With the enhanced industrial and domestic energy needs, there is a great urge for renewable energy sources because of their eco-friendly nature. Solar energy is crucial among renewable energy sources and there is a great need to optimize and enhance the performance of solar energy usage that is mainly dependent on the system components. The current work has been aimed to discuss the fault detection of photovoltaic (PV) modules by evaluating an efficient, facile inspection algorithm electrical analysis for real-time applications. The paper presents a real-time experimental model for infrared thermography using a thermal imager mounted on a tripod at a suitable distance from the PV modules to capture the images in the best possible way. A novel hybrid algorithm has been proposed and the fault detection along with the electrical parameter analysis has been accurately performed on the PV modules to analyze and process various externally induced faults in the PV systems.
Performance of low-cost solar radiation loggerIJECEIAES
In solar power systems, irradiance value data are among the most important parameters. Such data can be used in installing photovoltaic (PV) modules, such as determining the exact location, tilt angle, and required area, for optimal power efficiency. In this study, the comprehensive simulation and implementation of a solar radiation meter with a PV cell and temperature sensor are presented. The irradiance measurement value is based on the power reading generated by the small capacity of the PV cell at a specific load converted into a digital value in the microcontroller using the implicit Newton polynomial interpolation (NPI) equation as a low-cost alternative method. The effect of temperature is included in the conversion to obtain precise measurement results. Firstly, the structure and characteristics of the PV cell are discussed. Secondly, the parameters, measuring method, and conversion of the measurement reading data using the NPI equation are presented to assess the results. Finally, the simulation of the solar radiation meter using the PSIM and implementation of the hardware are conducted to validate the concepts and compare their results. The proposed hardware has an average error of 2.72% in the implementation of the measurement test.
This study investigates experimentally the performance of two-dimensional solar tracking systems with reflector using commercial silicon based photovoltaic module, with open and closed loop control systems. Different reflector materials were also investigated. The experiments were performed at the Hashemite University campus in Zarqa at a latitude of 32⁰, in February and March. Photovoltaic output power and performance were analyzed. It was found that the modified photovoltaic module with mirror reflector generated the highest value of power, while the temperature reached a maximum value of 53 ̊ C. The modified module suggested in this study produced 5% more PV power than the two-dimensional solar tracking systems without reflector and produced 12.5% more PV power than the fixed PV module with 26⁰ tilt angle.
This article presents the system design and prediction performance of a 1kW capacity grid-tied photovoltaic inverter applicable for low or medium-voltage electrical distri-bution networks. System parameters, for instance, the longitude and latitude of the solar plant location, panel orientation, tilt and azimuth angle calculation, feasibility testing, optimal sizing of installment are analyzed in the model and the utility is sim-ulated precisely to construct an efficient solar power plant for residential applications. In this paper, meteorological data are computed to discuss the impact of environmen-tal variables. As regards ensuring reliability and sustenance, a simulation model of the system of interest is tested in the PVsyst software package. Simulation results yield that the optimum energy injected to the national grid from the solar plant, specific pro-duction, and performance ratio are 1676kWh/year, 1552kWh/kWp/year, and 79.29% respectively. Moreover, the predicted carbon footprint reduction is 23.467 tons during the 30 years lifetime of the system. Therefore, the performance assessments affirm the effectiveness of the proposed research.
PVPF tool: an automated web application for real-time photovoltaic power fore...IJECEIAES
In this paper, we propose a fully automated machine learning based forecasting system, called Photovoltaic Power Forecasting (PVPF) tool, that applies optimised neural networks algorithms to real-time weather data to provide 24 hours ahead forecasts for the power production of solar photovoltaic systems installed within the same region. This system imports the real-time temperature and global solar irradiance records from the ASU weather station and associates these records with the available solar PV production measurements to provide the proper inputs for the pre-trained machine learning system along with the records’ time with respect to the current year. The machine learning system was pre-trained and optimised based on the Bayesian Regularization (BR) algorithm, as described in our previous research, and used to predict the solar power PV production for the next 24 hours using weather data of the last five consecutive days. Hourly predictions are provided as a power/time curve and published in real-time at the website of the renewable energy center (REC) of Applied Science Private University (ASU). It is believed that the forecasts provided by the PVPF tool can be helpful for energy management and control systems and will be used widely for the future research activities at REC.
Performance of low-cost solar radiation loggerIJECEIAES
In solar power systems, irradiance value data are among the most important parameters. Such data can be used in installing photovoltaic (PV) modules, such as determining the exact location, tilt angle, and required area, for optimal power efficiency. In this study, the comprehensive simulation and implementation of a solar radiation meter with a PV cell and temperature sensor are presented. The irradiance measurement value is based on the power reading generated by the small capacity of the PV cell at a specific load converted into a digital value in the microcontroller using the implicit Newton polynomial interpolation (NPI) equation as a low-cost alternative method. The effect of temperature is included in the conversion to obtain precise measurement results. Firstly, the structure and characteristics of the PV cell are discussed. Secondly, the parameters, measuring method, and conversion of the measurement reading data using the NPI equation are presented to assess the results. Finally, the simulation of the solar radiation meter using the PSIM and implementation of the hardware are conducted to validate the concepts and compare their results. The proposed hardware has an average error of 2.72% in the implementation of the measurement test.
This study investigates experimentally the performance of two-dimensional solar tracking systems with reflector using commercial silicon based photovoltaic module, with open and closed loop control systems. Different reflector materials were also investigated. The experiments were performed at the Hashemite University campus in Zarqa at a latitude of 32⁰, in February and March. Photovoltaic output power and performance were analyzed. It was found that the modified photovoltaic module with mirror reflector generated the highest value of power, while the temperature reached a maximum value of 53 ̊ C. The modified module suggested in this study produced 5% more PV power than the two-dimensional solar tracking systems without reflector and produced 12.5% more PV power than the fixed PV module with 26⁰ tilt angle.
