Back-to-back voltage source converters operated by the ANFIS controller are used to maximize both renewable power generations. Simulation results under different operating conditions and nonlinear faults show the proposed ANFIS control algorithm improves the overall system performance.
This document analyzes a unified output MPPT control strategy for a subpanel PV converter system (SPMC) to address real-world mismatch issues in photovoltaic systems. The SPMC system connects a dedicated MPPT converter to each PV cell string in a panel. This allows each string to operate at its individual maximum power point regardless of mismatch conditions. However, implementing independent MPPT control for each string increases costs. Therefore, the document proposes a unified output MPPT control structure that reduces costs by saving on analog-to-digital units, current sensors, and MPPT controllers while still allowing each SPMC to operate at its optimal maximum power point. Simulation and experimental results confirm the effectiveness of this unified output control approach.
Maximum power point tracking techniques for photovoltaic systems: a comparati...IJECEIAES
Photovoltaic (PV) systems are one of the most important renewable energy resources (RER). It has limited energy efficiency leading to increasing the number of PV units required for certain input power i.e. to higher initial cost. To overcome this problem, maximum power point tracking (MPPT) controllers are used. This work introduces a comparative study of seven MPPT classical, artificial intelligence (AI), and bio-inspired (BI) techniques: perturb and observe (P&O), modified perturb and observe (M-P&O), incremental conductance (INC), fuzzy logic controller (FLC), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and cuckoo search (CS). Under the same climatic conditions, a comparison between these techniques in view of some criteria’s: efficiencies, tracking response, implementation cost, and others, will be performed. Simulation results, obtained using MATLAB/SIMULINK program, show that the MPPT techniques improve the lowest efficiency resulted without control. ANFIS is the highest efficiency, but it requires more sensors. CS and ANN produce the best performance, but CS provided significant advantages over others in view of low implementation cost, and fast computing time. P&O has the highest oscillation, but this drawback is eliminated using M-P&O. FLC has the longest computing time due to software complexity, but INC has the longest tracking time.
An IntelligentMPPT Method For PV Systems Operating Under Real Environmental C...theijes
The sun irradiance (G) and temperature (T) are the two main factors that affect the output power gained from the photovoltaic (PV) DC–DC converter. Therefore, to enhance the performance of the overall system; a mechanism to track the maximum power point (MPP) is required. Conventional maximum power point tracking approaches, such as observation and perturbation technique, experience difficulty in identifying the true MPP. Therefore, intelligent systems including fuzzy logic controllers (FLC) are introduced for the maximum power point tracking system (MPPT). The selection of the membership functions (MFs) and the fuzzy sets (FSs) numbers are crucial in the performance of the FLC based MPPT. Accordingly, this work presents numerous adaptive neuro-fuzzy systems to automatically adjustthe fuzzy logic controller membership functions as an alternative to the trial and error approach, which waste time and effort in MPPT design. For this purpose an adaptive neuro-fuzzy system is developed in MATLAB/Simulink to determine suitable MFs and the FSs for the fuzzy logic controller. The effects of different types of MFs and the FSs are deeply investigated using real data collected from the rooftop PV system. The investigations show that the fuzzy logic controller with a triangular membership function and seven fuzzy setsprovides the best results
Two fuzzy logic controllers are proposed in this paper to control a three phase inverter for grid connected photovoltaic system. The first controller was used to predict the DC voltage that allows the three phase inverter to track the maximum power point of photovoltaic array under different environmental conditions such as irradiances and temperature. The second was used to control the active power and reactive power injected into the grid in order to inject the maximum active power produced by photovoltaic systems into grid with high efficiency and low total harmonic distortion using the same three phase inverter. The system components are photovoltaic array, DC link voltage, three-phase inverter, inverter control, LC filter, transformer and grid. To verify the effectivnesse of the introdueced system, modeling and simulation are verified in Matlab/Simulink due to its frequent use and its effectiveness.
This paper presents a maximum power point (MPP) tracking method based on a hybrid combination between the fuzzy logic controller (FLC) and the conventional Perturb-and-Observe (P&O) method. The proposed algorithm utilizes the FLC to initialize P&O algorithm with an initial duty cycle. MATLAB/Simulink models consisting of, the photovoltaic system, boost converter and controllers, are built to evaluate the performance of the proposed algorithm. To accurately illustrate the performance of the proposed algorithm, comparisons with standalone FLC and P&O are carried out. The performance of the proposed algorithm is investigated difficult weather conditions including sudden changes and partial shading. The results showed that the proposed algorithm successfully reaches MPP in all scenarios.
Fuzzy based Modular Cascaded H-Bridge Multilevel PV Inverter with Distributed...IJMTST Journal
The inverters are categorized according to the configuration of the PV system, the configuration of the conversion stages within the inverter and whether they use transformers. After the introduction of the state of the art of inverters for PV systems with and without transformers, the paper focuses on some known problems and challenges for transformer less inverters. Topologies without transformers have big advantages like low weight, volume and cost. In addition they often reach higher efficiencies than topologies with transformers. Eliminating the leakage current is one of the most important issues for transformer less inverters in grid-connected photovoltaic system applications, where the technical challenge is how to keep the system common-mode voltage constant to reduce the leakage current. To realize better utilization of PV modules and maximize the solar energy extraction, a distributed maximum power point tracking control scheme is applied to both single- and three-phase multilevel inverters, which allows independent control of each dc-link voltage. For three-phase grid-connected applications, PV mismatches may introduce unbalanced supplied power, leading to unbalanced grid current.
Perturb and observe maximum power point tracking for photovoltaic cellAlexander Decker
This document discusses perturb and observe (P&O) maximum power point tracking (MPPT) for photovoltaic cells. It begins with an abstract that outlines P&O MPPT and its drawbacks, including oscillation around the maximum power point and confusion during rapidly changing conditions. The document then provides background on renewable energy sources like photovoltaics and the need for MPPT techniques. It describes the P&O MPPT algorithm and its implementation using MATLAB modeling of a PV array's I-V and P-V characteristics under varying irradiance and temperature conditions.
