The objective of this paper is to study the dynamic response of the wind energy conversion system (WECS) based on the Doubly Fed Induction Generator (DFIG). The DFIG rotor is connected to the grid via a converter. The active and reactive power control is realized by the DFIG rotor variables control, using the field oriented control (FOC). The vector control of DFIG is applied by the use of tow regulators PI and the neural network regulator (NN). The generator mathematical model is implemented in Matlab/ Simulink software to simulate a DFIG of 1.5 MW in order to show the efficiency of the performances and robustness of the studied control systems. The simulation obtained results shows that the robustness and response time of the neural network regulator is better than those obtained by the PI classical regulator.
Performance evaluation of ann based plasma position controllers for aditya to...IAEME Publication
This paper evaluates the performance of artificial neural network (ANN) based plasma position controllers for the Aditya tokamak device. Radial basis function networks and generalized recurrent neural networks are developed as controllers and their performance is compared to an existing backpropagation network controller. Training data for the ANNs comes from the Aditya RZIP model. Testing shows the backpropagation network provides better performance in terms of signal-to-noise ratio and root mean square error compared to the other controllers. Further testing on actual plasma discharge data from Aditya is recommended, as well as exploring neuro-fuzzy controllers for plasma position control.
Robustness and Stability Analysis of a Predictive PI Controller in WirelessHA...IJECEIAES
As control over wireless network in the industry is receives increasing attention, its appli- cation comes with challenges such as stochastic network delay. The PIDs are ill equipped to handle such challenges while the model based controllers are complex. A settlement between the two is the PPI controller. However, there is no certainty on its ability to preserve closed loop stability under such challenges. While classical robustness measures do not require extensive uncertainty modelling, they do not guarantee stability under simultaneous process and network delay variations. On the other hand, the model uncertainty measures tend to be conservative. Thus, this work uses extended complementary sensitivity function method which handles simultaneously those challenges. Simulation results shows that the PPI controller can guarantee stability even under model and delay uncertainties.
This document presents a data-mining based intelligent protection scheme for fault detection and classification in a microgrid. The microgrid consists of synchronous generators, a photovoltaic module, and a wind farm, and is modelled in RSCAD. The protection scheme retrieves current samples after a fault occurs and uses transforms to extract statistical features to build a machine learning model for fault detection and classification, which will be validated on additional data and implemented on an RTDS platform integrated with Matlab. Extensive testing will evaluate the performance of the proposed intelligent relaying scheme for microgrids under different operating conditions.
- Motivated Electrical Engineer with 1 year of experience in power transmission planning, generator interconnection studies, and NERC compliance studies seeking a position in power systems engineering.
- Master's degree in Electrical Engineering with a focus on power systems and experience in software development.
- Skilled in transmission planning tools like PSSE and experience analyzing power flows, contingencies, and reliability standards.
The power supply system is completely hooked into three major parts. First one is generation, second one is
transmission and the last one is distribution of electricity supply at the range of 415V to 400V approx. But while
the fault occurs it affects other lines additionally, and this causes difficulties for local people and additionally
perturb the flow of current in different areas. This eccentric and perturbed supply of nuisance is very
hazardous as it cannot be ceased when it comes to equal distribution of electricity. The area suffering from
faults and the other both get affected. So to stop all these we have implemented this project of Coordination of
over current relay utilising optimisation technique. We have utilised crow search algorithms with Kennedy as
swarm perspicacity algorithms which are very auxiliary in storing excess electricity supply and can be used
when needed. With the avail of this we can renovate the potency supply and this will conclusively implement
our main objective of this project.
Hierarchical Droop Controlled Frequency Optimization and Energy Management of a Grid-Connected Microgrid ,
Sustech 2017 conference, Nov 12-14
Presented by Sima Aznavi
Design and implementation of a generator power sensor and shutdown timerAlexander Decker
This document describes the design and implementation of a generator power sensor and shutdown timer. Key points:
1) A microcontroller (Atmega8) is used to control the timing operation and sense power restoration, making the circuit more compact, efficient and reliable compared to using discrete components.
2) The microcontroller is programmed in C language to control an LCD display, buttons, LEDs, buzzer, and relay for switching the generator.
3) In addition to automatically shutting down the generator after a set time, the circuit can sense when utility power is restored and switch the load to that power while stopping the timer.
A Passive Islanding Detection Method for Neutral point clamped Multilevel Inv...IJECEIAES
Presently renewable energies have taken a special place in the world and most of the Distributed Generations (DGs) used in the interconnected power system are utilized, renewable energy resources. Due to the DG‟s advantages, including use of renewable energy such as, clean nature, does not pollute environment and having endless nature the use of these renewable resources to produce electrical energy in the world are increasing in day to day life. One problem with such Distributed generators is an unintentional islanding phenomenon. Islanding occurs when a Distributed Generation continues to energize an isolated part of a power system even after it was disconnected from the main grid, which is surrounded by unpowered lines. Since islanding can cause hazardous conditions for people and equipment which is connected to it. As per IEEE 1547 DG Interconnection standards, islanding should be quickly detected within 2 seconds, by protective relays and inverters that are part of the DG system. In this paper, a new passive method to identify islanding states has been proposed, based on the rate of change of frequency analysis (ROCOF) for a multilevel inverter based solar distributed generation systems. This method is efficient for both connecting DGs to the network with or without the Inverter. This method is more efficient than the existing methods and reducing the Non Detection Zone (NDZ), which is the disadvantage of existing passive methods and also clearly differentiating between the Islanding and Non-islanding events. The simulation results, which are carried on the MATLAB/Simulink environment shows the performance of the proposed method
Performance evaluation of ann based plasma position controllers for aditya to...IAEME Publication
This paper evaluates the performance of artificial neural network (ANN) based plasma position controllers for the Aditya tokamak device. Radial basis function networks and generalized recurrent neural networks are developed as controllers and their performance is compared to an existing backpropagation network controller. Training data for the ANNs comes from the Aditya RZIP model. Testing shows the backpropagation network provides better performance in terms of signal-to-noise ratio and root mean square error compared to the other controllers. Further testing on actual plasma discharge data from Aditya is recommended, as well as exploring neuro-fuzzy controllers for plasma position control.
Robustness and Stability Analysis of a Predictive PI Controller in WirelessHA...IJECEIAES
As control over wireless network in the industry is receives increasing attention, its appli- cation comes with challenges such as stochastic network delay. The PIDs are ill equipped to handle such challenges while the model based controllers are complex. A settlement between the two is the PPI controller. However, there is no certainty on its ability to preserve closed loop stability under such challenges. While classical robustness measures do not require extensive uncertainty modelling, they do not guarantee stability under simultaneous process and network delay variations. On the other hand, the model uncertainty measures tend to be conservative. Thus, this work uses extended complementary sensitivity function method which handles simultaneously those challenges. Simulation results shows that the PPI controller can guarantee stability even under model and delay uncertainties.
This document presents a data-mining based intelligent protection scheme for fault detection and classification in a microgrid. The microgrid consists of synchronous generators, a photovoltaic module, and a wind farm, and is modelled in RSCAD. The protection scheme retrieves current samples after a fault occurs and uses transforms to extract statistical features to build a machine learning model for fault detection and classification, which will be validated on additional data and implemented on an RTDS platform integrated with Matlab. Extensive testing will evaluate the performance of the proposed intelligent relaying scheme for microgrids under different operating conditions.
- Motivated Electrical Engineer with 1 year of experience in power transmission planning, generator interconnection studies, and NERC compliance studies seeking a position in power systems engineering.
- Master's degree in Electrical Engineering with a focus on power systems and experience in software development.
- Skilled in transmission planning tools like PSSE and experience analyzing power flows, contingencies, and reliability standards.
The power supply system is completely hooked into three major parts. First one is generation, second one is
transmission and the last one is distribution of electricity supply at the range of 415V to 400V approx. But while
the fault occurs it affects other lines additionally, and this causes difficulties for local people and additionally
perturb the flow of current in different areas. This eccentric and perturbed supply of nuisance is very
hazardous as it cannot be ceased when it comes to equal distribution of electricity. The area suffering from
faults and the other both get affected. So to stop all these we have implemented this project of Coordination of
over current relay utilising optimisation technique. We have utilised crow search algorithms with Kennedy as
swarm perspicacity algorithms which are very auxiliary in storing excess electricity supply and can be used
when needed. With the avail of this we can renovate the potency supply and this will conclusively implement
our main objective of this project.