This article presents the system design and prediction performance of a 1kW capacity grid-tied photovoltaic inverter applicable for low or medium-voltage electrical distri-bution networks. System parameters, for instance, the longitude and latitude of the solar plant location, panel orientation, tilt and azimuth angle calculation, feasibility testing, optimal sizing of installment are analyzed in the model and the utility is sim-ulated precisely to construct an efficient solar power plant for residential applications. In this paper, meteorological data are computed to discuss the impact of environmen-tal variables. As regards ensuring reliability and sustenance, a simulation model of the system of interest is tested in the PVsyst software package. Simulation results yield that the optimum energy injected to the national grid from the solar plant, specific pro-duction, and performance ratio are 1676kWh/year, 1552kWh/kWp/year, and 79.29% respectively. Moreover, the predicted carbon footprint reduction is 23.467 tons during the 30 years lifetime of the system. Therefore, the performance assessments affirm the effectiveness of the proposed research.
PVPF tool: an automated web application for real-time photovoltaic power fore...IJECEIAES
In this paper, we propose a fully automated machine learning based forecasting system, called Photovoltaic Power Forecasting (PVPF) tool, that applies optimised neural networks algorithms to real-time weather data to provide 24 hours ahead forecasts for the power production of solar photovoltaic systems installed within the same region. This system imports the real-time temperature and global solar irradiance records from the ASU weather station and associates these records with the available solar PV production measurements to provide the proper inputs for the pre-trained machine learning system along with the records’ time with respect to the current year. The machine learning system was pre-trained and optimised based on the Bayesian Regularization (BR) algorithm, as described in our previous research, and used to predict the solar power PV production for the next 24 hours using weather data of the last five consecutive days. Hourly predictions are provided as a power/time curve and published in real-time at the website of the renewable energy center (REC) of Applied Science Private University (ASU). It is believed that the forecasts provided by the PVPF tool can be helpful for energy management and control systems and will be used widely for the future research activities at REC.
Harvesting solar energy as a renewable energy source has received significant attention through serious studies that could be applied massively. However, the nonlinear nature of photovoltaic (PV) concerning the surrounding environment, especially irradiation and temperature, affects the resulting output. Therefore, the correlation between environmental parameters and PV's energy needs to be studied. This paper presents a design for measuring solar PV parameters monitored on a laboratory scale. The monitoring is based on internet of things (IoT) technology analyzed in realtime. The system was tested in various weather conditions for 18 hours. The results obtained indicate that the output voltage was influenced by the lighting factor of the PV and the surrounding temperature.
Design and performance analysis of PV grid-tied system with energy storage sy...IJECEIAES
With the increasing demand for solar energy as a renewable source has brought up new challenges in the field of energy. However, one of the main advantages of photovoltaic (PV) power generation technology is that it can be directly connected to the grid power generation system and meet the demand of increasing energy consumption. Large-scale PV grid-connected power generation system put forward new challenges on the stability and control of the power grid and the grid-tied photovoltaic system with an energy storage system. To overcome these problems, the PV grid-tied system consisted of 8 kW PV array with energy storage system is designed, and in this system, the battery components can be coupled with the power grid by AC or DC mode. In addition, the feasibility and flexibility of the maximum power point tracking (MPPT) charge controller are verified through the dynamic model built in the residential solar PV system. Through the feasibility verification of the model control mode and the strategy control, the grid-connected PV system combined with reserve battery storage can effectively improve the stability of the system and reduce the cost of power generation. To analyze the performance of the grid-tied system, some realtime simulations are performed with the help of the system advisor model (SAM) that ensures the satisfactory working of the designed PV grid-tied system.
Sizing of Hybrid PV/Battery Power System in Sohag cityiosrjce
This paper gives the feasibility analysis of PV- Battery system for an off-grid power station in Sohag
city. Hybrid PV-battery system was used for supplying a combined pumping and residential load. A simple cost
effective method for sizing stand-alone PV hybrid systems was introduced. The aim of sizing hybrid system is to
determine the cost effective PV configuration and to meet the estimated load at minimum cost. This requires
assessing the climate conditions which determine the temporal variation of the insolation in Sohag city. Sizing
of the hybrid system components was investigated using RETscreen and HOMER programs. The sizing software
tools require a set of data on energy resource demand and system specifications. The energy cost values of the
hybrid system agrees reasonably with those published before.
THERMAL FAULT DETECTION SYSTEM FOR PV SOLAR MODULESelelijjournal
Photovoltaic (PV) modules used to convert sunlight into electricity. PV researches and industries are
rapidly becoming popular in the energy field since PV technologies do not harm to environment and use
sun which is unlimited energy source. Nowadays, many applications are realized with photovoltaic (PV)
modules in different areas such as buildings, aviation, solar power plants, land and sea transportations,
etc. Construction, operation and maintenance of solar PV system are not easy and complex. There are
many methods for PV plants inspection such as visual inspection, using current sensors, comparing the
input and output power units of PV modules, and thermal monitoring with infrared cameras. Monitoring
the differences on the PV module output voltage by means of sensors is the most appropriate methods but it
is very expensive solution since there are thousand PV modules in some plants. Thermal monitoring system
is more suitable method for large PV plants’ inspection. Because, it reduces the fault detection costs and
provide shorten maintenance time. The main aim of this paper is to investigate thermal monitoring of the
PV solar modules and realize image processing by thermal radiation on PV modules. For this purpose, it is
created a wireless directable robotic vehicle which has RF and thermal camera, two brushless hub motor
and X-Bee modules to send direction commands. In this way, the robot moves between the panels and sent
data for user whether there is fault on the panels or not. The test results indicate that PV module faults are
detected effectively by using thermal cameras.