The power supplied by photovoltaic DC–DC converter is affected by two factors, sun irradiance and temperature. Therefore, to improve the performance of the PV system; a mechanism to track the maximum power point (MPP) is required. Conventional maximum power point tracking approaches, such as observation and perturbation technique present some difficulties in identifying the true MPP. Therefore, intelligent systems including fuzzy logic controllers (FLC) are introduced for the maximum power point tracking system (MPPT). In this paper, we present a comparative study of the PV standalone system which is controlled by three techniques. The first one is conventional based on the observation and perturbation technique, the other are intelligent based on fuzzy logic according Mamdani and Takagi-Sugeno models. The investigations show that the fuzzy logic controllers provide the best results and Takagi-Sugeno model presents the lower overshoot value.
Investigation of Interleaved Boost Converter with Voltage multiplier for PV w...ecij
This paper depicts the significance of Interleaved Boost Converter (IBC) with diode-capacitor multiplierwith PV as the input source. Maximum Power Point Tracking (MPPT) was used to obtain maximum power from the PV system. In this, interleaving topology is used to reduce the input current ripple, output voltage ripple, power loss and to suppress the ripple in battery current in the case of Plugin Hybrid Electric Vehicle (PHEV). Moreover, voltage multiplier cells are added in the IBC configuration to reduce the narrow turn-off periods. Two MPPT techniques are compared in this paper: i) Perturb and Observe (P&O) algorithm ii) Fuzzy Logic . The two algorithms are simulated using MATLAB and the comparison of performance parameters like the ripple is done and the results are verified.
A Novel Approach for Power Quality Improvement in Distributed Generationseema appa
This document discusses passive filter designs for improving power quality in standalone photovoltaic (PV) systems. It analyzes LC, LCL, and LLCC filter topologies to reduce the total harmonic distortion of a single-phase standalone PV system. Simulation results in MATLAB-SIMULINK show that an LLCC filter is most effective at improving power quality by highly reducing the total harmonic distortion compared to LC and LCL filters. The paper focuses on the design, analysis, and comparison of different passive filter topologies to evaluate their effectiveness in power quality improvement for medium power standalone PV applications.
Modeling and simulation of three phases cascaded H-bridge grid-tied PV inverterjournalBEEI
In this paper a control scheme for three phase seven level cascaded H-bridge inverter for grid tied PV system is presented. As power generation from PV depends on varing environmental conditions, for extractraction of maximum power from PV array, fuzzy MPPT controller is incorporated with each PV array. It gives fast and accurate response. To maintain the grid current
sinusoidal under varying conditions, a digital PI controller scheme is adopted. A MATLAB/Simulink model is developed for this purpose and results are presented. At last THD analysis is carried out in order to validate the performance of the overall system. As discussed, with this control strategy the balanced grid current is obtained keeping THD values with in the specified range of IEEE-519 standard.
Electric Vehicle as an Energy Storage for Grid Connected Solar Power SystemIAES-IJPEDS
In the past few years the growing demand for electricity and serious concern
for the environment have given rise to the growth of sustainable sources like
wind, solar, tidal, biomass etc. The technological advancement in power
electronics has led to the extensive usage of solar power. Solar power output
varies with the weather conditions and under shading conditions. With the
increasing concerns of the impacts of the high penetration of Photovoltaic
(PV) systems, a technical study about their effects on the power quality of
the utility grid is required. This paper investigates the functioning of a gridtied
PV system along with maximum power point tracking (MPPT)
algorithm. The effects of varying atmospheric conditions like solar irradiance
and temperature are also taken into account. It is proposed in this work that
an Electric Vehicle (EV) can be used as an energy storage to stabilize the
power supplied to the grid from the photovoltaic resources. A coordinated
control is necessary for the EV to obtain desired outcome. The modeling of
the PV and EV system is carried out in PSCAD and the proposed idea is
verified through simulation results utilizing real field data for solar irradiance
and temperature.
MAXIMUM POWER POINT TRACKING BASED PHOTO VOLTAIC SYSTEM FOR SMART GRID INTEGR...IRJET Journal
This document presents a study on implementing Maximum Power Point Tracking (MPPT) algorithms in a photovoltaic (PV) system designed for integration into smart grids using MATLAB. It examines MPPT algorithms like Perturb and Observe, Incremental Conductance, and Fuzzy Logic Control to optimize power extraction from PV panels under varying conditions. The paper models and simulates the PV system in MATLAB/Simulink to analyze its performance and dynamic responses. It also addresses challenges and benefits of integrating the MPPT-based PV system into a smart grid, including bidirectional power flow and responding to grid events. Simulation results demonstrate the effectiveness of the MPPT algorithms and the system's potential to support the grid and enhance power generation efficiency
Similar to ANFIS used as a Maximum Power Point Tracking Algorithmfor a Photovoltaic System (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
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The Unbelievable Tale of Dwayne Johnson Kidnapping: A Riveting Sagagreendigital
Introduction
The notion of Dwayne Johnson kidnapping seems straight out of a Hollywood thriller. Dwayne "The Rock" Johnson, known for his larger-than-life persona, immense popularity. and action-packed filmography, is the last person anyone would envision being a victim of kidnapping. Yet, the bizarre and riveting tale of such an incident, filled with twists and turns. has captured the imagination of many. In this article, we delve into the intricate details of this astonishing event. exploring every aspect, from the dramatic rescue operation to the aftermath and the lessons learned.
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The Origins of the Dwayne Johnson Kidnapping Saga
Dwayne Johnson: A Brief Background
Before discussing the specifics of the kidnapping. it is crucial to understand who Dwayne Johnson is and why his kidnapping would be so significant. Born May 2, 1972, Dwayne Douglas Johnson is an American actor, producer, businessman. and former professional wrestler. Known by his ring name, "The Rock," he gained fame in the World Wrestling Federation (WWF, now WWE) before transitioning to a successful career in Hollywood.
Johnson's filmography includes blockbuster hits such as "The Fast and the Furious" series, "Jumanji," "Moana," and "San Andreas." His charismatic personality, impressive physique. and action-star status have made him a beloved figure worldwide. Thus, the news of his kidnapping would send shockwaves across the globe.
Setting the Scene: The Day of the Kidnapping
The incident of Dwayne Johnson's kidnapping began on an ordinary day. Johnson was filming his latest high-octane action film set to break box office records. The location was a remote yet scenic area. chosen for its rugged terrain and breathtaking vistas. perfect for the film's climactic scenes.