Hierarchical Droop Controlled Frequency Optimization and Energy Management of a Grid-Connected Microgrid ,
Sustech 2017 conference, Nov 12-14
Presented by Sima Aznavi
Design and implementation of a generator power sensor and shutdown timerAlexander Decker
This document describes the design and implementation of a generator power sensor and shutdown timer. Key points:
1) A microcontroller (Atmega8) is used to control the timing operation and sense power restoration, making the circuit more compact, efficient and reliable compared to using discrete components.
2) The microcontroller is programmed in C language to control an LCD display, buttons, LEDs, buzzer, and relay for switching the generator.
3) In addition to automatically shutting down the generator after a set time, the circuit can sense when utility power is restored and switch the load to that power while stopping the timer.
A Passive Islanding Detection Method for Neutral point clamped Multilevel Inv...IJECEIAES
Presently renewable energies have taken a special place in the world and most of the Distributed Generations (DGs) used in the interconnected power system are utilized, renewable energy resources. Due to the DG‟s advantages, including use of renewable energy such as, clean nature, does not pollute environment and having endless nature the use of these renewable resources to produce electrical energy in the world are increasing in day to day life. One problem with such Distributed generators is an unintentional islanding phenomenon. Islanding occurs when a Distributed Generation continues to energize an isolated part of a power system even after it was disconnected from the main grid, which is surrounded by unpowered lines. Since islanding can cause hazardous conditions for people and equipment which is connected to it. As per IEEE 1547 DG Interconnection standards, islanding should be quickly detected within 2 seconds, by protective relays and inverters that are part of the DG system. In this paper, a new passive method to identify islanding states has been proposed, based on the rate of change of frequency analysis (ROCOF) for a multilevel inverter based solar distributed generation systems. This method is efficient for both connecting DGs to the network with or without the Inverter. This method is more efficient than the existing methods and reducing the Non Detection Zone (NDZ), which is the disadvantage of existing passive methods and also clearly differentiating between the Islanding and Non-islanding events. The simulation results, which are carried on the MATLAB/Simulink environment shows the performance of the proposed method
Design and Analysis of PID and Fuzzy-PID Controller for Voltage Control of DC...Francisco Gonzalez-Longatt
DC microgrids are desired to provide the electricity for the remote areas which are far from the main grid. The microgrid creates the open horizontal environment to interconnect the distributed generation especially photovoltaic (PV). The stochastic nature of the PV output power introduces the large fluctuations of the power and voltage in the microgrid and forced to introduce the controller for voltage stability. There are many control strategies to control the voltage of a DC microgrid in the literature. In this paper the proportional-integral-derivative (PID) and fuzzy logic PID (FL-PID) controller has been designed and compared in term of performance. Performance measures like maximum overshoot and settling time of FL-PID compared with the PID proved that the former is better controller. The controllers are designed and simulated in the MATLAB programming environment. The controllers has been tested for the real time data obtained from Pecan Street Project, University of Texas at Austin USA.
This document summarizes recent developments in microgrid protection techniques. It discusses (1) a differential energy based protection scheme that uses time-frequency transforms to detect faults in grid-connected and island modes, (2) an autonomous protection method for low voltage DC microgrids using current sensors and circuit breakers to isolate faulty lines, and (3) an adaptive protection approach using communication between relays and a central protection unit to dynamically adjust settings based on distributed generator conditions and fault contributions. The challenges of microgrid protection include bidirectional power flow, topological changes, intermittent generation, insufficient fault currents, and potential nuisance tripping.
The document presents a new method for fault classification and direction discrimination in transmission lines using 1D convolutional neural networks (1D-CNNs). A 132kV transmission line model is simulated to generate training and testing data for the 1D-CNN algorithm. The proposed 1D-CNN approach directly uses the voltage and current signals from one end as input, merging feature extraction and classification into a single learning process. Testing shows the 1D-CNN method accurately classifies and discriminates fault direction with higher accuracy than conventional neural network and fuzzy neural network methods under different fault conditions.
Modeling of Micro-Hydro Power Plant and its Direct Based on Neural systemIRJET Journal
This document proposes a neural network based PID controller to maintain stable frequency in micro-hydro power plants when load changes. It models a micro-hydro power plant using five blocks: PID controller, governor, servomotor, turbine, and generator. A neural network PID controller is constructed using the Brandt-Lin algorithm to help the governor regulate water flow and keep turbine rotation stable. Simulation results show the neural network controller more accurately and precisely maintains frequency compared to a simple linear controller, improving plant performance.
This paper proposes a Wavelet based Adaptive Neuro-Fuzzy Inference System (WANFIS) applied to forecast the wind power and enhance the accuracy of one step ahead with a 10 minutes resolution of real time data collected from a wind farm in North India. The proposed method consists two cases. In the first case all the inputs of wind series and output of wind power decomposition coefficients are carried out to predict the wind power. In the second case all the inputs of wind series decomposition coefficients are carried out to get wind power prediction. The performance of proposed WANFIS is compared to Wavelet Neural Network (WNN) and the results of the proposed model are shown superior to compared methods.
Softmax function is an integral part of object detection frameworks based on most deep or shallow neural
networks. While the configuration of different operation layers in a neural network can be quite different,
softmax operation is fixed. With the recent advances in object detection approaches, especially with the
introduction of highly accurate convolutional neural networks, researchers and developers have suggested
different hardware architectures to speed up the overall operation of these compute-intensive algorithms.
Xilinx, one of the leading FPGA vendors, has recently introduced a deep neural network development kit for
exactly this purpose. However, due to the complex nature of softmax arithmetic hardware involving
exponential function, this functionality is only available for bigger devices. For smaller devices, this operation is
bound to be implemented in software. In this paper, a light-weight hardware implementation of this function
has been proposed which does not require too many logic resources when implemented on an FPGA device.
The proposed design is based on the analysis of the statistical properties of a custom convolutional neural
network when used for classification on a standard dataset i.e. CIFAR-10. Specifically, instead of using a brute
force approach to design a generic full precision arithmetic circuit for SoftMax function using real numbers, an
approximate integer-only design has been suggested for the limited range of operands encountered in realworld
scenario. The approximate circuit uses fewer logic resources since it involves computing only a few
iterations of the series expansion of exponential function. However, despite using fewer iterations, the function
has been shown to work as good as the full precision circuit for classification and leads to only minimal error
being introduced in the associated probabilities. The circuit has been synthesized using Hardware Description
Language (HDL) Coder and Vision HDL toolboxes in Simulink® by Mathworks® which provide higher level
abstraction of image processing and machine learning algorithms for quick deployment on a variety of target
hardware. The final design has been implemented on a Xilinx FPGA development board i.e. Zedboard which
contains the necessary hardware components such as USB, Ethernet and HDMI interfaces etc. to implement a
fully working system capable of processing a machine learning application in real-time.
This document is a project report submitted to Amity University Rajasthan for the degree of Bachelor of Technology in Electronics and Communication Engineering. The report contains 4 chapters that discuss microstrip antenna basics, modified patch microstrip antennas for modern communication systems, modified patch antennas for geometry, and conclusions. The chapters review previous work, describe simple and slotted patch antenna designs, and discuss observations and the scope for future work on modified patch antennas.
This document analyzes the impact of distributed generation placement on the stability of Nigeria's power network. It uses the ETAP software to model the power network system and analyze faults both with and without distributed generation. The results show that distributed generation has the potential to improve system performance. Specifically, adding distributed generation units reduces the magnitude of power angle deviations during transients and improves transient stability. Higher penetration levels of distributed generation allow the system to withstand more severe faults by maintaining synchronism and reducing maximum power angle deviations. The document then describes methods that will be used to analyze transient, frequency, and voltage stability of the Nigeria power network with distributed generation, including time-domain simulation and analytical methods like the Runge-Kutta method and equal
wireless fault protection and detection for dc microgrid MAHESH M
This document proposes a fault protection and location method for DC microgrid systems using wireless communication and intelligent electronic devices (IEDs). The method uses IEDs with current sensors and circuit breakers to monitor currents, detect faults, and isolate faulty sections. A probe power unit is then used to locate faults without needing to reclose circuit breakers. Simulations showed the method can successfully detect, isolate, and locate faults to maintain operation of unfaulted sections and identify permanent faults. The document presents the DC microgrid system, IED operation, possible fault types, protection techniques, the proposed protection system, fault location methods, and concludes the method was demonstrated through successful computer simulations.
Voltage stability Analysis using GridCalAnmol Dwivedi
Power system voltage stability is characterized as being capable of maintaining load voltage magnitudes within specified operating limits under steady state conditions. This presentation deals with the modeling of two standard power systems test cases i.e the Nordic-32 and the Nordic-68, comparing the power flows results obtained from GridCal against PSS/E, finding the respective P-V curves for the two test cases using the continuation power flow under contingencies, and finally proposing a graph-based test statistic which can be used for an imminent voltage instability. The simulations are carried out using an open-source power system software called GridCal and the scripts for this project are written in python.
