This document summarizes research on analyzing the steady-state performance of a self-excited induction generator using three optimization techniques: genetic algorithms, pattern search, and quasi-Newton methods. It provides background on induction generators and how they can operate as self-excited generators by connecting capacitors to the stator terminals. The document presents the standard steady-state equivalent circuit model and derives nonlinear equations that are solved using the three optimization techniques to determine unknown parameters. The performance of the self-excited induction generator is then evaluated based on the determined parameters.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problemijeei-iaes
This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA) for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
This paper presents a grid-connected photovoltaic system (PV) used as a shunt active power filter (SAPF) to provide the power factor correction, harmonic elimination, reactive power compensation and to simultaneously supply power from a PV system to the utility. A direct power control (DPC) method is used for controlling the system to feed the photovoltaic energy in synchronization with grid and provide power quality improvement. The PI parameters of DC-link voltage controller are tuned using the Particle Swarm Optimization (PSO) algorithm without the need for an exact mathematical model of system. This PI-PSO controller gives better results for robustness, harmonic minimization and reduces the overshoot and undershoots of PI controller. The overall control of system is tested in Matlab/Simulink environment. Then, the simulations results demonstrate the robustness and feasibility of proposed method.
Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problemijeei-iaes
This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA) for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality of wolf is possessing both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .
This paper presents a grid-connected photovoltaic system (PV) used as a shunt active power filter (SAPF) to provide the power factor correction, harmonic elimination, reactive power compensation and to simultaneously supply power from a PV system to the utility. A direct power control (DPC) method is used for controlling the system to feed the photovoltaic energy in synchronization with grid and provide power quality improvement. The PI parameters of DC-link voltage controller are tuned using the Particle Swarm Optimization (PSO) algorithm without the need for an exact mathematical model of system. This PI-PSO controller gives better results for robustness, harmonic minimization and reduces the overshoot and undershoots of PI controller. The overall control of system is tested in Matlab/Simulink environment. Then, the simulations results demonstrate the robustness and feasibility of proposed method.
Metric Projections to Identify Critical Points in Electric Power Systemstheijes
The identification of weak nodes and branches involved have been analyzed with different technical of analysis as: sensitivities, modal and of the singular minimum value, applying the Jacobian matrix of load flows. We show up a metric projections application to identify weak nodes and branches with more participation in the electric power system.
Line Losses in the 14-Bus Power System Network using UPFCIDES Editor
Controlling power flow in modern power systems
can be made more flexible by the use of recent developments
in power electronic and computing control technology. The
Unified Power Flow Controller (UPFC) is a Flexible AC
transmission system (FACTS) device that can control all the
three system variables namely line reactance, magnitude and
phase angle difference of voltage across the line. The UPFC
provides a promising means to control power flow in modern
power systems. Essentially the performance depends on proper
control setting achievable through a power flow analysis
program. This paper presents a reliable method to meet the
requirements by developing a Newton-Raphson based load
flow calculation through which control settings of UPFC can
be determined for the pre-specified power flow between the
lines. The proposed method keeps Newton-Raphson Load Flow
(NRLF) algorithm intact and needs (little modification in the
Jacobian matrix). A MATLAB program has been developed to
calculate the control settings of UPFC and the power flow
between the lines after the load flow is converged. Case studies
have been performed on IEEE 5-bus system and 14-bus system
to show that the proposed method is effective. These studies
indicate that the method maintains the basic NRLF properties
such as fast computational speed, high degree of accuracy and
good convergence rate.
Design and Performance Analysis of Genetic based PID-PSS with SVC in a Multi-...IDES Editor
Damping of power system oscillations with the help
of proposed optimal Proportional Integral Derivative Power
System Stabilizer (PID-PSS) and Static Var Compensator
(SVC)-based controllers are thoroughly investigated in this
paper. This study presents robust tuning of PID-PSS and
SVC-based controllers using Genetic Algorithms (GA) in
multi machine power systems by considering detailed model
of the generators (model 1.1). The effectiveness of FACTSbased
controllers in general and SVC-based controller in
particular depends upon their proper location. Modal
controllability and observability are used to locate SVC–based
controller. The performance of the proposed controllers is
compared with conventional lead-lag power system stabilizer
(CPSS) and demonstrated on 10 machines, 39 bus New England
test system. Simulation studies show that the proposed genetic
based PID-PSS with SVC based controller provides better
performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Artificial Intelligence Technique based Reactive Power Planning Incorporating...IDES Editor
Reactive Power Planning is a major concern in the
operation and control of power systems This paper compares
the effectiveness of Evolutionary Programming (EP) and
New Improved Differential Evolution (NIMDE) to solve
Reactive Power Planning (RPP) problem incorporating
FACTS Controllers like Static VAR Compensator (SVC),
Thyristor Controlled Series Capacitor (TCSC) and Unified
power flow controller (UPFC) considering voltage stability.
With help of Fast Voltage Stability Index (FVSI), the critical
lines and buses are identified to install the FACTS controllers.
The optimal settings of the control variables of the generator
voltages,transformer tap settings and allocation and parameter
settings of the SVC,TCSC,UPFC are considered for reactive
power planning. The test and Validation of the proposed
algorithm are conducted on IEEE 30–bus system and 72-bus
Indian system.Simulation results shows that the UPFC gives
better results than SVC and TCSC and the FACTS controllers
reduce the system losses.
Optimized placement of multiple FACTS devices using PSO and CSA algorithms IJECEIAES
This paper is an attempt to develop a multi-facts device placementin deregulated power system using optimization algorithms. The deregulated power system is the recent need in the power distribution as it has many independent sellers and buyers of electricity. The problem of deregulation is the quality of the power distribution as many sellers are involved. The placement of FACTS devices provides the solution for the above problem. There are researches available for multiple FACTS devices. The optimization algorithms like Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are implemented to place the multiple FACTS devices in a power system. MATLAB based implementation is carried out for applying Optimal Power Flow (OPF) with variation in the bus power and the line reactance parameters. The cost function is used as the objective function. The cost reduction of FACTS as well as generation by placement of different compensators like, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC). The cost calculation is done on the 3-seller scenario. The IEEE 14 bus is taken here as 3-seller system.
Power System State Estimation - A ReviewIDES Editor
The aim of this article is to provide a comprehensive
survey on power system state estimation techniques. The
algorithms used for finding the system states under both static
and dynamic state estimations are discussed in brief. The
authors are opinion that the scope of pursuing research in the
area of state estimation with PMU and SCADA measurements
is the state of the art and timely.