But, beneath the veneer of normalcy, a sinister plot was unfolding. Unbeknownst to Johnson and his team, a group of criminals had planned his abduction. hoping to leverage his celebrity status for a hefty ransom. The stage was set for an event that would soon dominate worldwide headlines and social media feeds.
The Abduction: Unfolding the Dwayne Johnson Kidnapping
The Moment of Capture
On the day of the kidnapping, everything seemed to be proceeding as usual on set. Johnson and his co-stars and crew were engrossed in shooting a particularly demanding scene. As the day wore on, the production team took a short break. providing the kidnappers with the perfect opportunity to strike.
The abduction was executed with military precision. A group of masked men, armed and organized, infiltrated the set. They created chaos, taking advantage of the confusion to isolate Johnson. Johnson was outnumbered and caught off guard despite his formidable strength and fighting skills. The kidnappers overpowered him, bundled him into a waiting vehicle. and sped away, leaving everyone on set in a state of shock and disbelief.
The Immediate Aftermath
The immediate aftermath of the Dwayne Johnson kidnappin
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The landscape of independent filmmaking is evolving at an unprecedented pace. Technological advancements, changing consumer preferences, and new distribution models are reshaping the industry, creating new opportunities and challenges for filmmakers and film industry jobs. This article explores the future of independent filmmaking, highlighting key trends and emerging job opportunities.
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Leonardo DiCaprio, a name synonymous with Hollywood stardom and acting excellence. has captivated audiences for decades with his talent and charisma. But, the Leonardo DiCaprio haircut is one aspect of his public persona that has garnered attention. From his early days as a teenage heartthrob to his current status as a seasoned actor and environmental activist. DiCaprio's hairstyles have evolved. reflecting both his personal growth and the changing trends in fashion. This article delves into the many phases of the Leonardo DiCaprio haircut. exploring its significance and impact on pop culture.
Orpah Winfrey Dwayne Johnson: Titans of Influence and Inspirationgreendigital
Introduction
In the realm of entertainment, few names resonate as Orpah Winfrey Dwayne Johnson. Both figures have carved unique paths in the industry. achieving unparalleled success and becoming iconic symbols of perseverance, resilience, and inspiration. This article delves into the lives, careers. and enduring legacies of Orpah Winfrey Dwayne Johnson. exploring how their journeys intersect and what we can learn from their remarkable stories.
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Early Life and Backgrounds
Orpah Winfrey: From Humble Beginnings to Media Mogul
Orpah Winfrey, often known as Oprah due to a misspelling on her birth certificate. was born on January 29, 1954, in Kosciusko, Mississippi. Raised in poverty by her grandmother, Winfrey's early life was marked by hardship and adversity. Despite these challenges. she demonstrated a keen intellect and an early talent for public speaking.
Winfrey's journey to success began with a scholarship to Tennessee State University. where she studied communication. Her first job in media was as a co-anchor for the local evening news in Nashville. This role paved the way for her eventual transition to talk show hosting. where she found her true calling.
Dwayne Johnson: From Wrestling Royalty to Hollywood Superstar
Dwayne Johnson, also known by his ring name "The Rock," was born on May 2, 1972, in Hayward, California. He comes from a family of professional wrestlers, with both his father, Rocky Johnson. and his grandfather, Peter Maivia, being notable figures in the wrestling world. Johnson's early life was spent moving between New Zealand and the United States. experiencing a variety of cultural influences.
Before entering the world of professional wrestling. Johnson had aspirations of becoming a professional football player. He played college football at the University of Miami. where he was part of a national championship team. But, injuries curtailed his football career, leading him to follow in his family's footsteps and enter the wrestling ring.
Career Milestones
Orpah Winfrey: The Queen of All Media
Winfrey's career breakthrough came in 1986 when she launched "The Oprah Winfrey Show." The show became a cultural phenomenon. drawing millions of viewers daily and earning many awards. Winfrey's empathetic and candid interviewing style resonated with audiences. helping her tackle diverse and often challenging topics.
Beyond her talk show, Winfrey expanded her empire to include the creation of Harpo Productions. a multimedia production company. She also launched "O, The Oprah Magazine" and OWN: Oprah Winfrey Network, further solidifying her status as a media mogul.
Dwayne Johnson: From The Ring to The Big Screen
Dwayne Johnson's wrestling career took off in the late 1990s. when he became one of the most charismatic and popular figures in WWE. His larger-than-life persona and catchphrases endeared him to fans. making him a household name. But, Johnson had ambitions beyond the wrestling ring.
In the early 20
Everything You Need to Know About IPTV Ireland.pdfXtreame HDTV
The way we consume television has evolved dramatically over the past decade. Internet Protocol Television (IPTV) has emerged as a popular alternative to traditional cable and satellite TV, offering a wide range of channels and on-demand content via the internet. In Ireland, IPTV is rapidly gaining traction, with Xtreame HDTV being one of the prominent providers in the market. This comprehensive guide will delve into everything you need to know about IPTV Ireland, focusing on Xtreame HDTV, its features, benefits, and how it is revolutionizing TV viewing for Irish audiences.
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At Digidev, we are working to be the leader in interactive streaming platforms of choice by smart device users worldwide.
Our goal is to become the ultimate distribution service of entertainment content. The Digidev application will offer the next generation television highway for users to discover and engage in a variety of content. While also providing a fresh and
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Leonardo DiCaprio House: A Journey Through His Extravagant Real Estate Portfoliogreendigital
Introduction
Leonardo DiCaprio, A name synonymous with Hollywood excellence. is not only known for his stellar acting career but also for his impressive real estate investments. The "Leonardo DiCaprio house" is a topic that piques the interest of many. as the Oscar-winning actor has amassed a diverse portfolio of luxurious properties. DiCaprio's homes reflect his varied tastes and commitment to sustainability. from retreats to historic mansions. This article will delve into the fascinating world of Leonardo DiCaprio's real estate. Exploring the details of his most notable residences. and the unique aspects that make them stand out.
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Leonardo DiCaprio House: Malibu Beachfront Retreat
A Prime Location
His Malibu beachfront house is one of the most famous properties in Leonardo DiCaprio's real estate portfolio. Situated in the exclusive Carbon Beach. also known as "Billionaire's Beach," this property boasts stunning ocean views and private beach access. The "Leonardo DiCaprio house" in Malibu is a testament to the actor's love for the sea and his penchant for luxurious living.