This document summarizes a study that aimed to improve the dynamic performance of a microgrid (MG) consisting of renewable energy sources including wind, solar, and microturbine generation during fault conditions. An adaptive neuro-fuzzy inference system (ANFIS) was used for maximum power point tracking of the solar arrays. A fuzzy logic controller was also developed for pitch angle control of the wind turbine to control output power at high wind speeds. Simulation results showed the ANFIS controller was able to meet load demand with less fluctuation around the maximum power point. The fuzzy logic pitch angle controller also led to flatter power curves and improved dynamic performance of the wind turbine by preventing damage during faults or high winds.
Fault protection of a loop type low voltage dc bus based microgridsIAEME Publication
This document proposes a fault protection scheme for a loop-type low voltage DC microgrid system. The scheme uses differential relaying between a master controller and two slave controllers located at either end of a DC bus transmission line. When a fault is detected based on a current difference, the master controller commands the slave controllers to open solid state switches and isolate only the faulty section, allowing the rest of the system to continue operating. The scheme aims to quickly detect and isolate faults while maintaining power supply to loads. Simulation results using MATLAB Simulink are presented to demonstrate the proposed concepts.
IRJET- IoT based Solar Power Monitoring SystemIRJET Journal
This document proposes an IOT-based solar power monitoring system that can monitor and control a solar photovoltaic system remotely. The system uses sensors to monitor the voltage, current, and power output of solar panels. A microcontroller connects the sensors to the internet via WiFi to upload the data to a cloud server. The system also includes a sun tracking mechanism using an LDR sensor and DC motor to automatically rotate the solar panels and maximize sunlight exposure for increased efficiency. The remote monitoring capabilities allow users to view the solar panel performance from anywhere via a web interface.
Controllers are used in renewable energy systems like electric vehicles, wind turbines, and solar power plants to regulate various functions. Modern controllers for electric vehicles use pulse width modulation to smoothly control motor speed and acceleration. Advanced controllers for wind turbines and solar plants employ strategies like variable pitch control, maximum power point tracking, and fuzzy logic to optimize power capture despite changing environmental conditions. Controllers are critical for integrating renewable sources into smart grids and ensuring stable, efficient system operation as use of intermittent renewables increases.
Genetic algorithm approach into relay co ordinationIAEME Publication
This document summarizes a research paper that uses a genetic algorithm to optimize the coordination of overcurrent relays in an electrical power distribution system. The paper formulates the relay coordination problem as an optimization problem to minimize the total operating times of relays while satisfying coordination constraints. A genetic algorithm is applied to find the optimal settings for time multipliers on the relays. As a case study, the algorithm is applied to coordinate relays on a simple radial system and finds settings that achieve the minimum fitness function value while satisfying constraints. The genetic algorithm approach provides an effective method for automating the optimization of relay coordination in electrical power systems.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
This document discusses DC microgrids and the research being done on them at Aalborg University. It provides an overview of the microgrid research programme, including its focus areas and team members. It then discusses various DC microgrid projects, from residential to industrial applications. It also covers DC microgrid control architectures, including primary, secondary and tertiary control levels.
Modelling and Control of a Microgrid with100kW PV System and Electrochemical ...usman1441
This document outlines the modeling and control of a microgrid system with a 100kW PV system and battery energy storage. It discusses the components of a microgrid including distributed generators, energy storage systems, loads, and power conditioning for grid connection and islanding modes. Power electronic converters including boost converters and inverters are modeled for interfacing the PV and battery. Maximum power point tracking and current control methods are summarized for grid synchronization. Simulation results are presented to validate the microgrid model and control strategies.
Automatic Fault Detection System with IOT BasedYogeshIJTSRD
The fault location is an important part for any transmission line and distribution system. The location of fault is difficult task sometimes it takes lot of times needed for the exact location of the fault. The exact fault location can help the service man to overcome the fault free system in very less time. In this paper we are able to detect the fault range in easy way using the ESP module and the message is transferred on the mobile. This project is cost effective and reliable. Fast fault detection provide the protection of equipment before any significant damage. Er. Sanjeev Kumar | Mohd Mehraj Khan | Nadeem | Shailesh Kumar Yadav | Harsh Gupta "Automatic Fault Detection System with IOT Based" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43806.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/43806/automatic-fault-detection-system-with-iot-based/er-sanjeev-kumar
A novel efficient adaptive-neuro fuzzy inference system control based smart ...IJECEIAES
This document presents a novel adaptive-neuro fuzzy inference system (ANFIS) control algorithm for a smart grid integrating solar, wind, and grid power sources. The proposed ANFIS controller is used to improve the steady-state and transient response of the hybrid power system. Fuzzy logic maximum power point tracking algorithms are used to extract maximum power from solar photovoltaic panels and a permanent magnet synchronous generator is used for wind power generation. Back-to-back voltage source converters operated by the ANFIS controller are used to maximize both renewable power generations. Simulation results under different operating conditions and nonlinear faults show the proposed ANFIS control algorithm improves the overall system performance.
Independent Control Of Active And Reactive Powers From DFIG By Logic FuzzyIJRES Journal
This paper presents the study and use by simulating the fuzzy logic control of asynchronous
generator dual fuel in the production of electrical energy that the .for I prepared a study of the wind system and
a model of the wind turbine was established by following the study and modeling of doubly fed asynchronous.
Two types of vector control have been the subject of study in this work for independent control of active and
reactive power: the direct and indirect control .la fuzzy PI control is introduced to increase the robustness of
markers vis-à-screw parametric variation of the machine in the simulation results obtained were compared to the
validated work articles cited in the bibliography.
Design and Analysis of PID and Fuzzy-PID Controller for Voltage Control of DC...Francisco Gonzalez-Longatt
DC microgrids are desired to provide the electricity for the remote areas which are far from the main grid. The microgrid creates the open horizontal environment to interconnect the distributed generation especially photovoltaic (PV). The stochastic nature of the PV output power introduces the large fluctuations of the power and voltage in the microgrid and forced to introduce the controller for voltage stability. There are many control strategies to control the voltage of a DC microgrid in the literature. In this paper the proportional-integral-derivative (PID) and fuzzy logic PID (FL-PID) controller has been designed and compared in term of performance. Performance measures like maximum overshoot and settling time of FL-PID compared with the PID proved that the former is better controller. The controllers are designed and simulated in the MATLAB programming environment. The controllers has been tested for the real time data obtained from Pecan Street Project, University of Texas at Austin USA.
This document summarizes recent developments in microgrid protection techniques. It discusses (1) a differential energy based protection scheme that uses time-frequency transforms to detect faults in grid-connected and island modes, (2) an autonomous protection method for low voltage DC microgrids using current sensors and circuit breakers to isolate faulty lines, and (3) an adaptive protection approach using communication between relays and a central protection unit to dynamically adjust settings based on distributed generator conditions and fault contributions. The challenges of microgrid protection include bidirectional power flow, topological changes, intermittent generation, insufficient fault currents, and potential nuisance tripping.
The document presents a new method for fault classification and direction discrimination in transmission lines using 1D convolutional neural networks (1D-CNNs). A 132kV transmission line model is simulated to generate training and testing data for the 1D-CNN algorithm. The proposed 1D-CNN approach directly uses the voltage and current signals from one end as input, merging feature extraction and classification into a single learning process. Testing shows the 1D-CNN method accurately classifies and discriminates fault direction with higher accuracy than conventional neural network and fuzzy neural network methods under different fault conditions.
Modeling of Micro-Hydro Power Plant and its Direct Based on Neural systemIRJET Journal
This document proposes a neural network based PID controller to maintain stable frequency in micro-hydro power plants when load changes. It models a micro-hydro power plant using five blocks: PID controller, governor, servomotor, turbine, and generator. A neural network PID controller is constructed using the Brandt-Lin algorithm to help the governor regulate water flow and keep turbine rotation stable. Simulation results show the neural network controller more accurately and precisely maintains frequency compared to a simple linear controller, improving plant performance.
This paper proposes a Wavelet based Adaptive Neuro-Fuzzy Inference System (WANFIS) applied to forecast the wind power and enhance the accuracy of one step ahead with a 10 minutes resolution of real time data collected from a wind farm in North India. The proposed method consists two cases. In the first case all the inputs of wind series and output of wind power decomposition coefficients are carried out to predict the wind power. In the second case all the inputs of wind series decomposition coefficients are carried out to get wind power prediction. The performance of proposed WANFIS is compared to Wavelet Neural Network (WNN) and the results of the proposed model are shown superior to compared methods.