Application of the Least Square Support Vector Machine for point-to-point for...IJECEIAES
In today's industrial world, the growing capacity of renewable energy sources is a crucial factor for sustainable power generation. The application of solar photovoltaic (PV) energy sources, as a clean and safe renewable energy resource has found great attention among the consumers in the recent decades. Accurate forecasting of the generated PV power is an important task for scheduling the generators and planning the consumption patterns of customers to save electricity costs. To this end, it is necessary to develop a global model of the generated power based on the effective factors which are mainly the solar radiation intensity and the ambient weather temperature. As a result of the wide numerical range of these parameters and various weather conditions, a large training database must be used for developing the models, which results in high-computational complexity of the algorithms used for training the models. In this paper, a novel algorithm for point to point prediction of the generated power based on the least squares support vector machine (LS-SVM) has been proposed which can handle the large training database with a very fewer deal of computation and benefits from reasonable accuracy and generalization capability.
The inverter is the principal part of the photovoltaic (PV) systems that assures the direct current/alternating current (DC/AC) conversion (PV array is connected directly to an inverter that converts the DC energy produced by the PV array into AC energy that is directly connected to the electric utility). In this paper, we present a simple method for detecting faults that occurred during the operation of the inverter. These types of faults or faults affect the efficiency and cost-effectiveness of the photovoltaic system, especially the inverter, which is the main component responsible for the conversion. Hence, we have shown first the faults obtained in the case of the short circuit. Second, the open circuit failure is studied. The results demonstrate the efficacy of the proposed method. Good monitoring and detection of faults in the inverter can increase the system's reliability and decrease the undesirable faults that appeared in the PV system. The system behavior is tested under variable parameters and conditions using MATLAB/Simulink.
Distributed energy resources (DER) based micro grid and Nano-grid framework is most technically viable bottom-top approach to sustainably meet ever-increasing demand of rural and urban communities. Recently the growth of DC operative home appliances like mobile and lap top chargers, ovens and hair dryer’s etc. are increasing and therefore a DC/DC converter is an efficient way to meet the electricity need from the local DER and helps in improving the system efficiency. This paper presents simulation results of a buck boost converter, MPPT algorithm (P & O method) for solar PV module and closed loop PI control system for obtaining constant 12 V and 24 V DC output voltage at DC bus. The proposed methodology is to extract maximum DC power from solar PV system and it is directly fed to DC load or DC Nano grid.
Maximum power point tracking based on improved spotted hyena optimizer for s...IJECEIAES
The conventional maximum power point tracking (MPPT) method such as perturb and observe (P&O) under partial shading conditions with non-uniform irradiation, can get trapped on local maximum power point (LMPP) and cannot reach global maximum power point (GMPP). This study proposes a bio-inspired metaheuristic algorithm spotted hyena optimizer (SHO) and improved SHO as a new MPPT technique. The proposed SHO-MPPT and improved SHO-MPPT are used to extract GMPP from solar photovoltaic (PV) arrays operated under uniform irradiation and non-uniform irradiation. Simulation with Powersim (PSIM) and experimental with the emulated PV source were presented. Furthermore, to evaluate the performance of the proposed algorithm, SHO-MPPT is compared with P&O-MPPT and particle swarm optimization (PSO)-MPPT. The SHO-MPPT has an accuracy of 99% and has the good capability, but there are power fluctuations before reaching MPP. Therefore, improved SHO-MPPT was developed to get better results. The improved SHO-MPPT proved high accuracy of 99% and faster than SHO-MPPT and PSO-MPPT in tracking the maximum power point (MPP). Furthermore, there are minor power fluctuations.
Analysis, Modeling and Implementation of Incremental Conductance Maximum Powe...ijtsrd
Maximum power point tracking must be used in PV systems to get the most of solar energy. A solar cells property is non linear. The intensity of solar radiation falling on the earths surface is affected by a variety of elements including clouds, water vapour, pollution, absorption, scattering, and climate conditions. A PV system without MPPT seldom generates maximum power, which also affects the Maximum Power Point of the PV system with regard to a certain environmental situation, resulting in low power. In order to monitor PV systems MPP Incremental conductance IC method gives greater steady state accuracy with better and efficient output compared to non MPPT system. Several simulation results are shown here. Reetu Kalbhor | Priyanka Kamdar | Dr. Geetam Richhariya | Neeti Dugaya "Analysis, Modeling and Implementation of Incremental Conductance Maximum Power Point Tracking" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-7 , December 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52544.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/52544/analysis-modeling-and-implementation-of-incremental-conductance-maximum-power-point-tracking/reetu-kalbhor
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.
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Harvesting solar energy as a renewable energy source has received significant attention through serious studies that could be applied massively. However, the nonlinear nature of photovoltaic (PV) concerning the surrounding environment, especially irradiation and temperature, affects the resulting output. Therefore, the correlation between environmental parameters and PV's energy needs to be studied. This paper presents a design for measuring solar PV parameters monitored on a laboratory scale. The monitoring is based on internet of things (IoT) technology analyzed in realtime. The system was tested in various weather conditions for 18 hours. The results obtained indicate that the output voltage was influenced by the lighting factor of the PV and the surrounding temperature.