Architectural Highlights
The Malibu house features a modern design with clean lines, large windows. and open spaces blending indoor and outdoor living. The expansive deck and patio areas provide ample space for entertaining guests or enjoying a quiet sunset. The house has state-of-the-art amenities. including a gourmet kitchen, a home theatre, and many guest suites.
Sustainable Features
Leonardo DiCaprio is a well-known environmental activist. whose Malibu house reflects his commitment to sustainability. The property incorporates solar panels, energy-efficient appliances, and sustainable building materials. The landscaping around the house is also designed to be water-efficient. featuring drought-resistant plants and intelligent irrigation systems.
Leonardo DiCaprio House: Hollywood Hills Hideaway
Privacy and Seclusion
Another remarkable property in Leonardo DiCaprio's collection is his Hollywood Hills house. This secluded retreat offers privacy and tranquility. making it an ideal escape from the hustle and bustle of Los Angeles. The "Leonardo DiCaprio house" in Hollywood Hills nestled among lush greenery. and offers panoramic views of the city and surrounding landscapes.
Design and Amenities
The Hollywood Hills house is a mid-century modern gem characterized by its sleek design and floor-to-ceiling windows. The open-concept living space is perfect for entertaining. while the cozy bedrooms provide a comfortable retreat. The property also features a swimming pool, and outdoor dining area. and a spacious deck that overlooks the cityscape.
Environmental Initiatives
The Hollywood Hills house incorporates several green features that are in line with DiCaprio's environmental values. The home has solar panels, energy-efficient lighting, and a rainwater harvesting system. Additionally, the landscaping designed to support local wildlife and promote
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2. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 2, April 2018 : 867 – 879
868
as MPPT [4], proposition ANFIS as energy losses predicament [5], peak load predicament [6], and wind
power plant MPPT [8-11]. However, none of them was implemented in the actual PV plant system.
Therefore, none of them have results compared against results collected from PV plant. Numerous articles
have demonstrated the flexibility of the ANFIS method, although not directly related to PV systems, but were
instead: compared against the Neural Network in laboratory conditions [7], used in the role of Expert system
for steel grading [8], and integrated bidirectional subsystem MPPT [17]. The articles that have focused on the
comparison of the ANFIS method with some other Artificial Intelligence (AI) methods such as the Neural
Networks (NN), Genetic Algorithm (GA), proved that ANFIS is the most suitable for use in uncertain
systems [17] and without a doubt presented ANFIS as the most suitable algorithm for MPP tracking.
Previous work also presents ANFIS as multilevel cascade inverter for PV systems [18] concluding the quality
of the methods in predicting MPP in a simulated environment. In the past four years, numerous articles and
reports addressed the simulations of PV cells and consequently of PV modules, and served as the basis for
developing authentic models for further research. Type-2 Fuzzy logic controller [10], PV MPPT controller
with I-V and P-V curve results [12], comparison with the Fuzzy logic controller [13], standalone complex PV
system with MPPT controller [14], trained ANFIS and Fuzzy logic controller according to Perturb and
Observe (P&O) algorithm [16]. The papers that dealt with ANFIS in detail, considering all layers and
training methods, opened the path to use ANFIS as the method to resolve all insufficiently defined problems
with a high rate of uncertainty in conclusions [2-4], [21]. The MPPT algorithm is, in general, already
integrated in DC-AC inverters, so that all algorithms for managing control systems are locked and cannot be
modified, and which are known: Perturb and Observe (P&O) and Incremental Conductance (InCond), or
both, are installed in the MPPT algorithm. Many researchers have embedded the ANFIS algorithm in the
filed-programmable gate array (FPGA) [2], [6].
This paper deals with ANFIS as an MPPT algorithm in an actual 10 kW PV system used for electricity
generation, which has the role of a distributed generation (DG) source of energy, i.e. it feeds all generated
energy into the distribution system operator [1]. The specifications of the actual PV system installed on the
roof, which are important for the simulation, are presented in Section 2. Taking samples from the inverters,
„teaching‟ and training the algorithm in ANFIS structure, its block diagram and modelling of the actual
system is presented in Section 3. Basics of ANFIS architecture and algorithm, simulations with the data from
the actual measurements, the comparison of the obtained results and discussion are contained in Section 4.
Section 5 contains the conclusion drawn from the simulation results.
2. SAMPLING AND SYSTEM MODELLING
2.1. PV System
The properties of the PV system taken into account in the process of designing the model include
THDU (Total Harmonic Distortion of Voltage), which is addressed in the article referred to under references,
DC Voltage characteristics based on PV modules model provided by in-field measurement, P-V and I-V
graphs provided by calculations of string connected PV modules. THD is installed in a three-level PWM
signal generator where the impact on voltage distortion is defined. The set THDU is 1.48% presented in
Figure 1 for voltage frequency scan.
Figure 1. Total harmonic voltage distortion - THDU.
The analysis of the field measurements in the PV system established that there was no reactive
power exchange between the PV system and the distribution network, so no simulation of a reactive power
3. Int J Elec & Comp Eng ISSN: 2088-8708
ANFIS used as a Maximum Power Point Tracking Algorithm for a Photovoltaic System (Dragan Mlakić)
869
source (Q) was used. The measuring point from which the data for subsequent analysis was taken is the
identical location of the actual PV system at the point of power exchange between the PV array and the
distribution network. The size of the sample for analysis is Ts=10-6
so that the sinusoid is clearly visible, as
well as all transients in the operation of the DC-DC stabilizer. All components used in the simulation are set
up on the basis of the actual results of the system output, so that transients are presented as realistically as
possible. As in Section 2, the modules in the simulation are arranged accordingly: in 4 rows for each inverter
and of the same type as in the actual PV system. P-V and I-V module specifications are shown in Figure 2.
Figure 2. P-V and I-V characteristics of the entire PV system
In order to limit the inverter power output, a three-phase 10 kVA AC-AC transformer was installed
on the array, immediately at the outlet of the PV system to the distribution network. The consumer
representing the distribution network as an energy-using device was simulated using the RLC line parameters
P= 15 kW, QL=0 kVAr, QC=0 kVAr. Since QL and QC do not participate in the consumption from the PV
system, as there is no reactive power exchange, their value was set as 0 kVAr. The frequency of the PV
system during the entire simulation was in the range 49.96 Hz – 50.05 Hz, which complies with the HRN EN
50160 electric power quality standard. Adjustment to the mains voltage of the distribution network was
simulated with the constant 230 V voltage on the inlet to the PWM signal generator.