Softmax function is an integral part of object detection frameworks based on most deep or shallow neural
networks. While the configuration of different operation layers in a neural network can be quite different,
softmax operation is fixed. With the recent advances in object detection approaches, especially with the
introduction of highly accurate convolutional neural networks, researchers and developers have suggested
different hardware architectures to speed up the overall operation of these compute-intensive algorithms.
Xilinx, one of the leading FPGA vendors, has recently introduced a deep neural network development kit for
exactly this purpose. However, due to the complex nature of softmax arithmetic hardware involving
exponential function, this functionality is only available for bigger devices. For smaller devices, this operation is
bound to be implemented in software. In this paper, a light-weight hardware implementation of this function
has been proposed which does not require too many logic resources when implemented on an FPGA device.
The proposed design is based on the analysis of the statistical properties of a custom convolutional neural
network when used for classification on a standard dataset i.e. CIFAR-10. Specifically, instead of using a brute
force approach to design a generic full precision arithmetic circuit for SoftMax function using real numbers, an
approximate integer-only design has been suggested for the limited range of operands encountered in realworld
scenario. The approximate circuit uses fewer logic resources since it involves computing only a few
iterations of the series expansion of exponential function. However, despite using fewer iterations, the function
has been shown to work as good as the full precision circuit for classification and leads to only minimal error
being introduced in the associated probabilities. The circuit has been synthesized using Hardware Description
Language (HDL) Coder and Vision HDL toolboxes in Simulink® by Mathworks® which provide higher level
abstraction of image processing and machine learning algorithms for quick deployment on a variety of target
hardware. The final design has been implemented on a Xilinx FPGA development board i.e. Zedboard which
contains the necessary hardware components such as USB, Ethernet and HDMI interfaces etc. to implement a
fully working system capable of processing a machine learning application in real-time.
This document is a project report submitted to Amity University Rajasthan for the degree of Bachelor of Technology in Electronics and Communication Engineering. The report contains 4 chapters that discuss microstrip antenna basics, modified patch microstrip antennas for modern communication systems, modified patch antennas for geometry, and conclusions. The chapters review previous work, describe simple and slotted patch antenna designs, and discuss observations and the scope for future work on modified patch antennas.
This document analyzes the impact of distributed generation placement on the stability of Nigeria's power network. It uses the ETAP software to model the power network system and analyze faults both with and without distributed generation. The results show that distributed generation has the potential to improve system performance. Specifically, adding distributed generation units reduces the magnitude of power angle deviations during transients and improves transient stability. Higher penetration levels of distributed generation allow the system to withstand more severe faults by maintaining synchronism and reducing maximum power angle deviations. The document then describes methods that will be used to analyze transient, frequency, and voltage stability of the Nigeria power network with distributed generation, including time-domain simulation and analytical methods like the Runge-Kutta method and equal
wireless fault protection and detection for dc microgrid MAHESH M
This document proposes a fault protection and location method for DC microgrid systems using wireless communication and intelligent electronic devices (IEDs). The method uses IEDs with current sensors and circuit breakers to monitor currents, detect faults, and isolate faulty sections. A probe power unit is then used to locate faults without needing to reclose circuit breakers. Simulations showed the method can successfully detect, isolate, and locate faults to maintain operation of unfaulted sections and identify permanent faults. The document presents the DC microgrid system, IED operation, possible fault types, protection techniques, the proposed protection system, fault location methods, and concludes the method was demonstrated through successful computer simulations.
Voltage stability Analysis using GridCalAnmol Dwivedi
Power system voltage stability is characterized as being capable of maintaining load voltage magnitudes within specified operating limits under steady state conditions. This presentation deals with the modeling of two standard power systems test cases i.e the Nordic-32 and the Nordic-68, comparing the power flows results obtained from GridCal against PSS/E, finding the respective P-V curves for the two test cases using the continuation power flow under contingencies, and finally proposing a graph-based test statistic which can be used for an imminent voltage instability. The simulations are carried out using an open-source power system software called GridCal and the scripts for this project are written in python.
This document summarizes a study that aimed to improve the dynamic performance of a microgrid (MG) consisting of renewable energy sources including wind, solar, and microturbine generation during fault conditions. An adaptive neuro-fuzzy inference system (ANFIS) was used for maximum power point tracking of the solar arrays. A fuzzy logic controller was also developed for pitch angle control of the wind turbine to control output power at high wind speeds. Simulation results showed the ANFIS controller was able to meet load demand with less fluctuation around the maximum power point. The fuzzy logic pitch angle controller also led to flatter power curves and improved dynamic performance of the wind turbine by preventing damage during faults or high winds.
Fault protection of a loop type low voltage dc bus based microgridsIAEME Publication
This document proposes a fault protection scheme for a loop-type low voltage DC microgrid system. The scheme uses differential relaying between a master controller and two slave controllers located at either end of a DC bus transmission line. When a fault is detected based on a current difference, the master controller commands the slave controllers to open solid state switches and isolate only the faulty section, allowing the rest of the system to continue operating. The scheme aims to quickly detect and isolate faults while maintaining power supply to loads. Simulation results using MATLAB Simulink are presented to demonstrate the proposed concepts.
IRJET- IoT based Solar Power Monitoring SystemIRJET Journal
This document proposes an IOT-based solar power monitoring system that can monitor and control a solar photovoltaic system remotely. The system uses sensors to monitor the voltage, current, and power output of solar panels. A microcontroller connects the sensors to the internet via WiFi to upload the data to a cloud server. The system also includes a sun tracking mechanism using an LDR sensor and DC motor to automatically rotate the solar panels and maximize sunlight exposure for increased efficiency. The remote monitoring capabilities allow users to view the solar panel performance from anywhere via a web interface.
Controllers are used in renewable energy systems like electric vehicles, wind turbines, and solar power plants to regulate various functions. Modern controllers for electric vehicles use pulse width modulation to smoothly control motor speed and acceleration. Advanced controllers for wind turbines and solar plants employ strategies like variable pitch control, maximum power point tracking, and fuzzy logic to optimize power capture despite changing environmental conditions. Controllers are critical for integrating renewable sources into smart grids and ensuring stable, efficient system operation as use of intermittent renewables increases.
Genetic algorithm approach into relay co ordinationIAEME Publication
This document summarizes a research paper that uses a genetic algorithm to optimize the coordination of overcurrent relays in an electrical power distribution system. The paper formulates the relay coordination problem as an optimization problem to minimize the total operating times of relays while satisfying coordination constraints. A genetic algorithm is applied to find the optimal settings for time multipliers on the relays. As a case study, the algorithm is applied to coordinate relays on a simple radial system and finds settings that achieve the minimum fitness function value while satisfying constraints. The genetic algorithm approach provides an effective method for automating the optimization of relay coordination in electrical power systems.
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Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
This document discusses DC microgrids and the research being done on them at Aalborg University. It provides an overview of the microgrid research programme, including its focus areas and team members. It then discusses various DC microgrid projects, from residential to industrial applications. It also covers DC microgrid control architectures, including primary, secondary and tertiary control levels.
Modelling and Control of a Microgrid with100kW PV System and Electrochemical ...usman1441
This document outlines the modeling and control of a microgrid system with a 100kW PV system and battery energy storage. It discusses the components of a microgrid including distributed generators, energy storage systems, loads, and power conditioning for grid connection and islanding modes. Power electronic converters including boost converters and inverters are modeled for interfacing the PV and battery. Maximum power point tracking and current control methods are summarized for grid synchronization. Simulation results are presented to validate the microgrid model and control strategies.
Automatic Fault Detection System with IOT BasedYogeshIJTSRD
The fault location is an important part for any transmission line and distribution system. The location of fault is difficult task sometimes it takes lot of times needed for the exact location of the fault. The exact fault location can help the service man to overcome the fault free system in very less time. In this paper we are able to detect the fault range in easy way using the ESP module and the message is transferred on the mobile. This project is cost effective and reliable. Fast fault detection provide the protection of equipment before any significant damage. Er. Sanjeev Kumar | Mohd Mehraj Khan | Nadeem | Shailesh Kumar Yadav | Harsh Gupta "Automatic Fault Detection System with IOT Based" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd43806.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/43806/automatic-fault-detection-system-with-iot-based/er-sanjeev-kumar
A novel efficient adaptive-neuro fuzzy inference system control based smart ...IJECEIAES
This document presents a novel adaptive-neuro fuzzy inference system (ANFIS) control algorithm for a smart grid integrating solar, wind, and grid power sources. The proposed ANFIS controller is used to improve the steady-state and transient response of the hybrid power system. Fuzzy logic maximum power point tracking algorithms are used to extract maximum power from solar photovoltaic panels and a permanent magnet synchronous generator is used for wind power generation. Back-to-back voltage source converters operated by the ANFIS controller are used to maximize both renewable power generations. Simulation results under different operating conditions and nonlinear faults show the proposed ANFIS control algorithm improves the overall system performance.