1.a fuzzy based pv apf controller for compensating current harmonics (2)EditorJST
The main aim of this paper is to compensate a current harmonics in PV-APF system using Fuzzy Logic Controller. A 3- Ф 3-wire system is proposed in this paper which consists of PV system, a dc/dc converter which is controlled by MPPT, three phase VSC to act as APF and Non-Linear Load. The main theme of this INC MPPT is to efficiency from the PV system. For reliable performance of active power filter and better harmonic compensation this paper propose a concept of instantaneous power theory. Also, a comparison analysis is performed for improving THD by PI/Fuzzy controllers. The proposed system is simulated and verified in MATLAB/SIMULINK software.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Oscillatory Stability Prediction Using PSO Based Synchronizing and Damping To...journalBEEI
This paper presents the assessment of stability domains for the angle stability condition of the power system using Particle Swarm Optimization (PSO) technique. An efficient optimization method using PSO for synchronizing torque coefficients Ksand damping torque coefficients Kd to identify the angle stability condition on multi-machine system. In order to accelerate the determination of angle stability, PSO is proposed to be implemented in this study. The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as Evolutionary Programming (EP) and Artificial Immune System (AIS). Validation with respect to eigenvalues determination, Least Square (LS) method and minimum damping ratio ξmin confirmed that the proposed technique is feasible to solve the angle stability problems.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
The quality of data and the accuracy of energy generation forecast by artific...IJECEIAES
The paper presents the issues related to predicting the amount of energy generation, in a particular wind power plant comprising five generators located in south-eastern Poland. Thelocation of wind power plant, the distribution and type of applied generators, and topographical conditions were given and the correlation between selected weather parameters and the volume of energy generation was discussed. The primary objective of the paper was to select learning data and perform forecasts using artificial neural networks. For comparison, conservative forecasts were also presented. Forecasts results obtained shaw that Artificial Neural Networks are more universal than conservative method. However their forecast accuracy of forecasts strongly depends on the selection of explanatory data.
Voltage Regulators Placement in Unbalanced Radial Distribution Systems for Lo...paperpublications3
Abstract: The Automatic Voltage Regulators (AVRs) help to reduce energy loss and improve the power quality of electric utilities. This paper presents selection of optimal location and tap setting for voltage regulators in Unbalanced Radial Distribution Systems (URDS). Power loss index (PLI) is used for the selection of optimal location of voltage regulators which will first found at each branch except source bus and the bus that has the highest power loss index are picked as the best location for the voltage regulators placement. Particle swarm optimization (PSO), is used for selecting the tap position of voltage regulator in an unbalanced radial distribution system. This algorithm makes the initial selection and tap position setting of the voltage regulators to minimize power losses and provide a good voltage profile along the distribution network and then reduce the total cost to obtain the maximum net savings. The effectiveness of the proposed method is illustrated on a test system of IEEE 33 bus unbalanced radial distribution systems.
Keywords:Unbalanced Radial Distribution Systems (URDS), Load Flow, Power loss index(PLI),Particle swarm optimization(PSO), Voltage Regulator placement, Loss minimization, cost saving.
Passivity Based Control for PV Applications by Using a Buck Power Converter
The use of power converters for everyday applications is becoming more and more important. Current technological applications simultaneously demand a high level of precision and performance, so DC-DC converters have a very important role in systems requiring energy level conversion and adaptation. As part of the work of this paper, we are interested in an analysis of modeling and control law synthesis approaches to ensure stability and a certain level of performance in the entire operating domain. The objective of our research work is therefore to propose a control law whose synthesis is based on a formalized (modeling & control) approach with a view to obtaining a control law adapted to the operating point. The principles used are based on the control and observation by the theory of passivity for the synthesis of control law of buck power converter for PV Applications.
This paper propose a new approach to determine a linear mathematical model of a PV moduel based on an accurate nonlinear model . In this study, electrical parameters at only one operating condition are calculated based on an accurate model. Then, first-order Taylor series approximations apply on the nonlinear model to estimate the proposed model at any operating conditionts. The proposed method determines the number of iteration times. This decreases calculation time and the speed of numerical convergence will be increased. And, it is observed that owing to this method, the system converged and the problem of failing to solve the system because of inappropriate initial values is eliminated. The proposed model is requested in order to allow photovoltaic plants simulations using low-cost computer platforms. The effectiveness of the proposed model is demonstrated for different temperature and irradiance values through conducting a comparison between result of the proposed model and experimental results obtained from the module data-sheet information.
Metric Projections to Identify Critical Points in Electric Power Systemstheijes
The identification of weak nodes and branches involved have been analyzed with different technical of analysis as: sensitivities, modal and of the singular minimum value, applying the Jacobian matrix of load flows. We show up a metric projections application to identify weak nodes and branches with more participation in the electric power system.
Line Losses in the 14-Bus Power System Network using UPFCIDES Editor
Controlling power flow in modern power systems
can be made more flexible by the use of recent developments
in power electronic and computing control technology. The
Unified Power Flow Controller (UPFC) is a Flexible AC
transmission system (FACTS) device that can control all the
three system variables namely line reactance, magnitude and
phase angle difference of voltage across the line. The UPFC
provides a promising means to control power flow in modern
power systems. Essentially the performance depends on proper
control setting achievable through a power flow analysis
program. This paper presents a reliable method to meet the
requirements by developing a Newton-Raphson based load
flow calculation through which control settings of UPFC can
be determined for the pre-specified power flow between the
lines. The proposed method keeps Newton-Raphson Load Flow
(NRLF) algorithm intact and needs (little modification in the
Jacobian matrix). A MATLAB program has been developed to
calculate the control settings of UPFC and the power flow
between the lines after the load flow is converged. Case studies
have been performed on IEEE 5-bus system and 14-bus system
to show that the proposed method is effective. These studies
indicate that the method maintains the basic NRLF properties
such as fast computational speed, high degree of accuracy and
good convergence rate.
Design and Performance Analysis of Genetic based PID-PSS with SVC in a Multi-...IDES Editor
Damping of power system oscillations with the help
of proposed optimal Proportional Integral Derivative Power
System Stabilizer (PID-PSS) and Static Var Compensator
(SVC)-based controllers are thoroughly investigated in this
paper. This study presents robust tuning of PID-PSS and
SVC-based controllers using Genetic Algorithms (GA) in
multi machine power systems by considering detailed model
of the generators (model 1.1). The effectiveness of FACTSbased
controllers in general and SVC-based controller in
particular depends upon their proper location. Modal
controllability and observability are used to locate SVC–based
controller. The performance of the proposed controllers is
compared with conventional lead-lag power system stabilizer
(CPSS) and demonstrated on 10 machines, 39 bus New England
test system. Simulation studies show that the proposed genetic
based PID-PSS with SVC based controller provides better
performance.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Artificial Intelligence Technique based Reactive Power Planning Incorporating...IDES Editor
Reactive Power Planning is a major concern in the
operation and control of power systems This paper compares
the effectiveness of Evolutionary Programming (EP) and
New Improved Differential Evolution (NIMDE) to solve
Reactive Power Planning (RPP) problem incorporating
FACTS Controllers like Static VAR Compensator (SVC),
Thyristor Controlled Series Capacitor (TCSC) and Unified
power flow controller (UPFC) considering voltage stability.