2.2. ANFIS Algorithm
Neuro-fuzzy method is important in the designing of fuzzy expert systems. In any case, the right
selection of the number, type, rules and parameters of the fuzzy system Membership Functions (MFs) is vital
for acquiring the minimum performance. Trial and error is the method to achieve the minimum performance.
This fact emphasizes the weight of settings of the fuzzy systems. ANFIS is a Sugeno network within the
adaptive systems facilitating learning and training. That framework makes models more systematic and uses
expert knowledge so that user does not have to be an expert. For better understanding the ANFIS
architecture, consider the following fuzzy system which has two rules, two inputs, and therefore is a first
order Sugeno model:
Rule 1: If (x is A1) and (y is B1) then (f1 = p1x + q1 + r1) (1)
Rule 2: If (x is A2) and (y is B2) then (f2 = p2x + q2 + r2) (2)
Literature proposes several types of reasoning of Sugeno fuzzy systems [11]. Based on type of fuzzy
reasoning and if-then rules, there are three types of fuzzy inference systems mostly used:
a. Depending on rule‟s strength, the overall output is the weighted average of each rule‟s crisp
output (the product or minimum of the degrees of match with the premise part) and MFs. The
output membership function used in this example is a monotonic function.
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b. The output of fuzzy system is obtained by applying “maximum” operation to the certified
fuzzy outputs (each is equal to the minimum of scoring result and the output membership
function of each rule). Diverse schemes have been presented to obtain the final (crisp) output
based on the main fuzzy output; some of them are centroid of area (CoA), bisector of area
(BoA), mean of max (MoM), etc. [11].
c. Takagi-Sugeno “if-the” rules are used for the purposes of this paper. Linear combination of
fuzzy input variables plus a constant term are used for output of each rule, and the ultimate
output is the average weight of output from every rule. One of the ANFIS architectures is the
implementation of these two rules as shown in Figure 3. A circle represents a fixed node, as
presented in Figure 3, a square indicates an adaptive node (the parameters are changing during
training with back propagation or hybrid method of learning).
Figure 3. ANFIS architecture
Layer 1: Nodes in this layer are adaptive nodes. The output of each node is the degree of
membership of the input of the fuzzy membership functions represented by the node. Expressions for
obtaining those outputs are:
O1,I = µAi(x) i=1,2 (3)
O1,I = µBi(x) i=3,4 (4)
where, Ai and Bi are any suitable fuzzy sets in parametric form, and O1,i is the output of the node in the i-th
layer. This paper uses trapezoidal shape MFs.
Layer 2: The nodes in this layer are fixed (not adaptive) and therefore are called a Neural Network
layer. They are signed with Π to indicate that they play the role of a multiplier function of inputs. Outputs
from this node are presented in expression (5).
O2,i = Wi =µAi(x)µBi(y) i=1,2 (5)
Layer 3: The nodes in this layer are also fixed nodes. They are signed with N to indicate that they
perform a normalization of the scoring strength from the previous layer. Output from this node is given
in (6).
̅̅̅̅ (6)
Layer 4: All the nodes in this layer are adaptive nodes, and therefore this layer is a Fuzzy logic
layer. The output of each node is simply the product of the normalized scoring strength and a first order
polynomial function. Output from each node from this layer is presented in (7).
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O4,I = fi = (pix + qiy + ri) i=1,2 (7)
Layer 5: This layer has one node signed with S to indicate simple summarization in this layer.
∑ ̅ ∑
∑ ̇
(8)
The ANFIS architecture is not unique. Combination of some layers can be still produce the same
output instead. In ANFIS architecture, there are two adaptive layers (Layers 1 and 4, Fuzzy layers). Layer 1
has three alterable parameters (ai, bi and ci) referring to the input of MFs. These parameters are called
premise parameters. Layer 4 also has three alterable parameters (pi, qi and ri) referring to the first order
polynomial function. These parameters are consequent parameters. The task of the training or learning
algorithm for this architecture is to tune all the alterable parameters to make the ANFIS output match the
training data as much as they can.
3. MPPT WITH THE ANFIS ALGORITHM
Representation of the entire modelled actual PV System presented in Figure 4 with its components
marked.
Figure 4. Actual modelled PV system diagram
Marked with a red ellipse is the DC-DC converter with the purpose of regulating output DC voltage
according to the ANFIS MPPT controller marked with another red ellipse. ANFIS controller works according
to input values of Temperature (o
C) and sun irradiance (W/m2
) based on trained .fis file. Another detail is
voltage control for outside voltage regulation based on user input working with the PWM signal generator.
The above mentioned are input for DC/AC inverter based on diode switching gear with set up dip and swell
voltage regulation. The next red ellipse is the AC/AC 10 kW power transformer used for power limiting
output and voltage regulation on AC side. The last two red ellipses are the measurement place for output
results and the Distribution network with simulated RLC consumer.