Independent Control Of Active And Reactive Powers From DFIG By Logic FuzzyIJRES Journal
This paper presents the study and use by simulating the fuzzy logic control of asynchronous
generator dual fuel in the production of electrical energy that the .for I prepared a study of the wind system and
a model of the wind turbine was established by following the study and modeling of doubly fed asynchronous.
Two types of vector control have been the subject of study in this work for independent control of active and
reactive power: the direct and indirect control .la fuzzy PI control is introduced to increase the robustness of
markers vis-à-screw parametric variation of the machine in the simulation results obtained were compared to the
validated work articles cited in the bibliography.
This document summarizes a research paper that proposes a hybrid power system combining wind and photovoltaic energy sources to provide an independent power supply. The system includes a solar photovoltaic array and a wind turbine with a doubly fed induction generator (DFG). A part of the power generated by the photovoltaic system is used to supply the rotor of the DFG while the rest is injected into the grid. Fuzzy logic control is used to regulate the power generated and injected into the grid by both energy conversion systems. The paper models the system components, describes the control strategy using fuzzy logic, and presents simulation results validating the approach.
Several algorithms have been offered to track the Maximum Power Point when we have one maximum power point. Moreover, fuzzy control and neural was utilized to track the Maximum Power Point when we have multi-peaks power points. In this paper, we will propose an improved Maximum Power Point tracking method for the photovoltaic system utilizing a modified PSO algorithm. The main advantage of the method is the decreasing of the steady state oscillation (to practically zero) once the Maximum Power Point is located. moreover, the proposed method has the ability to track the Maximum Power Point for the extreme environmental condition that cause the presence of maximum multi-power points, for example, partial shading condition and large fluctuations of insolation. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out under very challenging circumstance, namely step changes in irradiance, step changes in load, and partial shading of the Photovoltaic array. Finally, its performance is compared with the perturbation and observation” and fuzzy logic results for the single peak, and the neural-fuzzy control results for the multi-peaks.
This paper reports on the design and implementation in DSP as hardware in the loop of a nonlinear control strategy for a grid-connected variable speed wind turbine using a doubly fed induction generator (DFIG). The objective of this work is to build a real-time nonlinear hybrid approach combining Backstepping control and sliding mode control strategies for DFIG used in wind energy conversion systems (WECS). The results of the DSP implementation are discussed and qualitative and quantitative performance evaluations are performed under various disturbed conditions. The implementation is performed using the TMS320F28335 DSP combined with the MATLAB/Simulink (2016a) environment. The experimental results have been satisfactorily achieved, which implies that the proposed strategy is an efficient and robust approach to monitor the WECS.
Indirect power control of DFIG based on wind turbine operating in MPPT using ...IJECEIAES
This paper describes a MPPT control of the stator powers of a DFIG operating within a wind energy system using the backstepping control technique. The objective of this work consists of providing a robust control to the rotor-side converter allowing the stator active power to be regulated at the maximum power extracted from the wind turbine, as well as maintaining the stator reactive power at zero to maintain the power factor at unity, under various conditions. We have used the Matlab/Simulink platform to model the wind system based on a 7.5 kW DFIG and to implement the MPPT control algorithm in a first step, then we have implemented the field-oriented control and the backstepping controller in a second step. The simulation results obtained were very satisfactory with a fast transient response and neglected power ripples. They furthermore confirmed the high robustness of the approach used in dealing with the variation of the internal parameters of the machine.
This document summarizes a research article that addresses controlling a wind energy conversion system (WECS) consisting of a wind turbine connected to the grid via a doubly fed induction generator (DFIG) and an AC/DC/AC converter. The control objectives are to: 1) control the generator speed to track an optimal reference, 2) control the stator reactive power to be null, 3) regulate the DC-link voltage to a constant value, and 4) ensure a unitary power factor. A high gain observer is designed to estimate unmeasurable mechanical variables. A sliding mode controller is developed using the observer to achieve the control objectives. Simulation results using MATLAB/SIMULINK evaluate the performance of the proposed controller under a
This document summarizes an article from the International Journal of Power Electronics and Drive Systems that presents a dynamic power management model for a standalone DC microgrid using a Combined PI and Hysteresis Control (CPIHC) technique. The proposed microgrid includes a solar PV array, lead-acid battery storage, and constant/dynamic loads. Simulation results show the CPIHC technique efficiently manages power flow, regulates the DC link voltage, and maintains the battery's state of charge, performing better than a conventional Combined PI and Droop Control approach. The document provides background on various control methods used in microgrids and describes the modeling and simulation of the key components in the proposed standalone DC microgrid system.
This paper proposes a feedback linearization control of doubly fed induction generator based wind energy systems for improving decoupled control of the active and reactive powers stator. In order to enhance dynamic performance of the controller studied, the adopted control is reinforced by a fuzzy logic controller. This approach is designed without any model of rotor flux estimation. The difficulty of measuring of rotor flux is overcome by using high gain observer. The stability of the nonlinear observer is proved by the Lyapunov theory. Numerical simulations using MATLAB-SIMULINK shown clearly the robustness of the proposed control, particularly to the disturbance rejection and parametric variations compared with the conventional method.
IRJET- Improvement of Power System Stability in Wind Turbine by using Facts D...IRJET Journal
This document summarizes a research paper that proposes using a predictive power control strategy to improve the stability of power systems with wind farms that use doubly fed induction generator wind turbines. The strategy involves using a super capacitor energy storage system to control the active power from the grid side converter and using a static synchronous series compensator to reduce low frequency oscillations. A model predictive control approach is used to predict the future system response and increase damping. Simulation results on MATLAB/Simulink show the control strategy is able to stabilize voltage and current signals within 0.25 and 0.29 seconds respectively, improving upon conventional PI control.
A vertical wind turbine monitoring system using commercial online digital das...IJECEIAES
The output of a green energy generator is required to be monitor continuously. The monitoring process is important because the performance of the energy gen- erator needs to be known and evaluate. However, monitoring the generator manu- ally and efficiently is troublesome. Moreover, when most of the energy generator located at uneasy to reach or at a very remote place. Added to the cost, human intervention for the monitoring process contributes to the unnecessary bill. All the highlighted limitations can be overcome using an internet cloud base system and application. Most of the existing data logging instruments use a memory card or personal computer in their operation. The stored data is accessible only at a dedicated computer alone. This work presented a complete energy generator interface with a commercial online digital dashboard. The digital dashboard, parameters of the wind turbine, such as the amount of power generates and the magnitude of instantaneous voltage can be monitored, and the recorded data can be accessed quickly, at any time and anyplace.
Adıgüzel Hydroelectric Power Plant’s Modelling and LoadFrequency Control by F...IJERA Editor
In this study, to realize the load-frequency control according to different loading statuses, modelling of dynamic
behaviour of the Adıgüzel Hydroelectric Power Plant (HEPP) was made by using the Matlab/Simulink program.
By establishing the dynamic model of 36MVA synchronous generator and other components in the system in a
manner reflecting its behaviour in the real system, performance of classical controller and self-adjusting fuzzy
logic controller in electro-hydraulic governor circuit was examined according to different load statuses. During
the simulation works carried out when both control systems closely watched in the fuzzy logic control system
according to different loads the frequency of load and the number of frequency have been observed to be stable
in short period of time and allowed tolerance limits.
Study of Characteristics of DFIG Based Wind TurbineIJMTST Journal
In this paper the study of active power, reactive power, stator current, rotor current and grid voltage characteristics of doubly fed induction generator based wind turbine are studied. The pulses for the stator and rotor are applied by using a hysteresis current controller. The main drawback of wind energy conversion system is that it is highly nonlinear. To overcome this problem a fuzzy controller on rotor side and a discrete PID controller on stator side are applied. The active and reactive powers are controlled by this nonlinear strategy. The active power is maximized by these both controllers. The entire simulation is conducted on mat lab/simulink. The results obtained are satisfactory.
This document presents a study on modeling a photovoltaic system with maximum power point tracking (MPPT) control using neural networks. It discusses modeling the photovoltaic module and cell using equations. An artificial neural network model with three layers (input, hidden, output) is proposed to identify the maximum power point. Simulation results using Matlab/Simulink show the effectiveness of the neural network technique in improving photovoltaic system performance and maximizing power extraction compared to conventional MPPT methods. The document also analyzes how temperature and solar radiation influence the current-voltage and power-voltage characteristics of the photovoltaic module.