With help of Fast Voltage Stability Index (FVSI), the critical
lines and buses are identified to install the FACTS controllers.
The optimal settings of the control variables of the generator
voltages,transformer tap settings and allocation and parameter
settings of the SVC,TCSC,UPFC are considered for reactive
power planning. The test and Validation of the proposed
algorithm are conducted on IEEE 30–bus system and 72-bus
Indian system.Simulation results shows that the UPFC gives
better results than SVC and TCSC and the FACTS controllers
reduce the system losses.
Optimized placement of multiple FACTS devices using PSO and CSA algorithms IJECEIAES
This paper is an attempt to develop a multi-facts device placementin deregulated power system using optimization algorithms. The deregulated power system is the recent need in the power distribution as it has many independent sellers and buyers of electricity. The problem of deregulation is the quality of the power distribution as many sellers are involved. The placement of FACTS devices provides the solution for the above problem. There are researches available for multiple FACTS devices. The optimization algorithms like Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are implemented to place the multiple FACTS devices in a power system. MATLAB based implementation is carried out for applying Optimal Power Flow (OPF) with variation in the bus power and the line reactance parameters. The cost function is used as the objective function. The cost reduction of FACTS as well as generation by placement of different compensators like, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC). The cost calculation is done on the 3-seller scenario. The IEEE 14 bus is taken here as 3-seller system.
Power System State Estimation - A ReviewIDES Editor
The aim of this article is to provide a comprehensive
survey on power system state estimation techniques. The
algorithms used for finding the system states under both static
and dynamic state estimations are discussed in brief. The
authors are opinion that the scope of pursuing research in the
area of state estimation with PMU and SCADA measurements
is the state of the art and timely.
1.a fuzzy based pv apf controller for compensating current harmonics (2)EditorJST
The main aim of this paper is to compensate a current harmonics in PV-APF system using Fuzzy Logic Controller. A 3- Ф 3-wire system is proposed in this paper which consists of PV system, a dc/dc converter which is controlled by MPPT, three phase VSC to act as APF and Non-Linear Load. The main theme of this INC MPPT is to efficiency from the PV system. For reliable performance of active power filter and better harmonic compensation this paper propose a concept of instantaneous power theory. Also, a comparison analysis is performed for improving THD by PI/Fuzzy controllers. The proposed system is simulated and verified in MATLAB/SIMULINK software.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Oscillatory Stability Prediction Using PSO Based Synchronizing and Damping To...journalBEEI
This paper presents the assessment of stability domains for the angle stability condition of the power system using Particle Swarm Optimization (PSO) technique. An efficient optimization method using PSO for synchronizing torque coefficients Ksand damping torque coefficients Kd to identify the angle stability condition on multi-machine system. In order to accelerate the determination of angle stability, PSO is proposed to be implemented in this study. The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as Evolutionary Programming (EP) and Artificial Immune System (AIS). Validation with respect to eigenvalues determination, Least Square (LS) method and minimum damping ratio ξmin confirmed that the proposed technique is feasible to solve the angle stability problems.
Optimal Placement of DG for Loss Reduction and Voltage Sag Mitigation in Radi...IDES Editor
This paper presents the need to operate the power
system economically and with optimum levels of voltages has
further led to an increase in interest in Distributed
Generation. In order to reduce the power losses and to improve
the voltage in the distribution system, distributed generators
(DGs) are connected to load bus. To reduce the total power
losses in the system, the most important process is to identify
the proper location for fixing and sizing of DGs. It presents a
new methodology using a new population based meta heuristic
approach namely Artificial Bee Colony algorithm(ABC) for
the placement of Distributed Generators(DG) in the radial
distribution systems to reduce the real power losses and to
improve the voltage profile, voltage sag mitigation. The power
loss reduction is important factor for utility companies because
it is directly proportional to the company benefits in a
competitive electricity market, while reaching the better power
quality standards is too important as it has vital effect on
customer orientation. In this paper an ABC algorithm is
developed to gain these goals all together. In order to evaluate
sag mitigation capability of the proposed algorithm, voltage
in voltage sensitive buses is investigated. An existing 20KV
network has been chosen as test network and results are
compared with the proposed method in the radial distribution
system.
The quality of data and the accuracy of energy generation forecast by artific...IJECEIAES
The paper presents the issues related to predicting the amount of energy generation, in a particular wind power plant comprising five generators located in south-eastern Poland. Thelocation of wind power plant, the distribution and type of applied generators, and topographical conditions were given and the correlation between selected weather parameters and the volume of energy generation was discussed. The primary objective of the paper was to select learning data and perform forecasts using artificial neural networks. For comparison, conservative forecasts were also presented. Forecasts results obtained shaw that Artificial Neural Networks are more universal than conservative method. However their forecast accuracy of forecasts strongly depends on the selection of explanatory data.
Voltage Regulators Placement in Unbalanced Radial Distribution Systems for Lo...paperpublications3
Abstract: The Automatic Voltage Regulators (AVRs) help to reduce energy loss and improve the power quality of electric utilities. This paper presents selection of optimal location and tap setting for voltage regulators in Unbalanced Radial Distribution Systems (URDS). Power loss index (PLI) is used for the selection of optimal location of voltage regulators which will first found at each branch except source bus and the bus that has the highest power loss index are picked as the best location for the voltage regulators placement. Particle swarm optimization (PSO), is used for selecting the tap position of voltage regulator in an unbalanced radial distribution system. This algorithm makes the initial selection and tap position setting of the voltage regulators to minimize power losses and provide a good voltage profile along the distribution network and then reduce the total cost to obtain the maximum net savings. The effectiveness of the proposed method is illustrated on a test system of IEEE 33 bus unbalanced radial distribution systems.
Keywords:Unbalanced Radial Distribution Systems (URDS), Load Flow, Power loss index(PLI),Particle swarm optimization(PSO), Voltage Regulator placement, Loss minimization, cost saving.
Passivity Based Control for PV Applications by Using a Buck Power Converter
The use of power converters for everyday applications is becoming more and more important. Current technological applications simultaneously demand a high level of precision and performance, so DC-DC converters have a very important role in systems requiring energy level conversion and adaptation. As part of the work of this paper, we are interested in an analysis of modeling and control law synthesis approaches to ensure stability and a certain level of performance in the entire operating domain. The objective of our research work is therefore to propose a control law whose synthesis is based on a formalized (modeling & control) approach with a view to obtaining a control law adapted to the operating point. The principles used are based on the control and observation by the theory of passivity for the synthesis of control law of buck power converter for PV Applications.