Design and performance analysis of PV grid-tied system with energy storage sy...IJECEIAES
With the increasing demand for solar energy as a renewable source has brought up new challenges in the field of energy. However, one of the main advantages of photovoltaic (PV) power generation technology is that it can be directly connected to the grid power generation system and meet the demand of increasing energy consumption. Large-scale PV grid-connected power generation system put forward new challenges on the stability and control of the power grid and the grid-tied photovoltaic system with an energy storage system. To overcome these problems, the PV grid-tied system consisted of 8 kW PV array with energy storage system is designed, and in this system, the battery components can be coupled with the power grid by AC or DC mode. In addition, the feasibility and flexibility of the maximum power point tracking (MPPT) charge controller are verified through the dynamic model built in the residential solar PV system. Through the feasibility verification of the model control mode and the strategy control, the grid-connected PV system combined with reserve battery storage can effectively improve the stability of the system and reduce the cost of power generation. To analyze the performance of the grid-tied system, some realtime simulations are performed with the help of the system advisor model (SAM) that ensures the satisfactory working of the designed PV grid-tied system.
Sizing of Hybrid PV/Battery Power System in Sohag cityiosrjce
This paper gives the feasibility analysis of PV- Battery system for an off-grid power station in Sohag
city. Hybrid PV-battery system was used for supplying a combined pumping and residential load. A simple cost
effective method for sizing stand-alone PV hybrid systems was introduced. The aim of sizing hybrid system is to
determine the cost effective PV configuration and to meet the estimated load at minimum cost. This requires
assessing the climate conditions which determine the temporal variation of the insolation in Sohag city. Sizing
of the hybrid system components was investigated using RETscreen and HOMER programs. The sizing software
tools require a set of data on energy resource demand and system specifications. The energy cost values of the
hybrid system agrees reasonably with those published before.
THERMAL FAULT DETECTION SYSTEM FOR PV SOLAR MODULESelelijjournal
Photovoltaic (PV) modules used to convert sunlight into electricity. PV researches and industries are
rapidly becoming popular in the energy field since PV technologies do not harm to environment and use
sun which is unlimited energy source. Nowadays, many applications are realized with photovoltaic (PV)
modules in different areas such as buildings, aviation, solar power plants, land and sea transportations,
etc. Construction, operation and maintenance of solar PV system are not easy and complex. There are
many methods for PV plants inspection such as visual inspection, using current sensors, comparing the
input and output power units of PV modules, and thermal monitoring with infrared cameras. Monitoring
the differences on the PV module output voltage by means of sensors is the most appropriate methods but it
is very expensive solution since there are thousand PV modules in some plants. Thermal monitoring system
is more suitable method for large PV plants’ inspection. Because, it reduces the fault detection costs and
provide shorten maintenance time. The main aim of this paper is to investigate thermal monitoring of the
PV solar modules and realize image processing by thermal radiation on PV modules. For this purpose, it is
created a wireless directable robotic vehicle which has RF and thermal camera, two brushless hub motor
and X-Bee modules to send direction commands. In this way, the robot moves between the panels and sent
data for user whether there is fault on the panels or not. The test results indicate that PV module faults are
detected effectively by using thermal cameras.
Application of the Least Square Support Vector Machine for point-to-point for...IJECEIAES
In today's industrial world, the growing capacity of renewable energy sources is a crucial factor for sustainable power generation. The application of solar photovoltaic (PV) energy sources, as a clean and safe renewable energy resource has found great attention among the consumers in the recent decades. Accurate forecasting of the generated PV power is an important task for scheduling the generators and planning the consumption patterns of customers to save electricity costs. To this end, it is necessary to develop a global model of the generated power based on the effective factors which are mainly the solar radiation intensity and the ambient weather temperature. As a result of the wide numerical range of these parameters and various weather conditions, a large training database must be used for developing the models, which results in high-computational complexity of the algorithms used for training the models. In this paper, a novel algorithm for point to point prediction of the generated power based on the least squares support vector machine (LS-SVM) has been proposed which can handle the large training database with a very fewer deal of computation and benefits from reasonable accuracy and generalization capability.
The inverter is the principal part of the photovoltaic (PV) systems that assures the direct current/alternating current (DC/AC) conversion (PV array is connected directly to an inverter that converts the DC energy produced by the PV array into AC energy that is directly connected to the electric utility). In this paper, we present a simple method for detecting faults that occurred during the operation of the inverter. These types of faults or faults affect the efficiency and cost-effectiveness of the photovoltaic system, especially the inverter, which is the main component responsible for the conversion. Hence, we have shown first the faults obtained in the case of the short circuit. Second, the open circuit failure is studied. The results demonstrate the efficacy of the proposed method. Good monitoring and detection of faults in the inverter can increase the system's reliability and decrease the undesirable faults that appeared in the PV system. The system behavior is tested under variable parameters and conditions using MATLAB/Simulink.
Distributed energy resources (DER) based micro grid and Nano-grid framework is most technically viable bottom-top approach to sustainably meet ever-increasing demand of rural and urban communities. Recently the growth of DC operative home appliances like mobile and lap top chargers, ovens and hair dryer’s etc. are increasing and therefore a DC/DC converter is an efficient way to meet the electricity need from the local DER and helps in improving the system efficiency. This paper presents simulation results of a buck boost converter, MPPT algorithm (P & O method) for solar PV module and closed loop PI control system for obtaining constant 12 V and 24 V DC output voltage at DC bus. The proposed methodology is to extract maximum DC power from solar PV system and it is directly fed to DC load or DC Nano grid.