The explanation for creating and the levels comprising the ANFIS cognitive method has been
described in numerous earlier articles in bibliography [8], [10-13], [15], [17] and [18-22]. The creation of the
ANFIS MPPT algorithm was applied with the data recorded directly from the power exchange point between
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the PV system and the distribution network. The following data were used:
a. Hours of solar exposure (irradiance),
b. Ambient temperature per hour,
Humidity is not considered in this paper. The output power from the system was measured with
regard to the collected values for solar exposure and temperature. The input to the ANFIS algorithm
comprises the data about the solar exposure of PV modules and ambient temperature, and the output is a
nonlinear coefficient as a control signal for the DC-DC stabilizer which maintains voltage in PV modules in
the maximum efficiency range. These points are indicated in Figure 4. Based on the data concerning solar
exposure and temperature, the ANFIS algorithm with its output directly through the DC-DC stabilizer affects
the voltage in PV modules, thus modifying the output power of the PV system. Data on the best sunlit days
for 2015 and 2016 were used to train the ANFIS algorithm, so that all situations in between are within the
scope of ANFIS. Training was performed without the impact of the measured values from the actual PV
system; instead, the simulation was used as the basic model. Training was performed using the following
parameters: 10 training epochs, 6 trapezoidal membership functions. A Hybrid Optimization Model was
used, with error Er=10-6
, shown in Figure 7 are results of the ANFIS MPPT algorithm training. It can be
noticed in Figure 7 that the greatest level of efficiency is when ambient temperature is in the 15o
C - 20o
C
range, with solar irradiation over 900 W/m2
. It is important to note that the temperature that was used as input
for the training of the ANFIS MPPT algorithm is in fact ambient temperature, and solar exposure is
irradiation according to the weather reports. The output power from the PV system as “output” variable is
shown in Figure 5. The ANFIS trained system with Sugeno inference algorithm using two-inputs and one-
output is shown in Figure 6. The membership functions for both inputs and output regarding values are
shown in Figure 7. One can notice in Figure 7 the shape of a trapezoid for individual membership functions
and that is due to users‟ custom shifting. It‟s possible to change shape but the results are considerably
different. View with membership functions of trained system is shown in Figure 8, 2-input, 1-output ANFIS
with layers and membership functions in one image. The number of generated rules for the entire ANFIS
trained system is 72. Also, it is possible to generate more, but complexity of the system makes training last
much longer.
Figure 5. Surface of the functioning of the MPPT algorithm
Figure 6. Two inputs with the Sugeno Inference Model and system output
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Figure 7. Solar exposure with 6 trapezoidal membership functions
Figure 8. ANFIS MPPT system diagram with layers
Figure 9. Left – conventional dual-MPPT system, right – ANFIS MPPT algorithm with two sensors
The MPPT algorithm, which is built in the inverters in Table 2, was not used to train the ANFIS
MPPT algorithm. This means that the ANFIS MPPT algorithm “learns” independently from the existing
MPPT algorithm in inverters, and the final result of its activity provides the output to the DC-DC stabilizer
which regulates DC voltage of the modules. The company, which produces installed inverters, uses a Dual-
MPPT system to connect modules. This system requires that two separate connections be used to connect PV
modules facing different directions: east and west. This results in greater efficiency of all modules.
The Dual MPPT connection system to the same row of PV modules ensures separate operation in
the case of defect on an individual module, thus maintaining the maximum efficiency of the entire PV array.
Using a single ANFIS MPPT algorithm to which all PV modules are connected regardless of their tilt angle
or azimuth, it is possible to switch from one row of modules to the other using the universal solar irradiance
meter. This would have the same effect as a Dual-MPPT system, without having to change the DC/AC
inverter, but requires two additional inputs, as shown in Figure 9. Since training of the ANFIS MPPT
algorithm is unique for each PV array, this would cover all the costs of additional material, while such costs
are unavoidable in the case of the classic MPPT algorithms in a Dual-MPPT system.
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4. CASE SAMPLE AND SIMULATION RESULTS
The 9.59 kW solar photovoltaic modules for electricity generation are installed with a 30° tilt angle
on the south slope of the roof of a house in Špansko, a neighborhood in Zagreb. The system works parallel
with the distribution network, and it is used to supply electricity to the appliances in the family house, while
any excess electricity is fed into the power grid. During the period when the solar modules do not generate
sufficient electricity, power to the appliances is supplied by electricity from the grid. Having regard to the
fact that peak energy generation of the installed PV system is during mid-day, it meets approximately 50 %
of own demand while the remainder is fed into the electric power distribution network [1]. The photovoltaic
system consists of 56 modules mounted on the roof of a house, distributed in four rows with a 30° tilt angle,
with three rows comprising 14 modules, where the rated power per module is 170 W, and one row
comprising 14 modules with rated power per module of 175 W.
The entire PV system contains 56 PV modules with total power of 9.59 kWp. The specifications of
the installed modules presented in Table 1. Eleven (11) modules are connected in series to individual
inverters (overall three such inverters). The remaining 9 modules are connected in series and the added 14
new modules are also connected in series to the fourth inverter. The rated power of the three inverters is
3000 VA respectively, and one inverter has the power of 4200 VA [1].
Table 1. PV modules data
Technical data
PV strings 1,
2, 3 PV string 4
Maximum power Pmax 170 175 W
Maximum power voltage Ump 36 35,4 V
Maximum power current Imp 4,72 4,9 A
Short-circuit current Isc 5 5,5 A
Open circuit voltage Uoc 44,2 44,3 V
Maximum system voltage 600 600 V
Dimensions 1593 x 790 x 50 mm
Mass 15.4 15.4 kg
Number of modules 42 14 pcs
The PV system comprises three installed solar inverter units of 3000 VA, and one unit of 4200 VA,
whose specifications are listed in Table 2 [1].
Table 2. Inverter strings data.
Technical data
PV string
inverter
PV string
inverter
Input
Maximum PV Ppv 4100 W
Maximum DC power PDC, max 3250 4400 W
Maximum DC voltage UDC, max 600 750 V
PV voltage, MPP-range UPV 232-550 125-750 V
Maximum current IPV. Max 12 11 A
DC noise voltage USS <10 <10 %
Maximum No. in a series (parallel) 3 2
Output
Maximum AC power PAC, max 3000 4200 W
AC rated power PAC, nom 2750 4000 W
Total current harmonic distortion <4 <4 %
Operating range, grid voltage UAC 198-260 198-260 V
Rated range, grid voltage 180-265 180-265 V
AC power frequency fAC 49,8-50,2 49,8-50,2 Hz
Rated power frequency 45,5-54,5 45,5-54,5 Hz
Feed-in phase cos φ 1 1
Simplified block diagram of the PV system connection to the low voltage distribution network, is
shown in Figure 10. According to Figure 1, marketed place of measurement, “Energy meter”, from which the
gathered data are used in this paper, is in place between plant and distribution network.
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Figure 10. Block diagram of PV modules and inverters.
An algorithm for maximum Power Point Tracking imbedded in PV string inverters is not provided
by the manufacturer and the assumption is that inverters are using one of most popular methods: Perturb &
Observe or Incremental Conductance. Some manufacturers implement both methods combined in one or
more MPPT controllers, but in this case it uses more than one controller for string modules at a different
angle. The PV system that was considered in this paper, on the roof of house is oriented to the east with 30o
azimuth, presented in Figure 11.