This paper propose a new approach to determine a linear mathematical model of a PV moduel based on an accurate nonlinear model . In this study, electrical parameters at only one operating condition are calculated based on an accurate model. Then, first-order Taylor series approximations apply on the nonlinear model to estimate the proposed model at any operating conditionts. The proposed method determines the number of iteration times. This decreases calculation time and the speed of numerical convergence will be increased. And, it is observed that owing to this method, the system converged and the problem of failing to solve the system because of inappropriate initial values is eliminated. The proposed model is requested in order to allow photovoltaic plants simulations using low-cost computer platforms. The effectiveness of the proposed model is demonstrated for different temperature and irradiance values through conducting a comparison between result of the proposed model and experimental results obtained from the module data-sheet information.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Detection of Broken Bars in Three Phase Squirrel Cage Induction Motor using F...Dr.NAGARAJAN. S
Finite element method is more precise than the winding function approach, as it is based on the actual geometry of the machine and the machine model can easily be modified in order to study the effect of faults on the machine’s performance. Accurate models of the machine under healthy and faulty conditions are developed. This paper presents simulations of broken bars detection in a three phase squirrel cage induction motor under no load, half load and full load conditions for two and eight broken bars. The analysis is done using MagNet.
Comparative Study of the Success of PI and PI-Fuzzy Controller for Induction ...inventionjournals
Asynchronous motors have a wide range of applications in the industry.Therefore, speed control of asynchronous motors is of great importance.Speed control of asynchronous motors based on vector control techniques to achieve high performance.The vector control technique, motor flux and moment variables can be controlled independently of each other.Because of the nonlinear and complex model of asynchronous motors, the speed control applications of these motors are not provided with great efficiency by classical control methods.Fuzzy logic controllers (FLC), which were successful in many areas, present great performance in speed control of an asynchronous motor.In this study, a simulation study regarding speed control of a threephase squirrel cage asynchronous motor was carried out with a PI-Fuzzy type FLC and a conventional PI type controller.The data obtained by simulation are evaluated and the performances of the control methods are compared.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Optimization algorithms for steady state analysis of self excited induction g...IJECEIAES
The current publication is directed to evaluate the steady state performance of three-phase self-excited induction generator (SEIG) utilizing particle swarm optimization (PSO), grey wolf optimization (GWO), wale optimization algorithm (WOA), genetic algorithm (GA), and three MATLAB optimization functions (fminimax, fmincon, fminunc). The behavior of the output voltage and frequency under a vast range of variation in the load, rotational speed and excitation capacitance is examined for each optimizer. A comparison made shows that the most accurate results are obtained with GA followed by GWO. Consequently, GA optimizer can be categorized as the best choice to analyze the generator under various conditions.
This paper compares the reduction of harmonics in various level cascaded H-bridge inverters. The switching angles for the cascaded H-bridge inverter were calculated by evolutionary optimization technique. Fourier analysis is used to determine the switching angles for the desired electrical parameters.
Lower order harmonics such as third, fifth, seventh, ninth and eleventh order harmonics were taken into consideration to reduce the total harmonic distortion. Simulation was done for thirteen, fifteen and seventeen level cascaded H-bridge inverters using Matlab. Total harmonic distortion of voltage and current for R, RL and Motor load were analyzed.
Robust Evolutionary Approach to Mitigate Low Frequency Oscillation in a Multi...IDES Editor
This paper proposes a new optimization algorithm
known as Modified Shuffled Frog Leaping Algorithm (MSFLA)
for optimal designing of PSSs controller. The design problem
of the proposed controller is formulated as an optimization
problem and MSFLA is employed to search for optimal
controller parameters. An eigenvalue based objective function
reflecting the combination of damping factor and damping
ratio is optimized for different operating conditions. The
proposed approach is applied to optimal design of multimachine
power system stabilizers. Three different power
systems, A Single Machine Infinite Bus (SMIB), four-machine
of Kundur and ten-machine New England systems are
considered. The obtained results are evaluated and compared
with other results obtained by Genetic Algorithm (GA).
Eigenvalue analysis and nonlinear system simulations assure
the effectiveness and robustness of the proposed controller in
providing good damping characteristic to system oscillations
and enhancing the system dynamic stability under different
operating conditions and disturbances.
SENSORLESS VECTOR CONTROL OF BLDC USING EXTENDED KALMAN FILTER sipij
This Paper mainly deals with the implementation of vector control technique using the brushless DC motor
(BLDC). Generally tachogenerators, resolvers or incremental encoders are used to detect the speed. These
sensors require careful mounting and alignment, and special attention is required with electrical noises. A
speed sensor need additional space for mounting and maintenance and hence increases the cost and size of
the drive system. These problems are eliminated by speed sensor less vector control by using Extended
Kalman Filter and Back EMF method for position sensing. By using the EKF method and Back EMFmethod, the sensor less vector control of BLDC is implemented and its simulation using MATLAB/SIMULINK and hardware kit is implemented.
Power system transient stability margin estimation using artificial neural ne...elelijjournal
This paper presents a methodology for estimating the normalized transient stability margin by using the multilayered perceptron (MLP) neural network. The complex relationship between the input variables and output variables is established by using the neural networks. The nonlinear mapping relation between the normalized transient stability margin and the operating conditions of the power system is established by using the MLP neural network. To obtain the training set of the neural network the potential energy boundary surface (PEBS) method along with time domain simulation method is used. The proposed method is applied on IEEE 9 bus system and the results shows that the proposed method provides fast and accurate tool to assess online transient stability.
ESTIMATION OF THE PARAMETERS OF SOLAR CELLS FROM CURRENT-VOLTAGE CHARACTERIST...ijscai
This paper presents a method for calculating the light generated current, the series resistance, shun
resistance and the two components of the reverse saturation current usually encountered in the double
diode representation of the solar cell from the experimental values of the current-voltage characteristics
of the cell using genetic algorithm. The theory is able to regenerate the above mentioned parameters to
very good accuracy when applied to cell data that was generated from pre-defined parameters. The
method is applied to various types of space quality solar cells and sub cells. All parameters except the
light generated current are seen to be nearly the same in the case of a cell whose characteristics under
illumination and in dark were analyzed. The light generated current is nearly equal to the short- circuit
current in all cases. The parameters obtained by this method and another method are nearly equal
wherever applicable. The parameters are also shown to represent the current-voltage characteristics
well.