Maximum power point tracking based on improved spotted hyena optimizer for s...IJECEIAES
The conventional maximum power point tracking (MPPT) method such as perturb and observe (P&O) under partial shading conditions with non-uniform irradiation, can get trapped on local maximum power point (LMPP) and cannot reach global maximum power point (GMPP). This study proposes a bio-inspired metaheuristic algorithm spotted hyena optimizer (SHO) and improved SHO as a new MPPT technique. The proposed SHO-MPPT and improved SHO-MPPT are used to extract GMPP from solar photovoltaic (PV) arrays operated under uniform irradiation and non-uniform irradiation. Simulation with Powersim (PSIM) and experimental with the emulated PV source were presented. Furthermore, to evaluate the performance of the proposed algorithm, SHO-MPPT is compared with P&O-MPPT and particle swarm optimization (PSO)-MPPT. The SHO-MPPT has an accuracy of 99% and has the good capability, but there are power fluctuations before reaching MPP. Therefore, improved SHO-MPPT was developed to get better results. The improved SHO-MPPT proved high accuracy of 99% and faster than SHO-MPPT and PSO-MPPT in tracking the maximum power point (MPP). Furthermore, there are minor power fluctuations.
Analysis, Modeling and Implementation of Incremental Conductance Maximum Powe...ijtsrd
Maximum power point tracking must be used in PV systems to get the most of solar energy. A solar cells property is non linear. The intensity of solar radiation falling on the earths surface is affected by a variety of elements including clouds, water vapour, pollution, absorption, scattering, and climate conditions. A PV system without MPPT seldom generates maximum power, which also affects the Maximum Power Point of the PV system with regard to a certain environmental situation, resulting in low power. In order to monitor PV systems MPP Incremental conductance IC method gives greater steady state accuracy with better and efficient output compared to non MPPT system. Several simulation results are shown here. Reetu Kalbhor | Priyanka Kamdar | Dr. Geetam Richhariya | Neeti Dugaya "Analysis, Modeling and Implementation of Incremental Conductance Maximum Power Point Tracking" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-7 , December 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52544.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/52544/analysis-modeling-and-implementation-of-incremental-conductance-maximum-power-point-tracking/reetu-kalbhor
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%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Cosmetic shop management system project report.pdf
An efficient optical inspection of photovoltaic modules deploying edge detectors and ancillary techniques
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 12, No. 5, October 2022, pp. 4772~4781
ISSN: 2088-8708, DOI: 10.11591/ijece.v12i5.pp4772-4781 4772
Journal homepage: http://ijece.iaescore.com
An efficient optical inspection of photovoltaic modules
deploying edge detectors and ancillary techniques
Kummara Venkata Guru Raghavendra, Nutakki Tirumala Uday Kumar, Waqarullah Kazim
RAK Research and Innovation Centre, American University of Ras Al Khaimah, Ras Al Khaimah, United Arab Emirates
Article Info ABSTRACT
Article history:
Received May 2, 2021
Revised May 25, 2022
Accepted Jun 9, 2022
With the enhanced industrial and domestic energy needs, there is a great
urge for renewable energy sources because of their eco-friendly nature. Solar
energy is crucial among renewable energy sources and there is a great need
to optimize and enhance the performance of solar energy usage that is
mainly dependent on the system components. The current work has been
aimed to discuss the fault detection of photovoltaic (PV) modules by
evaluating an efficient, facile inspection algorithm electrical analysis for
real-time applications. The paper presents a real-time experimental model
for infrared thermography using a thermal imager mounted on a tripod at a
suitable distance from the PV modules to capture the images in the best
possible way. A novel hybrid algorithm has been proposed and the fault
detection along with the electrical parameter analysis has been accurately
performed on the PV modules to analyze and process various externally
induced faults in the PV systems.
Keywords:
Electrical parameter analysis
Fault detection
Performance
Photo voltaic modules
Renewable energy
This is an open access article under the CC BY-SA license.
Corresponding Author:
Nutakki Tirumala Uday Kumar
RAK Research and Innovation Centre, American University of Ras Al Khaimah
Ras Al Khaimah, PO Box: 31208, United Arab Emirates
Email: uday.kumar@aurak.ac.ae
1. INTRODUCTION
Industrial revolution 4.0 has dramatized the energy demand of industrial and domestic utilities. The
aim of fulfilling the demand needs to be reconsidered as the depletion of fossil fuels is more. The solution is
simple and lucid to rely on renewable energy resources such as solar photovoltaic (PV), wind, and tidal.
Among them, the scope of research for solar PV is more commending. PV power generation plants have
attained predominant attention because of their high potential and promising aspect of exploiting renewable
solar energy. The fundamental component of PV power generation is a solar cell which forces the electrons
to move through light absorption and causes the current flow. The metal contacts placed at the top and
bottom of the solar cell collect the current. The cell voltage and the current offer the power. Certain factors
influence the amount of electricity produced i.e. module composition, type, and the installation combined
effect [1]. Solar irradiance is a crucial element to maintain the PV module’s heat balance, power output,
convective and radiative heat exchanges [2]. The major limitations are uncertain solar irradiance that leads to
fluctuation of temperatures in the PV modules [3], [4]. For instance, PV modules of crystalline kind suffer a
0.5% loss of efficiency when there is a 1 C rise in temperature. The abnormal weather conditions lead to
fluctuations in voltage and frequency creating complications in the power systems operation and
maintenance. In other perspectives, the variable loads can adjust themselves based on real-time onset points
[5]–[7].
Solar PV modules provide power to the utilities like buildings, homes, and many more applications.