The document describes the design and implementation of a hybrid renewable energy system using solar power, small hydro power and stair climbing power. A programmable logic controller (PLC) and supervisory control and data acquisition (SCADA) technology are used to monitor and control the system. The system can operate both on-grid and off-grid. Experimental results show the system is able to generate around 600W of power from the hybrid sources. The system proves to be an effective way to provide power for remote and domestic applications.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Experimental Testing of a Real-Time Implementation of a PMU-Based Wide-Area D...Power System Operation
The modern power grid is being used under operating conditions of increasing stress, giving
rise to grid stability issues. One of these stability issues is the phenomenon of inter-area oscillations.
Simulations have demonstrated the advantages of Wide-area Measurement Signals (WAMS)-based Oscillation Damping Controls in achieving improved electromechanical mode damping compared to traditional,
local signal-based Power System Stabilizers (PSS). This work takes an existing Phasor-based oscillation
damping (POD) algorithm and uses it to implement a proof-of-concept, wide-area, real-time controller
on National Instruments hardware. The developed prototype is tested in a real-time Hardware-in-theloop setup (RT-HIL) using OPAL-RT’s eMEGASIM real-time simulation platform and synchrophasor data
from actual Phasor Measurement Units (PMUs). The prototype and experiments provide insight into the
feasibility and real-world limitations of wide-area controls. Further, it is demonstrated how the proposed
control architecture has applications independent of the controlled power system device. Challenges faced,
the solutions implemented together with the present prototype’s limitations are also discussed.
To design and implementation of variable and constant with no load for induction motor (IM) that is the goal in this work. This paper was including three parts, first the simulation model with no load for IM, Second the simulation model with constant load for IM, Third the simulation model with variable load for IM. In addition, this work includes comparative between two different controllers (PI and fuzzy logic control (FLC). The simulation results clearly the implementation of variable and constant with no load for IM. The simulation response of the system achieves better results when choosing to use type fuzzy-PI controller technique comparison with conventional PI controller and improve the performance of the system at different operation conditions.
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...IAES-IJPEDS
This document summarizes a research paper that proposes using fuzzy logic control for a Doubly Fed Induction Generator (DFIG) wind turbine system, compared to traditional PI control.
1) A fuzzy logic controller is designed for the rotor side converter to independently control the active and reactive power output of the DFIG and regulate the voltage, with the goal of improving dynamic performance under faulty conditions compared to PI control.
2) Simulation results using MATLAB/Simulink are presented for different fault scenarios, showing the fuzzy logic control provides better power quality, stability and performance than PI control for the DFIG wind turbine system.
3) The fuzzy logic controller does not require an exact mathematical model of the system, instead
Similar to Artificial Intelligence Control Applied in Wind Energy Conversion System (20)
The aim of this research is the speed tracking of the permanent magnet synchronous motor (PMSM) using an intelligent Neural-Network based adapative backstepping control. First, the model of PMSM in the Park synchronous frame is derived. Then, the PMSM speed regulation is investigated using the classical method utilizing the field oriented control theory. Thereafter, a robust nonlinear controller employing an adaptive backstepping strategy is investigated in order to achieve a good performance tracking objective under motor parameters changing and external load torque application. In the final step, a neural network estimator is integrated with the adaptive controller to estimate the motor parameters values and the load disturbance value for enhancing the effectiveness of the adaptive backstepping controller. The robsutness of the presented control algorithm is demonstrated using simulation tests. The obtained results clearly demonstrate that the presented NN-adaptive control algorithm can provide good trackingperformances for the speed trackingin the presence of motor parameter variation and load application.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different x- and y-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both x- and y-directions are used for the training and testing of the network.
This paper focuses on the artificial bee colony (ABC) algorithm, which is a nonlinear optimization problem. is proposed to find the optimal power flow (OPF). To solve this problem, we will apply the ABC algorithm to a power system incorporating wind power. The proposed approach is applied on a standard IEEE-30 system with wind farms located on different buses and with different penetration levels to show the impact of wind farms on the system in order to obtain the optimal settings of control variables of the OPF problem. Based on technical results obtained, the ABC algorithm is shown to achieve a lower cost and losses than the other methods applied, while incorporating wind power into the system, high performance would be gained.
The significance of the solar energy is to intensify the effectiveness of the Solar Panel with the use of a primordial solar tracking system. Here we propounded a solar positioning system with the use of the global positioning system (GPS) , artificial neural network (ANN) and image processing (IP) . The azimuth angle of the sun is evaluated using GPS which provide latitude, date, longitude and time. The image processing used to find sun image through which centroid of sun is calculated and finally by comparing the centroid of sun with GPS quadrate to achieve optimum tracking point. Weather conditions and situation observed through AI decision making with the help of IP algorithms. The presented advance adaptation is analyzed and established via experimental effects which might be made available on the memory of the cloud carrier for systematization. The proposed system improve power gain by 59.21% and 10.32% compare to stable system (SS) and two-axis solar following system (TASF) respectively. The reduced tracking error of IoT based Two-axis solar following system (IoT-TASF) reduces their azimuth angle error by 0.20 degree.
Kosovo has limited renewable energy resources and its power generation sector is based on fossil fuels. Such a situation emphasizes the importance of active research and efficient use of renewable energy potential. According to the analysis of meteorological data for Kosovo, it can be concluded that among the most attractive potential wind power sites are the locations known as Kitka (42° 29' 41" N and 21° 36' 45" E) and Koznica (42° 39′ 32″ N, 21° 22′30″E). The two terrains in which the analysis was carried out are mountain areas, with altitudes of 1142 m (Kitka) and 1230 m (Koznica). the same measuring height, about 84 m above the ground, is obtained for these average wind speeds: Kitka 6,667 m/s and Koznica 6,16 m/s. Since the difference in wind speed is quite large versus a difference in altitude that is not being very large, analyses are made regarding the terrain characteristics including the terrain relief features. In this paper it will be studied how much the roughness of the terrain influences the output energy. Also, that the assumption to be taken the same as to how much they will affect the annual energy produced.
The document summarizes a research paper that proposes using a battery energy storage system (BESS) with droop control to reduce frequency fluctuations in a multi-machine power system connected to a large-scale photovoltaic (PV) plant. The paper develops a droop control strategy for the BESS that incorporates a frequency error signal and dead-band. Simulation results using PSCAD/EMTDC software show that the proposed droop control-based BESS can efficiently curtail frequency oscillations caused by fluctuations in PV power injection due to changing solar irradiance.
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 paper focuses on the modeling and control of a wind energy conversion chain using a permanent magnet synchronous machine. This system behaves a turbine, a generator, DC/DC and DC/AC power converters. These are connected on both sides to the DC bus, where the inverter is followed by a filter which is connected to the grid. In this paper, we have been used two types of controllers. For the stator side converter, we consider the Takagi-Sugeno approach where the parameters of controller have been computed by the theory of linear matrix inequalities. The stability synthesis has been checked using the Lyapunov theory. According to the grid side converter, the proportional integral controller is exploited to keep a constant voltage on the DC bus and control both types of powers. The simulation results demonstrate the robustness of the approach used.
The development of modeling wind speed plays a very important in helping to obtain the actual wind speed data for the benefit of the power plant planning in the future. The wind speed in this paper is obtained from a PCE-FWS 20 type measuring instrument with a duration of 30 minutes which is accumulated into monthly data for one year (2019). Despite the many wind speed modeling that has been done by researchers. Modeling wind speeds proposed in this study were obtained from the modified Rayleigh distribution. In this study, the Rayleigh scale factor (Cr) and modified Rayleigh scale factor (Cm) were calculated. The observed wind speed is compared with the predicted wind characteristics. The data fit test used correlation coefficient (R2), root means square error (RMSE), and mean absolute percentage error (MAPE). The results of the proposed modified Rayleigh model provide very good results for users.
This paper deals with an advanced design for a pump powered by solar energyto supply agricultural lands with water and also the maximum power point is used to extract the maximum value of the energy available inside the solar panels and comparing between techniques MPPT such as Incremental conductance, perturb & observe, fractional short current circuit, and fractional open voltage circuit to find the best technique among these. The solar system is designed with main parts: photovoltaic (PV) panel, direct current/direct current (DC/DC) converter, inverter, filter, and in addition, the battery is used to save energy in the event that there is an increased demand for energy and not to provide solar radiation, as well as saving energy in the case of generation more than demand. This work was done using the matrix laboratory (MATLAB) simulink program.