Estimation Of The Parameters Of Solar Cells From Current-Voltage Characterist...IJSCAI Journal
This paper presents a method for calculating the light generated current, the series resistance, shun
resistance and the two components of the reverse saturation current usually encountered in the double
diode representation of
the solar cell from the experimental values of the current
-
voltage characteristics
of the cell using genetic algorithm. The theory is able to regenerate the above mentioned parameters to
very good accuracy when applied to cell data that was generated from
pre
-
defined parameters. The
method is applied to various types of space quality solar cells and sub cells. All parameters except the
light generated current are seen to be nearly the same in the case of a cell whose characteristics under
illumination and i
n dark were analyzed. The light generated current is nearly equal to the short
-
circuit
current in all cases. The parameters obtained by this method and another method are nearly equal
wherever applicable. The parameters are also shown to represent the cur
rent
-
voltage characteristics
well
ESTIMATION OF THE PARAMETERS OF SOLAR CELLS FROM CURRENT-VOLTAGE CHARACTERIST...ijscai
This paper presents a method for calculating the light generated current, the series resistance, shun
resistance and the two components of the reverse saturation current usually encountered in the double
diode representation of the solar cell from the experimental values of the current-voltage characteristics
of the cell using genetic algorithm. The theory is able to regenerate the above mentioned parameters to
very good accuracy when applied to cell data that was generated from pre-defined parameters. The
method is applied to various types of space quality solar cells and sub cells. All parameters except the
light generated current are seen to be nearly the same in the case of a cell whose characteristics under
illumination and in dark were analyzed. The light generated current is nearly equal to the short- circuit
current in all cases. The parameters obtained by this method and another method are nearly equal
wherever applicable. The parameters are also shown to represent the current-voltage characteristics
well.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Mathematical Modelling of an 3 Phase Induction Motor Using MATLAB/Simulink IJMER
Mechanical energy is needed in the daily life use as well as in the industry. Induction motors
play a very important role in both worlds, because of low cost, reliable operation, robust operation and low
maintenance. To derive the mathematical model of a 3 phase Induction motor, the theory of reference
frames has been effectively used as an efficient approach. Dynamic models (mathematical models) are
employed in to better understand the behaviour of induction motor in both transient and steady state. The
dynamic modelling sets all the mechanical equations for the inertia, torque and speed versus time. It also
models all the differential voltage, currents and flux linkages between the stationary stator as well as the
moving rotor. This paper presents a step by step Matlab/Simulink implementation of an induction machine
using dq0 axis transformations of the stator and rotor variables in the arbitrary reference frame [1].
“INVESTIGATIONS ON LCL-T FILTER BASED TWO STAGE SINGLE PHASE GRID CONNECTED M...Dr.Raja R
Motivation to Research
Objectives of Research
Introduction
Literature Survey
Proposed System
Simulation Model of the Proposed System
Simulation Results and Discussion
Experimental Model of the Proposed System
Experimental Model Results and Discussion
Conclusion
Future Work
References
Optimal Location of FACTS Device for Power System Security Improvement using ...
Ie2514631473
1. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1463 | P a g e
Steady State Analysis of Self-Excited Induction Generator using
THREE Optimization Techniques
SahilGupta*
Student,Microelectronics
Bhai Maha Singh College of Engineering and Technology
ABSTARCT
It is well known that a three-phase
induction machine can be made to work as a self-
excited induction generator. In an isolated
application a three-phase induction generator
operates in the self-excited mode by connecting
three AC capacitors to the stator terminals. In a
grid connected induction generator the magnetic
field is produced by excitation current drawn
from the grid. In this dissertation the steady state
performance of an isolated induction generator
excited by three AC capacitor is analyzed with
the different optimization techniques. The effects
of various system parameters on the steady state
performance have been studied.
Keywords:- Artificial Neural Network, Induction
Generator, Genetic Algorithm
1.1 INTRODUCTION
An induction generator is a type of
electrical generator that is mechanically and
electrically similar to a poly-phase induction motor.
Induction generators produce electrical power when
their shaft is rotated faster than the synchronous
frequency of the equivalent induction motor.
Induction generators are often used in wind turbines
and some micro hydro installations due to their
ability to produce useful power at varying rotor
speeds.
Induction generators are not self-exciting,
meaning they require an external supply to produce
a rotating magnetic flux. The external supply can be
supplied from the electrical grid or from the
generator itself, once it starts producing power. The
rotating magnetic flux from the stator induces
currents in the rotor, which also produces a
magnetic field. If the rotor turns slower than the rate
of the rotating flux, the machine acts like an
induction motor. If the rotor is turned faster, it acts
like a generator, producing power at the
synchronous frequency. In induction generators the
magnetising flux is established by a capacitor bank
connected to the machine in case of stand alone
system and in case of grid connection it draws
magnetising current from the grid. It is mostly
suitable for wind generating stations as in this case
speed is always a variable factor.
A self-excited induction generator systems
are shown in figure 1.1 consists of an induction
machine driven by a prime mover. A three-phase
capacitor bank provides for self-excitation and load
VARs requirements. As the load varies randomly
the capacitor has to be varied to obtain the desire
voltage.
Figure 1.1 Self-excited induction
generator systems
ANALYSIS OF SELF-EXCITED
INDUCTION GENERATOR
In the present dissertation, the standard
steady state equivalent circuit of a self-excited
induction generator with the usual assumptions,
considering the variation of magnetizing reactance
with saturation as the basis for calculation. The
equivalent circuit is nomalised to the base frequency
by dividing all the parameters by the p.u. frequency
as shown in figure 1.2.
For the purpose of obtaining required lagging
reactive power to maintain desired voltage at
machine terminals, XC and F are only unknown
parameters for a given speed and load.
Where
Z
Z
Z
ZS 3
2
1
(2)
F
X
F
R
R
X
Z
C
L
L
C
j
j
2
1
(3)
X
F
R
Z S
S
j
2
(4)
X
X
F
j
R
X
F
j
R
jX
Z
R
M
R
R
R
M
3
(5)
2. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1464 | P a g e
Since under steady state operation of SEIG IS can
not be equal to zero, therefore:
0
ZS
(6)
This equation after separation into real and
imaginary parts, can be rearranged into two
nonlinear equations which are solved using different
optimization techniques to obtain value of XC and F
after substituting XS= XR= XL.
0
5
4
3
2
2
3
1
,
X
A
F
A
X
A
F
A
F
A
F
X
f C
C
C
(7)
0
5
4
3
2
2
1
,
X
B
F
B
X
B
F
B
X
B
F
X
g C
C
C
C
(8)
Where the constants are defined as,
R
X
R
X
X
A L
L
L
M
L
2
1 2
A
A 1
2
R
R
R
X
X
A R
S
L
L
M
3
R
R
R
A R
L
S
4
R
R
X
X
A S
L
L
M
5
X
X
X
B L
M
L
2
1 2
X
X
R
R
R
B M
L
R
S
L
2
B
B 1
3
X
X
R
R
B L
M
L
S
4
R
R
R
B S
L
R
5
Objective function
2
2
2
g
f
Z (9)
The relation between XM and Vg/F are given by:
K
V
K
X
F
g
M
2
1
(10)
Where K1 and K2 are depends on the design of the
machine.
Z
Z
Z
V
V T
g
1
2
1
(11)
Thus for a given value of RL and VT, the
value of Vg can be determined. With the known
values of Vg, F, XC, , RL and the generator’s
equivalent circuit parameters, the following
relations can be used for the computation of the
machine performance.