Before the enhanced demand and the world energy needs, there is a continuous need for research and
2. Int J Elec & Comp Eng ISSN: 2088-8708
An efficient optical inspection of photovoltaic modules deploying … (Kummara Venkata Guru Raghavendra)
4773
development in this field. The optimum usage of renewable energy resources is a crucial point to reduce the
environmental perilous effects [8]. Due to the technological advancements and ample competitors in the
market reduced the production cost of the solar PV modules enabling rigorous installations by the consumers.
The tremendous spread and distribution of the PV modules have not only depreciated the installation of PV
plants but also providing the best return on investments for consumers [8]. Government organizations and
autonomous entrepreneurs have also vested much in renewable energy resources such as solar PV for
modernized technological applications [9], [10]. Hence to obtain the better performance of a PV system,
optimizing energy, money and mimicking the hazardous effects through fault diagnosis is a crucial procedure
to be adopted at an early stage.
The most common faults at the time of manufacturing are delamination, junction box malfunction
that can lead to high resistance, abnormal heating, and the breakage of the frame. There are also certain
external faults such as connectors failure, clamping, transport, and installation failures [11]. Other faults
related to the PV module include hotspots due to the panel behaving abnormally like load and electrical
problems in bypass diode or a shunt resistor, anti-reflective aging, bubbles in between the Tedlar and beneath
the panel [12]. To identify the faults in the PV modules, infrared imaging is a technology that captures
invisible infrared images and converts them into visible images. The PV modules inspection and fault
detection play a major role in getting optimized and efficient power from the PV systems by reducing the
maintenance costs through detection of the fault at an early stage of the damage [13]–[17]. Employing the
infrared (IR) images can aid to mimic the hotspots in the PV modules that can indicate the abnormal
operations causing reduced power generation or the harmful hazards caused to the humans or the plant.
Researchers in 1998, detected the hotspots in the circuits and devices employing fluorescence micro
thermography (FMT) based on the temperature-relying luminescence of chelate dyes. There had been a
survey on infrared imaging of the solar PV modules in 2000, the key formulations they dealt with were solar
cells, solder bonds of a resistive kind, heating in reverse bias, the functionality of the by-pass diodes, and the
other factors that affect the balance of the system [18]. Gao et al. [19] to diagnose the PV module defective
cases, a proposal of infrared imagery on the moving cart was developed. The frame-to-frame association for
optical flow to count the panel in an array has been implemented. They used the generalized Hough
transforms and the clustering density-based spatial clustering of applications with noise (DBSCAN) strategy
in relevance with the neighboring pixels [19]. Tsanakas et al. [20] implemented the canny edge detection
algorithm using thermal imaging technology. A key investigation was held on the hotspot detection based on
heating. The algorithm found the defective modules using the edge detection phenomenon [20]. An automatic
surveillance and fault diagnosis method employing the PV power loss route was proposed by Chouder and
Silvestre [21]. They employed the key parameters of the PV system for examining the data logger in
real-time considering the temperature effects and the solar insolation [21]. Inspired by the above literature,
we employed an efficient technique for fault diagnosis of the PV modules installed in the United Arab
Emirates (UAE). The current work elucidates the comprehensive understanding of the PV measures
employed with the consistent electrical and thermographic approach as shown in Figure 1. The novelty lies in
designing the most robust and competitive algorithm aids the efficient implementation.
Figure 1. A systematic flow for the current experimental setup
2. MATERIALS AND RESEARCH METHODS
Figure 2 demonstrates the schematic illustration of the experimental setup. The system consists of a
thermal imager to capture the PV module image instantaneously. The images obtained were processed using
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 12, No. 5, October 2022: 4772-4781
4774
the MATLAB software employing fault diagnosis and detection algorithms in image processing and
computer vision toolbox to detect the fault and identify the malfunctioned PV panels. The intended
monitoring system is operating on the multicore CPU along with the parallel processing module using C++
programming. The crucial image processing algorithms were accommodated to find the PV module defect.
The algorithm is robust with the least error and deviation in identifying the fault. The Table 1 furnishes the
information about the key elements employed for the current protocol. The components were obtained from
the laboratory and used under supervised inspection.
Figure 2. Schematic illustration of the experimental setup
Table 1. Components of the experiment
Components Specifications
Solar PV Panel Waaree WS-50 W
Battery Eternity Technologies 12 VDC, 56 AH
Charge Controller Morning Star SS-MPPT-15L
Thermal Imager Fluke Ti-45
Clamp Meter HEME Analyst 2050
Tripod BOSCH BS280
Multimeter Fluke 176
IR Light 250 W IR
Load 2 x 24 W DC Motors
2.1. Electrical setup
All the measurements were calibrated on a sunny day, with the average solar irradiance of
1000 W/m2
that can be measured by the pyranometer (DPA 053 and the mini data logger) along it. To
elucidate the voltage and current calibrations, the typical curves can be obtained by the IV tracer that was
connected to the workstation PC specifically considered as a load depending on the setup. Figure 3
demonstrates the electrical calibrations of the PV Panel associated with the IV tracer for obtaining various
parameters such as IV parameters, temperatures, solar global radiation. The setup in Figure 3(a) distinguishes
that the pyranometers, IV tracers, and thermocouples were properly attached to the PV panels. The global
solar radiation with respect to time and temperature has been mentioned in Figure 3(b). From Figure 3(c), it
is evident that the current and voltage measurements were found to have fewer amplitudes on par with the
proper PV panels without the shadowing or without the polystyrene patches. ΔIV depicts the difference
between actual IV and obtained IV after shadowing. Generally, identifying the shadowing and damages of
the PV panel cells is a bit of a tedious process, hence there is a great need to employ the thermographic setup
for depicting the shadowing or cracks on the PV panel surface which will be discussed in the following
sections.