The objective of this paper is to provide an overview of the current state of renewable energy resources in Bangladesh, as well as to examine various forms of renewable energies in order to gain a comprehensive understanding of how to address Bangladesh's power crisis issues in a sustainable manner. Electricity is currently the most useful kind of energy in Bangladesh. It has a substantial influence on a country's socioeconomic standing and living standards. Maintaining a stable source of energy at a cost that is affordable to everyone has been a constant battle for decades. Bangladesh is blessed with a wealth of natural resources. Bangladesh has a huge opportunity to accelerate its economic development while increasing energy access, livelihoods, and health for millions of people in a sustainable way due to the renewable energy system.
When the irradiance distribution over the photovoltaic panels is uniform, the pursuit of the maximum power point is not reached, which has allowed several researchers to use traditional MPPT techniques to solve this problem Among these techniques a PSO algorithm is used to have the maximum global power point (GMPPT) under partial shading. On the other hand, this one is not reliable vis-à-vis the pursuit of the MPPT. Therefore, in this paper we have treated another technique based on a new modified PSO algorithm so that the power can reach its maximum point. The PSO algorithm is based on the heuristic method which guarantees not only the obtaining of MPPT but also the simplicity of control and less expensive of the system. The results are obtained using MATLAB show that the proposed modified PSO algorithm performs better than conventional PSO and is robust to different partial shading models.
A stable operation of wind turbines connected to the grid is an essential requirement to ensure the reliability and stability of the power system. To achieve such operational objective, installing static synchronous compensator static synchronous compensator (STATCOM) as a main compensation device guarantees the voltage stability enhancement of the wind farm connected to distribution network at different operating scenarios. STATCOM either supplies or absorbs reactive power in order to ensure the voltage profile within the standard-margins and to avoid turbine tripping, accordingly. This paper present new study that investigates the most suitable-location to install STATCOM in a distribution system connected wind farm to maintain the voltage-levels within the stability margins. For a large-scale squirrel cage induction generator squirrel-cage induction generator (SCIG-based) wind turbine system, the impact of STATCOM installation was tested in different places and voltage-levels in the distribution system. The proposed method effectiveness in enhancing the voltage profile and balancing the reactive power is validated, the results were repeated for different scenarios of expected contingencies. The voltage profile, power flow, and reactive power balance of the distribution system are observed using MATLAB/Simulink software.
The electrical and environmental parameters of polymer solar cells (PSC) provide important information on their performance. In the present article we study the influence of temperature on the voltage-current (I-V) characteristic at different temperatures from 10 °C to 90 °C, and important parameters like bandgap energy Eg, and the energy conversion efficiency η. The one-diode electrical model, normally used for semiconductor cells, has been tested and validated for the polemeral junction. The PSC used in our study are formed by the poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl C61-butyric acid methyl ester (PCBM). Our technique is based on the combination of two steps; the first use the Least Mean Squares (LMS) method while the second use the Newton-Raphson algorithm. The found results are compared to other recently published works, they show that the developed approach is very accurate. This precision is proved by the minimal values of statistical errors (RMSE) and the good agreement between both the experimental data and the I-V simulated curves. The obtained results show a clear and a monotonic dependence of the cell efficiency on the studied parameters.
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.
The document describes a proposed modified bridge-type nonsuperconducting fault current limiter (NSFCL) for distribution networks. The NSFCL consists of a bridge rectifier, two DC reactors (one small in series and one large in parallel), and an IGBT semiconductor switch controlled by a command circuit. During normal operation, the IGBT is on and the parallel reactor is bypassed, making the NSFCL invisible. During a fault, the IGBT turns off, inserting the parallel reactor to limit fault current. Simulation results showed the design effectively limits fault current while minimally affecting normal operation.
This paper provides a new approach to reducing high-order harmonics in 400 Hz inverter using a three-level neutral-point clamped (NPC) converter. A voltage control loop using the harmonic compensation combined with NPC clamping diode control technology. The capacitor voltage imbalance also causes harmonics in the output voltage. For 400 Hz inverter, maintain a balanced voltage between the two input (direct current) (DC) capacitors is difficult because the pulse width modulation (PWM) modulation frequency ratio is low compared to the frequency of the output voltage. A method of determining the current flowing into the capacitor to control the voltage on the two balanced capacitors to ensure fast response reversal is also given in this paper. The combination of a high-harmonic resonator controller and a neutral-point voltage controller working together on the 400 Hz NPC inverter structure is given in this paper.
Direct current (DC) electronic load is a useful equipment for testing the electrical system. It can emulate various load at a high rating. The electronic load requires a power converter to operate and a linear regulator is a common option. Nonetheless, it is hard to control due to the temperature variation. This paper proposed a DC electronic load using the boost converter. The proposed electronic load operates in the continuous current mode and control using the integral controller. The electronic load using the boost converter is compared with the electronic load using the linear regulator. The results show that the boost converter able to operate as an electronic load with an error lower than 0.5% and response time lower than 13 ms.
This paper presents a new simplified cascade multiphase DC-DC buck power converter suitable for low voltage and large current applications. Cascade connection enables very low voltage ratio without using very small duty cycles nor transformers. Large current with very low ripple content is achieved by using the multiphase technique. The proposed converter needs smaller number of components compared to conventional cascade multiphase DC-DC buck power converters. This paper also presents useful analysis of the proposed DC-DC buck power converter with a method to optimize the phase and cascade number. Simulation and experimental results are included to verify the basic performance of the proposed DC-DC buck power converter.
More from International Journal of Power Electronics and Drive Systems (20)
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
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572
control of P-Q without mechanical sensor for DFIG-based WECS with intelligent controllers. They are
focused on the implementation of fuzzy logic controllers combined with conventional PI for the adjustment
of active and reactive power.
In these last years, a big interest is given to the use of neural network in identification and control of
the nonlinear systems [9] [10]; this is mainly due to their capacities of training and generalization. Mishra et
al [9] have developed an indirect vector control by implementing intelligent controllers (Fuzzy and Neural
netwerk) to control the speed of an induction motor (IM), they have concluded that the controller based on
the neural network has a more robust than the PI and fuzzy logic controllers.
This paper presents a comparison between the WECS performance using PI and NN controllers. The
PI regulator is simple and easy in implementation and gives acceptable performances, but it hasn't robustness
in case of parameter variations.The neural network controller is proved to be an interesting method for the
design of controllers and applied in many fields because of its excellent properties, such as insensitivity to
external disturbances and parameter variations, It can present also fast dynamic responses if the switching
devices support a high frequency. The studied system is presented in (Figure 1).
Figure 1. Diagram of the studied system
2. MODELING AND CONTROL OF DFIG
2.1. DFIG modeling
The Park transformation of the DFIG electrical equations gives the following equations [11]-[14]:
rd
r
dt
rq
d
rq
i
r
R
rq
V
rq
r
dt
rd
d
rd
i
r
R
rd
V
sd
s
dt
sq
d
sq
i
s
R
sq
V
sq
s
dt
sd
d
sd
i
s
R
sd
V
(1)
The fields are given by:
sq
i
sr
M
rq
i
r
L
rq
sd
i
sr
M
rd
i
r
L
rd
rq
i
sr
M
sq
i
s
L
sq
rd
i
sr
M
sd
i
s
L
sd
(2)
The electromagnetic torque is given by:
rq
i
sd
rd
i
sq
s
L
r
s
M
P
em
C
(3)
mec
f
r
C
em
C
dt
mec
d
J
.
(4)
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2.2. Power control
To easily control the electrical power produced by the DFIG, an independent control of the active
and reactive powers is applied by FOC of stator. The principle of this method consists in aligning stator field
along the d axis of Park reference frame in order to eliminate the coupling between the powers. (Figure 2)
[3] [15]. We have a quadratic stator flux null ( 0
sq
), then the direct stator flux is given by s
sd
. The
equation systems (1) and (2) can be simplified as the following form:
rd
r
dt
rq
d
rq
i
r
R
rq
V
rq
r
dt
rd
d
rd
i
r
R
rd
V
s
s
sq
i
s
R
sq
V
sd
i
s
R
sd
V
(5)
For the high power machines, the resistance of the stator windings are neglected. Equation 6.
Figure 2. Position of the stator flux [16] [17].
rd
r
dt
rq
d
rq
i
r
R
rq
V
rq
r
dt
rd
d
rd
i
r
R
rd
V
s
s
s
V
sq
V
sd
V
0
(6)
sq
i
sr
M
rq
i
r
L
rq
sd
i
sr
M
rd
i
r
L
rd
rq
i
sr
M
sq
i
s
L
rd
i
sr
M
sd
i
s
L
s
0
(7)
irq
s
Ls
Msr
P
Cem
(8)
The active and reactive stator power in the Park reference, are written as:
sq
i
sd
v
sd
i
sq
v
Q
sq
i
sq
v
sd
i
sd
v
P
(9)
According to FOC, the equation systems (9) can be simplified as:
sd
i
s
v
Q
sq
i
s
v
P
(10)
rq
i
s
L
Msr
sq
i
rd
i
s
L
Msr
s
L
s
s
V
sd
i
.