Figure 11. PV system installed on the house roof (Google Maps)
Following the training of the ANFIS MPPT algorithm, a simulation was launched with the activated
ANFIS MPPT algorithm as shown in Figure 1. The input data concerning solar exposure and temperature
were taken from the weather forecast for that day. The results obtained in the simulation were compared to
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the measured power values on the actual PV system from the online portal to which the PV system is linked.
The testing was conducted over a period of 18 chosen days. Due to the extensiveness of the obtained results,
only 12 days are presented. The results over 12 days are presented in Table 4 and Table 5. The generated day
power curve of simulation is shown in Figure 12 and Figure 13. Together with the measured power of the
inverter and irradiance. As can be seen, the ANFIS MPPT performs better than the installed MPPT
algorithm. Sunny day sample based on on-site measurements and compared against the results from designed
model is presented in Figure 12 together with sunlight irradiance. Same analogy for cloudy days is presented
in Figure 13 also with sunlight irradiance. Based on presented graphs, both Figure, 12 and Figure 13, show
results as presented in Table 3.
Table 3. Sunny day and cloudy day results
Difference
ANFIS Inverter kW %
Sunny day 49.91 kW 48.52 kW 1.38 2.78
Cloudy day 30.32 kW 28.67 kW 1.65 5.46
Figure 12. Comparison of the power curve for a sunny day of sampling and results from model
Figure 13. Comparison of the power curve over a cloudy day of sampling and results from model
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Table 4. 12-day sampling test results
Date Method/Units 6:00 AM – 09:00 AM;
Percentage difference
[%]
1.4.2016
ANFIS [kW] 62.892
18.27
Inverter [kW] 51.397
1.5.2016
ANFIS [kW] 65.800
2.49
Inverter [kW] 64.157
1.7.2016
ANFIS [kW] 61.010
7.51
Inverter [kW] 56.426
1.10.2015
ANFIS [kW] 51.299
3.,30
Inverter [kW] 34.728
6.2.2016
ANFIS [kW] 53.152
16.38
Inverter [kW] 44.444
10.9.2016
ANFIS [kW] 57.573
17.45
Inverter [kW] 47.524
13.6.2016
ANFIS [kW] 63.787
41.72
Inverter [kW] 37.170
13.9.2016
ANFIS [kW] 57.573
15.24
Inverter[kW] 48.795
14.1.2016
ANFIS[kW] 48.172
64.88
Inverter [kW] 16.916
18.3.2016
ANFIS[ kW] 61.275
6.28
Inverter [kW] 57.424
24.1.2016
ANFIS [kW] 48.172
33.75
Inverter [kW] 31.913
29.6.2016
ANFIS [kW] 63.787
7.06
Inverter [kW] 59.278
Table 5. Sum total of sampling results over 12 days
12 days test Difference
ANFIS [kW] Inverter [kW] kW %
694.492 550.172 144.320 20.78
From the results shown, it is obvious that the ANFIS MPPT performs better by 20.78 % than the
conventional algorithm in inverters to obtain the point of maximum efficiency of PV modules. This results
should not be taken for granted, because this experiment did not take into consideration non measurable
situations like cleaning of PV panels, birds and other animals making shadows, unpredictable malfunctions in
equipment, etc. The actual meteorological conditions that could not be tested in the simulation, and which
affect the behavior of the PV system, should be taken into consideration. Besides, account should be taken of
the greater complexity of the actual system, which comprises the position of the inverter (its heating up,
exploitation period), cross-section of DC distribution wiring, energy-consuming devices connected before the
meter of the output power from the PV system to the distribution network. As can be seen in Figure 8, the
actual PV system is turned slightly to the west compared to the simulated system, which is ideally positioned
between the east and west. This difference can be easily eliminated with a mathematical operation, so that the
simulation results remain the same.
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5. CONCLUSION
This work proves that ANFIS as a method meets the requirements of a PV system to use the MPPT
algorithm. It should be underlined that the benefits of ANFIS as an MPPT method are multiple: sampling is
not aggressive because it measures the values unrelated to the output of the PV system, voltage and
electricity (U and I), a very smooth and fast response to voltage fluctuations, it is irrelevant which materials
the PV system is made from, mobility from one system to another subject to additional training, universal for
any type of inverter as stated in Section 3, simple implementation of the Dual-MPPT method with additional
training. The importance of research done in this paper is a comparison of a real life example MPPT
controller with the ANFIS modelled system, and concrete results that are presented in Table 4 and Table 5.
As required by the presented results, there is a next step in this research. The next step in research is to train
the ANFIS MPPT algorithm over several additional days of sampling and to apply it as a Dual-MPPT
algorithm in a simulation. In addition, this conclusion has to be demonstrated by actually connecting the
ANFIS MPPT algorithm to the actual PV system.
ACKNOWLEDGEMENTS
We would like to thank the owner of PV power plant and Mariomont company for their valuable
data.
REFERENCES
[1] K. Fekete; Z. Klaić; Lj. Majdandzic, “Expansion of the residential photovoltaic systems and its harmonic impact on
the distribution grid”, Renewable Energy an International Journal, November 2011.
[2] S. Selvan, P. Nair, U. Umayal, “A Review on Photo Voltaic MPPT Algorithms”, International Journal of
Electrical and Computer Engineering (IJECE), Vol.6 No.2. April 2016.
[3] A. A. Kulaksız, “ANFIS-based estimation of PV module equivalent parameters: application to a stand-alone PV
system with MPPT controller”, November 2013, Turkish Journal of Electrical Engineering & Computer Sciences,
(2013) 21: 2127 – 2140.
[4] D. Mlakić; S. Nikolovski. “ANFIS as a Method for Determinating MPPT in the Photovoltaic System Simulated in
Matlab/Simulink”, 39 th International convention on information and communication technology, electronic and
microelectronic MIPRO 2016, Opatija, Croatia, 2015.
[5] D. Mlakić, S. Nikolovski, G. Knežević, “An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical
Losses in Distribution Networks”, International Journal of Electrical and Computer Engineering (IJECE), Vol. 6,
No 3, June 2016.