2.2. Thermographic setup
Thermal images were obtained with a photo rate of 10 seconds at the time of the panels’ heating
phase, which can be due to the exposure to the solar radiation and by the application of the electrical loads.
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A tripod, placed at a suitable distance from the panels, enables the continuous acquisition of the images. The
distance can be adopted in such a way that all the panels can be visible simultaneously avoiding the
possibility of the IR camera not obstructing the image acquisition. Hence, the angle of viewing in between
the IR camera lens and the object was perpendicular and was zero.
(a)
(b) (c)
Figure 3. Demonstration of layout and electrical calibration (a) experimental setup of electrical
measurements, (b) global solar radiation concerning the time and temperature, and (c) measured IV
characteristics before and after the shadowing
Hence, the thermal camera was employed in such a way that to acquire the images in a symmetrical
phenomenon Figure 4. The IR camera was tilted in such a way to precisely frame all the panels
simultaneously. It is a bit contrast in the common practice, viewing angle is not much encouraged because of
the camera reflection itself. The current work employed the distance in such a way that the distance between
the tripod and the PV panel along with their tilt angle about the ground does not affect the self-reflection. The
design perspective of the experiment and projection of design layout prototype of the experimental setup is
depicted in Figures 4(a) and 4(b) and a photograph of the setup is illustrated in Figure 4(c).
2.3. Segmentation by canny edge detection algorithm and bounding box technique
Initially, as mentioned in Figure 5, the input image is converted into grayscale where threshold
values are adjusted that are held for binary image edge detection and to identify the regions of interest from
the input thermal images. The solar cells of the defective kind are generally yellow or white in colors having
sharp edges in thermal images, makes lucid to identify the region of interest. The threshold value, ‘Th’ is
ascribed to a binary image. Convolution of the image is done by Gaussian filter coefficients. Later
non-maximum suppression (NMS) is performed on the image. The hysteresis thresholding is depicted for the
image followed by 8-connected components labeling. Furthermore, the morphological transformations also
benefit from the kernel assignment, defining the structuring element. At first, the erosion technique is applied
to the image, depending on the kernel kind, the pixels of the image are ascribed as such, else the erosion
takes place in the image. Boundary pixels will be faded or discarded in the image based on the kernel size
estimating the white color area reduction. The dilation is adopted later which is contradictory to the erosion,
the pixel is 1 when at least any one of the pixels under the kernel is 1. This can be elaborated as the white
region in the image grows or dimensions of the objects in the foreground enhances. Therefore, the faulty
solar cells in the modules can be identified by the optimal Canny’s Algorithm accompanied by the region
props and bounding box techniques.
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(a)
(b)
(c)
Figure 4. Thermographic setup (a) design perspective of the experiment, (b) projection of design layout, and
(c) experimental setup of thermographic calibrations
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Figure 5. The flow diagram for the fault detection algorithm
3. RESULTS AND DISCUSSION
The input images were captured for our PV modules in the Ras Al Khaima Research and Innovation
(RAKRIC) center at the American University of Ras Al Khaima (AURAK), UAE to substantiate our
proposal (Latitude and Longitude of 27.2046° N, 77.4977° E). The experimental setup has multiple hardware
components is such as depicted in the following tabular column of Table 1. The complete system was
constructed in our research facility is as shown in Figure 6 considering all the elements of connectivity,
calibrations, and escalations.
The Fluke Ti-45 has been used as a thermal imager and the resolution of the images is found to be
accurate for processing images in the MATLAB software. The BOSCH BS 280 tripod was employed for the
experiment. The thermal imager was mounted on the Tripod facing the solar PV module at an appropriate
distance to capture the images. Moreover, indoor imaging is also taken into consideration for fault detection
analysis. For this, the IR light sources of 250 W were employed and mounted on two more tripods. We
utilized placing certain pieces of polystyrene sheets on the surface of the PV panel that can act as a minimal
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defect. C++ program on the MATLAB command prompt was accessed to perform operations and process the
input images obtained from the thermal imager. The specifications of the workstation PC are ASUS Tek
Computer.Inc, X556UB, professional, Intel (R) Core (TM) i7-6500U Processor, 2.59 GHz, 12.0 GB RAM,
64-bit operation system x 64 based processor, and a Windows 10 professional operating system is employed.
MATLAB R2020b was installed on the Windows 10 platform, along with other image processing and
computer vision toolbox with other extensions. Employing internet of things (IoT), which will be our future
work provides the privilege for the real time monitoring of various PV panels parameters and crucial
constraints include temperature, cracks and shading of PV cells. This can be achieved by the novel
technologies in the AI such as Thinkspeak can avail facile access.
Figure 6. Scheme of PV module setup at RAKRIC
3.1. Algorithm implementation for edge detection
The morphological transformations and canny edge algorithm were used to identify the fault in the
PV module as depicted in Figure 7 in both the cases of indoor and outdoor setup. In the outdoor setup, two
out of the three panels of the system are made manually defective with a certain random arrangement, while
the other panel is left as it is. In the indoor setup, one PV panel was used and manually made defective. The
thermal image of all the panels is depicted in Figure 7(a). Now the processing of images is taken into
consideration. After loading the input thermal image and converting it into the grayscale, the thresholding is
foxed with Tlow as 0.075 and Thigh as 0.175 along with the Gaussian filter coefficients. Gaussian filtering is
intended for the convolution of the image in both X and Y directions. It is of a linear filter, typically aimed at
blurring the image or reducing the noise in the image. The considerable usage for dual purpose and
subtracting makes to edge detection or unsharp masking. The filter operates to blur the image and contrast
reduction. The Gaussian filter is faster since it multiplies and adds that makes it more robust than sorting.