.
(11)
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574
s
s
L
s
V
rd
i
s
L
sr
M
s
V
Q
rq
i
s
L
sr
M
s
V
P
2
(12)
rq
i
s
L
sr
M
r
L
rq
s
L
s
s
V
sr
M
rd
i
s
L
sr
M
r
L
rd
2
2
(13)
s
L
s
V
sr
M
g
rd
i
s
L
sr
M
r
L
s
g
dt
rq
di
s
L
sr
M
r
L
rq
i
r
R
rq
V
rq
i
s
L
sr
M
r
L
s
g
dt
rd
di
s
L
sr
M
r
L
rd
i
r
R
rd
V
2
2
2
2
(14)
2.3. Control of active and reactive powers of DFIG
The decoupling of the active and reactive powers is due to voltages and currents which are evaluated
using transient equations of the machine [18]. This method is favored with microprocessors, but it is very
sensitive to parameter variations of the machine. The voltages are calculated using the power equation.
2 2
m m
r r r
2
s s
r s s
m
s r
s m s s m s s m
s s
2 2
m m
r r r
2
s s
s
m
s s r
s s m s
s
s
L L
L R L
L L R V V
L
V g P p Q L p
dr V L V L L L L
m
L L
L L
R L L
L L V
L
V p P g Q g L
qr V L V L L
m
L
L
* *
* *
s m
L
(15)
In this used method, the power is controlled using two cascade controllers, the first is the power
controller and the second is the current controller. Figure 3.
Figure 3. Control diagram of DFIG.
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3. NEURAL NETWORK CONTROL
The use of an analogical controller leads to the performance degradation in nonlinear and several
processes [19], [10]. Many intelligent control methods have been applied on DFIG as fuzzy control, neural
networks [20], [10].
The use of neural networks is a technique for controlling complex systems can be justified by its
simplicity of implementation (preliminary mathematical analysis) [21], [10]. In this work, we consider the
process as a black box that has the ability to control the minimum of process informations. The idea is to
replace the four PI regulators of FOC by neural regulators (NN) simple. For the training of the neural weights
from PI regulators, we use an algorithm of back-propagation called the algorithm of Levenberg-Marquardt
(LM) [22] [23].
Each neural network has a function that is well defined depending on selected architecture (hidden
layers number and neural number in each hidden layer). The problem is to find the NN regulator that gives
the better results. In our case, we take a structure of neural network with only one hidden layer that
containing three neurons using the sigmoid transfer function (Figure 4).
Figure 4. Configuration of the multilevel perceptrons: (1-3-1).
The global diagram of FOC control with neural network regulators is presented in (Figure 5).
Figure 5. Global diagram of FOC control with neural network regulators
4. SIMULATION RESULTS
To prove the robustness and effectiveness of proposed control system, we apply the previous
proposed controller to control of the deoubly-fed induction generator with wind energy conversion system.
The generator and conversion system parameters are given in appendix. The configuration of the overall
control system is shown in Fig.05. It mainly consists of a doubly-fed induction generator, a ramp comparison
current-controlled pulse width modulated (PWM) inverter, an inverse park, a field oriented control and an
outer power feedback control loops. Two different operating conditions are simulated, reference tracking and
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robustness against DFIG parameters variation, to illustrate the operation of the PI controller, RST controller
and the proposed NN regulators.
4.1. The reference tracking
In this test, the simulation has been done with the rated parameters of the DFIM. This test consists
of step changes in active and reactive powers in order to observe the system behavior with the proposed
controller. The active and reactive power changes are made at 0.35sec and 0.45sec, respectively.
The performance of wind energy conversion system with DFIG under this operating points test is
shown in figure 6. This figure shows the active and reactive power responses for the PI, RST and NN
controllers. The obtained results that are shown in figure 6 prove that the proposed controller has good
performances in active and reactive power tracking. It is clearly observed that the oscillations decrease and
the proposed NN controller present minimal rising time, no overshoot and negligible steady-state error
compared to PI and RST regulators.
Figure 6. Simulation results for reference tracking using PI, RST and NN regulators.
4.2. Robustness test aginst parameter variation
The effectiveness of the proposed WECS with DFIG for the different controller has been tested
under DFIG parameters variation. This second test consists of change on rated values of rotor resistance,
stator inductance, rotor and mutual inductances. The applied variation rotor resistance is 50% of its nominal
value whereas the stator and rotor inductance has been increased by 10% to their rated values. Finally, a
decrease of 10% on the mutual inductance has been done.The performances of WECS with DFIG under this
operating points test are depicted in figure 7-10. Figure 7 shows the simulation results of the system using the
different controllers for rotor resistance variation. We notice here that the same reference of active and
reactive power has taken for this test. From the simulation results, it is clearly observed that the system is not
sensitive to this parameter variation and the NN controller shows good performance compared to another
controller (PI and RST regulator). The performance of the system in the presence of the rotor and stator
inductances are depicted in figure 8 and 9. Form the simulation results, it can be seen that the variation in
rotor or stator inductances has an important effect on the control performance of WECS for the PI and RST
regulators. However, the NN regulator presents the best performance in active and reactive responses
compared to classical PI and RST regulators.
Finally, the dynamic responses of the wind energy conversion system equipped whit DFIG system
under mutual inductance variation are illustrated in figure 10. The obtained results showed that mutual
inductance has an important effect on the system responses for the classical regulators. However, the NN
regulator can keep the same characteristics against this variation with a small effect on the rise time response.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
-20
-15
-10
-5
0
5
x 10
5
Time (s)
Active
power
(W)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
-1
-0.5
0
0.5
1
x 10
6
Time (s)
Reactive
power
(var)
Ps
ref
Ps
(PI)
Ps
(NN)
Ps
(RST)
Qs
ref
Qs
(PI)
Qs
(NN)
QS
(RST)
7. Int J Pow Elec & Dri Syst ISSN: 2088-8694
Artificial Intelligence Control Applied in Wind Energy Conversion System (Arama Fatima Zohra)
577
Figure 7. Simulation results for reference tracking
using PI, RST and NN regulators with rotor
resistance variation (+50 %)
Figure 8. Simulation results for reference tracking
using PI, RST and NN regulators with stator
inductance variation (+10 %).
Figure 9. Simulation results for reference tracking
using PI, RST and NN regulators with rotor
inductance variation (+10 %)
Figure 10. Simulation results for reference tracking
using PI, RST and NN regulators with mutual
inductance variation (-10 %)
5. CONCLUSION
This paper presented a WECS based on DFIG. The studied device is composed of a DFIG with the
rotor connected to the grid via a converter. The FOC of DFIG has been presented to regulate the active and
reactive powers of the machine. The regulation is made with PI, RST regulators and with neural networks.
The architecture of the neural network corrector retained is 1-3-1. It enabled us to improve the dynamic and
static performances of the DFIG. Three different controllers are analyzed and compared. In the case of power
reference tracking, the performances of the three controllers are almost similar but with a faster response time
for the regulator neural network. A robustness test has also been investigated where the machine’s parameters
have been modified, the impact on the active and reactive powers values is important for PI controller
whereas it is almost negligible for NN regulators.
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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
-20
-15
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-5
0
5
x 10
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Time (s)
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0
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1
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Qs
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Qs
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Qs
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ref
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(W)
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x 10
6
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power
(var)
Qs
ref
Qs
(PI)
Qs
(RST)
Qs
(NN)
Ps
ref
Ps
(PI)
Ps
(RST)
Ps
(NN)
8. ISSN: 2088-8694
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APPENDIX
Table 1. Parameters of DFIM
Symbol Value
Rated Power PN 1.5 MW
Stator resistance Rs 0.012
Rotor resistance Rr 0.021
Stator inductance Ls 0.0137 H
Rotor inductance Lr 0.0136 H
Mutual inductance Lm 0 0.0135 H
The friction coefficient fr 0.0024 N.m.s1
Slip g 0.03
Pole Pairs p 2
Table 2. Parameters of Turbine
Symbol Value
Radius of the wind
turbine R
35.25 m
Gear box G 90
inertia J 1000 kg.m ²
Surface swept by
rotor S
π ∙ R² m ²
Air density 1.22 kg/ m 3
Table 3. Parameters of Feed
Symbol Value
Stator rated voltage
Vs Rated
398/690V
Frequency stator f 50 Hz
Rotor rated voltage Vr 225/389 V
Rated frequency
stator f2
14 Hz