Z
Z
F
V
I
g
S
2
1
(12)
jX
F
R
F
V
I
R
R
g
R
(13)
jX
F
R
I
jX
I
C
L
S
C
L
(14)
R
I
V L
L
T
(15)
X
F
V
VAR C
T
2
(16)
F
F
R
I
P
R
R
in
2
(17)
R
I
P L
L
out
2
(18)
To obtain the performance of self-excited
induction generator for the given value of
capacitance and speed, the unknown parameters are
the XM and F. The two non-linear equations after
substitution XS= XR= XL is given by:
0
8
7
6
5
2
4
3
3
2
1
,
C
X
C
F
C
X
C
F
C
X
C
F
C
X
C
F
X
f
M
M
M
M
M
(19)
0
5
4
3
2
2
1
,
D
F
D
D
D
F
D
X
D
F
X
g M
M
M
(20)
Where
R
X
C L
L
2
1
R
X
C L
L
2
2
C
C 1
3
C
C 2
4
R
R
R
X
C R
S
L
C
5
R
R
R
R
R
R
X
X
C R
L
S
R
L
S
L
C
6
R
R
X
C L
S
C
7
R
R
X
X
C L
S
C
L
8
R
R
R
X
X
D R
S
L
C
L
2
1
3. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1465 | P a g e
X
X
R
R
X
R
D C
L
R
S
L
L
2
2
X
X
R
R
D L
C
L
S 2
3
X
X
R
R
X
D L
C
L
S
L
2
4
R
R
R
X
D S
L
R
C
5
Objective function
2
2
2
g
f
Z
(21)
By Finding these unknown parameters
using different optimization techniques and after
that performance of SEIG has been evaluated.
3.0 DIFFERENTOPTIMIZATION
TECHNIQUES FOR STEADY STATE
ANALYSIS OF SEIG GENETIC ALGORITHM
The genetic algorithm is a method for
solving optimization problems that is based on
natural selection, the process that drives biological
evolution. The genetic algorithm repeatedly
modifies a population of individual solutions. At
each step, the genetic algorithm selects individuals
at random from the current population to be parents
and uses them produce the children for the next
generation. Over successive generations, the
population evolves toward an optimal solution. The
GA has several advantages over other optimization
methods. It is robust, able to find global minimum
and does not require accurate initial estimates.
The genetic algorithm uses three main types of rules
at each step to create the next generation from the
current population:
Selection rules select the individuals, called parents
that contribute to the population at the next
generation.
Crossover rules combine two parents to form
children for the next generation.
Mutation rules apply random changes to individual
parents to form children.
3.2 PATTERN SEARCH
Pattern search is a subclass of direct search
algorithms, which involve the direct comparison of
objective function values and do not require the use
of explicit or approximate derivatives. Direct search
is a method for solving optimization problems that
does not require any information about the gradient
of the objective function. As opposed to more
traditional optimization methods that use
information about the gradient or higher derivative
to search for an optimal point, a direct search
algorithm searches a set of points around the current
point, looking for one where the value of the
objective function is lower than the value at the
current point. Direct search can be used to solve
problems for which the objective function is not
differential, or even continuous.
Pattern search over continuous variables is
defined via a finite set of directions used at each
search iteration. The direction set and a step length
parameter define a conceptual mesh centered about
the current iterate. Trial points are selected from the
mesh, evaluated, and compared to the current
iteration in order to select the next iterate. If an
improvement is found among the trial points, the
iteration is declared successful and the mesh is
retained; otherwise, the mesh is refined and a new
set of trial points is constructed. The key to
generating the mesh is the definition of the direction
set. This set must be sufficiently rich to ensure that
at least one of the directions is one of descent.
3.3 QUASI-NEWTON
Quasi-Newton methods, which are
currently the most robust and effective algorithms
for unconstrained optimization, are based on the
following set of ideas.
If Bk (definite matrix) is positive definite, the
direction –Bk-1 ∇f (xk) is always a descent direction
at xk, and we can perhaps get global convergence
(i.e. convergence starting anywhere) by searching in
those directions.
As long as Bk approximates the second
derivative matrix at least asymptotically, the method
is likely to work well locally (i.e. fast convergence).
For a quadratic function, a set of conjugate
directions, when searched sequentially, gives the
optimum solution in at most n iterations.
In terms of numerical computations for the inverse
of a matrix, the following formula is used for a low
rank update to a matrix
[A + uvT]-1 = A-1+(1/1+k) A-1 uvT A-1,
where k = vTA-1u Note that if A-1 is known, this is
much faster than computing [A + uvT]-1 directly.
This is a rank one update (uvT is a rank one matrix)
of the original matrix A. In particular, A + uuT is a
symmetric rank one update.
If Bk is updated by a small rank correction
to get Bk+1 then Bk+1-1 can be computed easily by
the above argument.
Quasi-Newton methods put all these ideas
together to construct approximations Bk to the
Hessian matrix at each stage. Note that some
updates work on Bk and update Bk and then find its
inverse, whereas some work directly on the inverse
of the second derivative approximation (Hk).
3.31 General Quasi-Newton Algorithm for
Minimizing a Function f
Start with x0 and H0 = I (approximation to the
inverse of the Hessian)
At step k,
dk = -Hk ∇f(xk)
4. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1466 | P a g e
Find αk so as to (exactly or approximately)
minimize f(xk + αk dk)
xk+1 = xk + αk dk
Update Hk+1
Continue until a termination condition is satisfied.
EFFECTS OF VARIOUS SYSTEM
PARAMETERS BY PATTERN SEARCH
The performance characteristics of capacitor
excited, 3.7 KW, cage generator (detailed data given
in Appendix A) has been verified [4], [7] using
pattern search.
4.1Effects of Terminal Voltage on VAR
Requirements
The computed results for the given machine are
presented in figures 4.1 - 4.8. From these results, the
following salient features are observed.
Figure 4.1 shows the variations of frequency,
efficiency and stator current with output power at
constant terminal voltage and rated speed.
Figure 4.1
At constant terminal voltage the frequency
variation is negligible. The efficiency is good
throughout the power range and the stator current
increases with output power.
Figure 4.2 shows the variations of reactive power in
terms of reactive VAR and capacitance in terms of
susceptance with output power for various constant
terminal voltages and rated speed.
Figure 4.2
For constant terminal voltage, the
susceptance and VARs increases with output power.
With increase or decrease in the terminal voltage,
the VARs requirements increase or decrease
accordingly.
Figure 4.3 shows the variations of stator
and rotor currents with output power for various
constant terminal voltages and rated speed.
The magnitude of the rotor current is always less
than the stator current. This is because the rotor
current is approximately in quadrature with the
magnetizing current in both the motoring and
generating modes.