[6] A. Draidi, D. Labed, “A Neuro-fuzzy Approach for Predicting Load Peak Profile”, International Journal of
Electrical and Computer Engineering (IJECE), Vol. 5, No 6, December 2015,
[7] S. S. Letha; T. Thakur; J. Kumar; D. Karanjkar; S. Chatterji, “Design and Real Time Simulation of Artificial
Intelligent based MPP Tracker for Photo-Voltaic System”, International Mechanical Engineering Congress and
Exposition IMECE2014, November 2014.
[8] M. H. F. Zarandi et al, “A Multi-Agent Expert System for Steel Grade Classification Using Adaptive Neuro-fuzzy
Systems”, Expert Systems InTech, Petrica Vizureanu (Ed.)
[9] A. Rezvani; M. Izadbakhsh; M. Gandomkar, “Enhancement of hybrid dynamic performance using ANFIS for fast
varying solar radiation and fuzzy logic controller in high speeds wind”, Journal of Electrical Systems (JES),
December 2014.
[10] F. Bendary; et al, “Genetic-ANFIS Hybrid Algorithm for Optimal Maximum Power Point Tracking of PV Systems”,
MEPCON 2015, 17th International Middle East Power Systems Conference, December 2015.
[11] N. Altin, “Interval Type-2 Fuzzy Logic Controller Based Maximum Power Point Tracking in Photovoltaic
Systems”, Advances in Electrical and Computer Engineering, August 2013.
[12] B. Tarek; D. Said; M.E.H. Benbouzid, “Maximum Power Point Tracking Control for Photovoltaic System Using
Adaptive Neuro- Fuzzy ANFIS”, Eighth International Conference and Exhibition on Ecological Vehicles and
Renewable Energies (EVER), March 2013.
[13] A. M. S. Aldobhani; R. John, “Maximum Power Point Tracking of PV System Using ANFIS Prediction and Fuzzy
Logic Tracking”, Proceedings of the International Multi Conference of Engineers and Computer Scientists
(IMECS) March 2008.
[14] S. S. Mohammed; D. Devaraj; T.P I. Ahamed, “Maximum Power Point Tracking system for Stand-alone Solar PV
power system using Adaptive Neuro-Fuzzy Inference System”, 2016 Biennial International Conference on Power
and Energy Systems, January 2016.
[15] A. Arora; P. Gaur, „Comparison of ANN and ANFIS based MPPT Controller for grid connected PV systems”,
Annual IEEE India Conference (INDICON), 2015
[16] M. A. Enany; M. A. Farahat; A. Nasr, “Modeling and evaluation of main maximum power point tracking
algorithms for photovoltaics systems”, Renewable and Sustainable Energy Reviews, February 2016.
13. Int J Elec & Comp Eng ISSN: 2088-8708
ANFIS used as a Maximum Power Point Tracking Algorithm for a Photovoltaic System (Dragan Mlakić)
879
[17] F. D. Murdianto; O. Penangsang; A. Priyadi, “Modeling and Simulation of MPPT-Bidirectional Using Adaptive
Neuro Fuzzy Inference System (ANFIS) in Distributed Energy Generation System”, Intelligent Technology and Its
Applications (ISITIA), May 2015.
[18] S.L. Shimi; et al, “Mppt Based Solar Powered Cascade Multilevel Inverter”, International Conference on
Microelectronics, Communication and Renewable Energy (ICMiCR-2013), June 2013.
[19] F.M.Bendary; et al, “Optimal Maximum Power Point Tracking of PV Systems based Genetic-ANFIS Hybrid
Algorithm”, International Journal of Scientific & Engineering Research, Volume 7, Issue 4, April 2016.
[20] F. M. Bendarya; et al, “Optimized Genetic-ANFIS Algorithm for Efficient Maximum PowerPoint Tracking of
Photovoltaic Systems”, Shubra Conference, January 2015.
[21] A. Tjahjono; et al, “Photovoltaic Module and Maximum Power Point Tracking Modelling Using Adaptive Neuro-
Fuzzy Inference System”, Makassar International Conference on Electrical Engineering and Informatics (MICEEI),
December 2014.
BIOGRAPHIES OF AUTHORS
Dragan Mlakić, MSc, (IEEE M`2015) was born in Travnik on June 15, 1981. He obtained his
BSc degree (2007) and MSc degree (2013), in electrical engineering at Faculty of Electrical
Engineering, University of Sarajevo, Bosnia and Hercegovina. Presently he works as Engineer in
Electric power company HZ-HB Inc. Mostar, Novi Travnik, Bosnia and Herzegovina and as
Assistant Professor at the Software Engineering Department at Faculty of Information
Technology, University Vitez, Bosnia and Herzegovina. His main interests are artificial
intelligence, expert systems, renewable energy sources, energy quality, energy losses, system
modeling, smart grid.
Ljubomir Majdnandžić PhD.Mech.Eng, was born on July 4, 1960 in Ivanjska at Banja
Luka.He graduated two post studies: in 1999 at the Faculty of Mechanical Engineering and
Naval Architecture University of Zagreb and in 2001 at the Faculty of Economics in Zagreb.
From 2001 to 2003 working on a doctorate at the Fraunhofer Institute for Solar Energy,
Department of electric power systems, in Freiburg, Germany. At the Faculty of Electrical
Engineering and Computing in Zagreb his PhD in 2004. He is Associate Professor of Electrical
Engineering, University of Osijek. Author of 64 scientific and professional work in the field of
energy, renewable energy and sustainable development. He is a member of the International
Solar Energy Society (ISES), the German Society for Solar Energy and the Croatian Energy
Association.
Srete Nikolovski, PhD.El.Eng. (IEEE M‟1995, SM‟2005) was born in Belgrade on October 1,
1954. He obtained his BSc degree (1978) and MSc degree (1989), in electrical engineering at the
Faculty of Electrical Engineering, University of Belgrade and his PhD degree from the Faculty
of Electrical and Computing Engineering, University of Zagreb, Croatia in 1993. Currently he is
a Full Professor at Power Engineering Department at Faculty of Electrical Engineering, J.J.
Strossmayer University in Osijek, Croatia. His main interests are power system protection,
power system modeling, simulation and reliability. He has published over200 technical papers in
journals and international conferences. He is a Senior Member of IEEE Reliability Society, PES
Society and the member of Croatian National Committee of CIGRE.