The output image with the color scaling is elucidated in Figure 7(b). In the concatenation to this, the
non-maximum suppression is performed and shown in Figure 7(c). The non-maximum suppression is
intended to scan the image in the image gradient direction in case the pixels are not in line with the local
maxima, they are zeros [22]. This has the overall effect of suppressing the information of the image which is
not in the local maxima region. For this image, the hysteresis thresholding is evaluated and assigned suitable
T values that give the outputs in Figure 7(d). The technique evaluates and compares the two images to build
the intermediary image by taking the two binary images which were thresholded at different levels [23]. The
more the threshold, the lower will be the pixels population. The accurate and more relevant pixels are found
in the higher threshold region depicting the real edges by adding them to the hysteresis images. Now the
morphological transformations with appropriate structural elements are assigned to get Figure 7(e) and
bounding box techniques are applied to detect the final defect in the PV module shown in Figure 7(f). This
technique is certainly an illusionary rectangle that acts as a reference point to aid object detection and draws
the collision boxes for the object [24], [25]. Data annotators generally draw the rectangles over the images
outlining the object of interest in each image by ascribing the X and Y coordinates. The following Table 2,
evaluates the comparison of thermal imaging for PV panel inspections.
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Figure 7. Various stages of the algorithm (a) input thermal image, (b) scaling colored image, (c) NMS,
(d) hysteresis thresholding, (e) morphological transformations, and (f) bounding box techniques
Table 2. Comparative literature with various thermal imagers
Reference Thermal Imager
Aghaei et al. [26] MicroCAM 640 by Thermoteknix Systems Ltd
Quater et al. [27] MicroCAM 640 by Thermoteknix Systems Ltd
Kauppinen et al. [28] FLIR Tau2
Muntwyler et al. [29] Optris PI Lightweight PI 400
Aghaei et al. [30] Flir A35
Addabbo et al. [31] FlirVue Pro and Flir TAU2
4. CONCLUSION
With the advent of industrialization, the quest for alternate energy resources has become more
ardent. Renewable energy resources are found more feasible and optimal for this purpose. Solar PV
technology playing a crucial role in satisfying the energy demands. Various factors need to consider in the
design, construction, and evaluation of the PV plant setup. Performance is the key factor that needs to be
addressed. To elucidate the faults and improve the performance of the system to save energy, economy and
mimic the dangerous effect during the operation of the PV systems, the current work has initiated a new
hybrid algorithm that can be employed for real-time monitoring. The experimental system employs an
infrared thermal camera mounted on a tripod along with the electrical parameters measured with the real-time
testing in our laboratory. The practical analysis on the current proposed model along with the suitable best-fit
algorithm correlated to minimize the hazardous effects and enhance the performance of the PV setup and
reliability through employing algorithms for fault detection. Our future work is to integrate the IoT
technology with the current work to check the performance and identify the fault on a go (through mobiles)
technology and dynamically monitor the electrical performance as well. The results found feasible for
real-time applications and processing time is found very optimal for the PV plants.
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BIOGRAPHIES OF AUTHORS
Kummara Venkata Guru Raghavendra received his bachelor’s degree in
electrical and Electronics Engineering from JNTU, Anantapur, India. He completed his
Master’s in Automation Engineering from University of Bologna, Bologna, Italy. He received
Ph.D. from Pusan National University, major in the Electrical Engineering on August 2020.
He worked as Post-Doctoral Researcher in Yeungnam University, South Korea. He is a
potential reviewer for Journal of Energy Storage, Materials Letters, Ceramics International. He
member of many reputed research organizations such as IEEE, International Society of
Automation, Franklin UK, the IRED. Now he is a Sustainable Energies Research and Project
Consultant and Visiting Post-Doctoral Researcher at American University of Ras Al Khaimah
University, RAKRIC, United Arab Emirates in Renewable Engineering. He can be contacted
at email: kvg.raghavendra999@gmail.com. Linkedin: https://www.linkedin.com/in/kvgr.
Nutakki Tirumala Uday Kumar holds his Ph.D. in Energy Technology from
KTH Royal Institute of Technology, Sweden 2016, M.Tech. from Indian Institute of
Technology Bombay, and B.Tech. from Andhra University, India in 2007 and 2005
respectively, both in Chemical Engineering. After completion of his Masters, Dr. Uday joined
RAK Research and Innovation center (previously CSEM-UAE) and work on various scientific
research projects in chemical, environmental based engineering processes especially related to
water purification. In 2011, Dr. Uday started his industrial Ph.D. research project on
‘Sustainable co/poly generation technologies by integrating membrane distillation process
with renewable energy systems’ which is a collaborative project between joined KTH, Scarab
and RAKRIC. Dr. Uday addressed the water and nexus by efficient integration of pilot scale
membrane distillation modules with solar thermal energy for production of heat, cooling and
pure water simultaneously. He can be contacted at email: uday.kumar@aurak.ac.ae. Website:
https://aurak.ac.ae/en/uday-kumar/.
Waqarullah Kazim is an Electrical R&D engineer at American University of
Ras-Al-Khaimah Research and Innovation center. He worked on Design Development and
testing of High SRI materials Lab at RAKRIC. He was also Electrical R&D engineer at
CSEM-UAE Innovation center. LLC. He was In-charge of Labs/Junior Instructor at IoBM
(Institute of Business and Management, Industrial Engineering and management). He
registered many professional certifications like FLUKE, SMA. He published many articles in
the domain of renewable engineering. He can be contacted at email: waqar.ullah@aurak.ac.ae.
Website: https://aurak.ac.ae/en/waqar/. Linkedin: linkedin.com/in/waqarullahkazim.