Figure 4.3
Figure 4.4 shows the variations of Cmin and
frequency with load resistance at constant terminal
voltage and rated speed.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.4
0.5
0.6
0.7
0.8
0.9
1
Performancecharacteristics at Constant Terminal Voltage
Stator
Current,
Efficiency,
Frequency
(p.u.)
Output power(p.u.)
StatorCurrent
Efficiency
Frequency
VT= 1p.u.
0 0.2 0.4 0.6 0.8 1
0
0.5
1
1.5
Variation of Reactive VAR and Susceptance for different Terminal Voltages at rated Speed
Reactive
VAR
and
Susceptance
(p.u.)
Output power (p.u.)
VARS
Susceptance
VT= 1.2 p.u.
VT= 1 p.u.
VT= 0.8 p.u.
0 0.2 0.4 0.6 0.8 1
0
0.5
1
1.5
Variation of Stator and Rotor Current with Output Power
Stator
and
Rotor
Currents
(p.u.)
Output power (p.u.)
Stator Current
Rotor Current
VT= 0.8 p.u.
VT= 1 p.u.
VT= 1.2 p.u.
5. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1467 | P a g e
Figure 4.4
As shown in figure the exciting capacitance
decreases as load resistance increases, whereas the
frequency increases.
Figure 4.5 and 4.6 shows the variations of
VARs with output power for different values of
stator and rotor resistance at constant terminal
voltage and rated speed.
Figure 4.5
Figure 4.6
It is seen from figures that a marginal reduction in
VAR requirement when stator and rotor resistance
are decrease.
Figure 4.7 shows the variation of VAR with output
power for different value of leakage reactance at
constant terminal voltage and rated sp
Figure 4.7
From figure the effect of leakage reactance on VAR
requirement at lower and higher loads are reverse,
the crossover taking place around the full load.
Figure 4.8 shows the variations of VAR with output
power for different values of K1 at constant voltage
and rated speed.
As shown in figure a small reduction in K1 there is
significant increase in VAR requirements.
Figure 4.8
4.1.1Effects of Capacitance on Terminal Voltage
The computed results for the given machine are
presented in figures 4.9 - 4.16. From these results,
the following salient features are observed.
0 2 4 6 8 10 12 14 16 18 20
16
18
20
22
24
26
Variation of Cmin and Frequency with RL, at v = VT = 1 (p.u.)
Minimum
Capacitance
(micro
farad)
0 2 4 6 8 10 12 14 16 18 20
0.95
0.96
0.97
0.98
0.99
1
Frequency
(p.u.)
Load Resistance (p.u.)
Frequency (p.u.)
Minimum Capacitance (micro farad)
VT = 1 p.u.
Speed = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.45
0.5
0.55
0.6
0.65
0.7
0.75
Effect ofStator Resistance on VAR requirement
Reactive
VAR
(p.u.)
Output power (p.u.)
Rs* 0.8
Rs* 1
Rs* 1.2
VT= 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.45
0.5
0.55
0.6
0.65
0.7
Effect ofRotor Resistance on VAR requirement
Reactive
VAR
(p.u.)
Output power (p.u.)
Rr* 0.8
Rr* 1
Rr* 1.2
VT= 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.45
0.5
0.55
0.6
0.65
0.7
Effect of leakage Reactance on VAR requirement
Reactive
VAR
(p.u.)
Output power (p.u.)
XL* 0.8
XL* 1
XL* 1.2
VT = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Effect ofMagnetising Reactance on VARrequirement
Reactive
VAR
(p.u.)
Output power (p.u.)
k1* 0.8
k1* 1
k1* 1.2
VT= 1 p.u.
6. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1468 | P a g e
Figure 4.9 shows the variation of terminal voltage,
frequency and efficiency with output power at fixed
capacitance and constant speed.
Figure 4.9
It can be noted that the terminal voltage
and frequency decreases with output power, and
generator efficiency improves with load.
Figure 4.10 shows the variation of terminal voltage
and frequency with output power for different
values of capacitance and constant speed.
It can be seen that the terminal voltage are almost
parallel, indicating the proportional increase of VT
with capacitance. The frequency drop with output
power was not very much affected by the
capacitance.
Figure 4.10
Figure 4.11 and 4.12 shows the variations
of terminal voltage with output power for different
values of stator and rotor resistance at fixed
capacitance and constant speed.
Figure 4.11
Figure 4.12
From figure it can be shown that at
increased value of stator and rotor resistance causes
more drooping the characteristics and decrease the
maximum output power.
Figure 4.13 shows the variation of terminal
voltage with output power for different values of
leakage reactance at fixed capacitance and constant
speed.
Figure 4.13
From figure it can be seen that for a given
value of capacitance and speed there is one value of
output power for which VT is independent of
leakage reactance. While lower value of
leaka
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
Performance Characteristics at given Capacitance and Speed
Terminal
Voltage,
Efficiency,
Frequency
(p.u.)
Output power(p.u.)
Terminal Voltage
Frequency
Efficiency
C= 25 micro farad
Speed = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0.2
0.4
0.6
0.8
1
1.2
1.4
Variation of Terminal Voltage and Frequency with Output Power at different C
Terminal
voltage
and
Frequency
(p.u.)
Output power (p.u.)
Terminal Voltage
Frequency
C = 30 mf
C = 25 mf
C = 20 mf
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
Effect of Stator Resistance on Terminal voltage
Terminal
Voltage
(p.u.)
Output power (p.u.)
Rs* 0.8
Rs* 1
Rs* 1.2
C = 25 micro farad
Speed = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
Effect of Leakage Reactance on Terminal Voltage
Terminal
Voltage
(p.u.)
Output power (p.u.)
XL* 0.8
XL* 1
XL* 1.2
C = 25 micro farad
Speed = 1 p.u.
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0.4
0.6
0.8
1
1.2
1.4
1.6
Effect of Magnetising Reactance on Terminal Voltage
Terminal
Voltage
(p.u.)
Output power (p.u.)
k1* 0.8
k1* 1
k1* 1.2
C = 25 micro farad
Speed = 1 p.u.
7. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
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1469 | P a g e
ge reactance the terminal voltage improves.
Figure 4.14 shows the variation of terminal voltage
with output power for different values of K1 at fixed
value of capacitance and constant speed.
Figure 4.14
From figure it can be seen that at increase value of
K1 causes increased terminal voltage and maximum
output
power. These changes are quite significant.
Figure 4.15 and 4.16 shows the variation of terminal
voltage and frequency with output power for
different values of speed at fixed capacitance.
Figure 4.15
Figure 4.16
From figure it can be seen that the terminal voltage
and frequency for the same output power increases
with speed. It is shown that both VT and frequency
are almost the same at all speed.
Effects of Various System Parameters by Genetic
Algorithm
The performance characteristics of capacitor
excited, 3.7 KW, cage generator (detailed data given
in Appendix A) has been verified [4], [7] using
genetic algorithm.
Effects of Terminal Voltage on VAR Requirements
The computed results for the given machine are
presented in figures 4.17 - 4.24.
Figure 4.17 shows the variations of frequency,
efficiency and stator current with output power at
constant terminal voltage and rated speed.
Figure 4.17
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
Effect ofRotorResistanceonTerminal Voltage
Terminal
Voltage
(p.u.)
Output power(p.u.)
Rr* 0.8
Rr* 1
Rr* 1.2
C= 25microfarad
Speed= 1p.u.
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
0.6
0.7
0.8
0.9
1
1.1
1.2
Effect ofSpeed on Frequency
Frequency
(p.u.)
Output power (p.u.)
v* 0.8
v* 1
v* 1.2
C= 25 micro farad
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Effect ofSpeed on Terminal Voltage
Terminal
voltage
(p.u.)
Output power (p.u.)
v* 0.8
v* 1
v* 1.2
C = 25 micro farad
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.4
0.5
0.6
0.7
0.8
0.9
1
Performance characteristics at Constant Terminal Voltage
Stator
Current,
Efficiency
and
Frequency
(p.u.)
Output power (p.u.)
Stator Current
Efficiency
Frequency
VT = 1 p.u.
8. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
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1470 | P a g e
Figure 4.19 shows the variations of stator and rotor
currents with output power for various constant
terminal voltages and rated speed.
Figure 4.19
Figure 4.20 shows the variations of Cmin and
frequency with load resistance at constant terminal
voltage and rated speed.
Figure 4.20
Figure 4.21 and 4.22 shows the variations of VARs
with output power for different values of stator and
rotor resistance at constant voltage and rated speed.
Figure 4.21
Figure 4.22
Figure 4.23 shows the variation of VAR with output
power for different values of leakage reactance at
constant terminal voltage and rated speed.
Figure 4.23
0 0.2 0.4 0.6 0.8 1
0
0.5
1
1.5
VariationofStatorandRotorCurrent withOutput Power
Stator
and
Rotor
Currents
(p.u.)
Output power(p.u.)
StatorCurrent
RotorCurrent
VT= 0.8p.u.
VT= 1p.u.
VT= 1.2p.u.
0 2 4 6 8 10 12 14 16 18 20
16
18
20
22
24
26
Variation ofCmin and Frequency with RL, at v= VT= 1 (p.u.)
Minimum
Capacitance
(micro
farad)
0 2 4 6 8 10 12 14 16 18 20
0.95
0.96
0.97
0.98
0.99
1
Frequency
(p.u.)
Load Resistance (p.u.)
Frequency (p.u.)
Minimum Capacitance (micro farad)
VT= 1 p.u.
Speed = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.45
0.5
0.55
0.6
0.65
0.7
0.75
Effect of Stator Resistance on VAR requirement
Reactive
VAR
(p.u.)
Output power (p.u.)
Rs* 0.8
Rs* 1
Rs* 1.2
VT = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.45
0.5
0.55
0.6
0.65
0.7
0.75
Effect of Rotor Resistance on VAR requirement
Reactive
VAR
(p.u.)
Output power (p.u.)
Rr* 0.8
Rr* 1
Rr* 1.2
VT = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.45
0.5
0.55
0.6
0.65
0.7
Effect of leakage Reactance on VAR requirement
Reactive
VAR
(p.u.)
Output power (p.u.)
XL* 0.8
XL* 1
XL* 1.2
VT= 1 p.u.
9. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1471 | P a g e
Figure 4.24 shows the variations of VAR with
output power for different values of K1 at constant
terminal voltage and rated speed.
Figure 4.24
Observations
There are close relation between the two results. The
genetic algorithm optimization technique gives
almost same results which we getting from the
pattern search optimization technique.
4.2.2 Effects of Capacitance on
Terminal Voltage
The computed results for the given machine are
presented in figures 4.25 - 4.32.
In this case also the values which are obtained from
genetic algorithm optimization technique are much
closed with the values of the pattern search
optimization technique the figures are shown below.
Figure 4.25 shows the variation of terminal voltage,
frequency and efficiency with output power at fixed
capacitance and constant speed.
Figure 4.25
Figure 4.26 shows the variation of terminal voltage
and frequency with output power for different
values of capacitance and constant speed.
Figure 4.26
Figure 4.27 and 4.28 shows the variations of
terminal voltage with output power for different
values of stator and rotor resistance at fixed
capacitance and constant speed.
Figure 4.27
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Effect of Magnetising Reactance on VAR requirement
Reactive
VAR
(p.u.)
Output power (p.u.)
k1* 0.8
k1* 1
k1* 1.2
VT= 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
Performance Characteristics at given Capacitance and Speed
Terminal
Voltage,
Efficiency
and
Frequency
(p.u.)
Output power (p.u.)
Terminal Voltage
Frequency
Efficiency
C = 25 micro farad
Speed = 1 p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0.2
0.4
0.6
0.8
1
1.2
1.4
Variation of Terminal Voltage and Frequency with Output Power at different C
Terminal
voltage
and
Frequency
(p.u.)
Output power (p.u.)
Terminal Voltage
Frequency
C = 30 mf
C = 25 mf
C = 20 mf
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
Effect ofStatorResistanceonTerminal voltage
Terminal
Voltage
(p.u.)
Output power(p.u.)
Rs* 0.8
Rs* 1
Rs* 1.2
C= 25microfarad
Speed= 1p.u.
10. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
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1472 | P a g e
Figure 4.28
Figure 4.29 shows the variation of terminal voltage
with output power for different values of leakage
reactance at fixed capacitance and constant speed.
Figure 4.29
Figure 4.30 shows the variation of terminal voltage
with output power for different values of K1 at fixed
value of capacitance and constant speed.
Figure 4.30
REFERENCES
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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
Effect ofRotorResistanceonTerminalVoltage
Terminal
Voltage
(p.u.)
Output power(p.u.)
Rr*0.8
Rr*1
Rr*1.2
C= 25microfarad
Speed= 1p.u.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
EffectofLeakageReactanceonTerminalVoltage
Terminal
Voltage
(p.u.)
Outputpower(p.u.)
XL*0.8
XL*1
XL*1.2
C=25microfarad
Speed=1p.u.
0 0.2 0.4 0.6 0.8 1 1.2 1.4
0.4
0.6
0.8
1
1.2
1.4
1.6
Effect ofMagnetisingReactanceonTerminalVoltage
Terminal
Voltage
(p.u.)
Output power(p.u.)
k1*0.8
k1*1
k1*1.2
C= 25microfarad
Speed= 1p.u.
11. SahilGupta / International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 www.ijera.com Vol. 2, Issue 5, September- October 2012, pp.1463-1473
1473 | P a g e
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