This document summarizes a research paper that proposes using particle swarm optimization (PSO) to design multi-machine power system stabilizers (PSS). The paper formulates a multi-objective optimization problem to simultaneously shift the lightly damped electro-mechanical modes of all machines to improve stability. PSO is applied to optimize the PSS parameters (gain and time constants) to minimize objectives related to damping factors and ratios. Simulation results on a three-machine system show the PSO-designed PSS provide effective damping over different loading conditions.
AN EFFICIENT ALGORITHM FOR WRAPPER AND TAM CO-OPTIMIZATION TO REDUCE TEST APP...IAEME Publication
System-on-Chip (SOC) designs composed of many embedded cores are ubiquitous in today’s integrated circuits. Each of these cores requires to be tested separately after manufacturing of the SoC. That’s why, modular testing is adopted for core-based SoCs, as it promotes test reuse and permits the cores to be tested without comprehensive knowledge about their internal structural details. Such modular testing triggers the need of a special test access mechanism (TAM) to build communication between core I/Os and TAM and promises to minimize overall test time. In this paper, various issues are analyzed to optimize the Wrapper and TAM, which comprises the optimal partitioning of TAM width, assignment of cores to partitioned TAM width etc.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Alienor method applied to induction machine parameters identification IJECEIAES
This paper presents an identification method to estimate simultaneously the electrical and mechanical induction machine (IM) parameters by using only the measured current and the corresponding phase voltage. This identification method is based on the output error and uses the multidimensional Alienor global optimization method as a minimization technique. Alienor method is essentially based on converting multivariable problem to monovariable one. To improve the Alienor method performance, the reducing transformation is proposed and compared with the genetic algorithm (GA). Firstly, the identification method is verified using the simulated data. Secondly, the validation is then confirmed by measured data from one machine. The corresponding computed transient and steady state currents agree well with the measured data. The results obtained show the superiority of the proposed Alienor method versus GA in terms of computing time.
Comparison of cascade P-PI controller tuning methods for PMDC motor based on ...IJECEIAES
In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.
Neuro-Genetic Adaptive Optimal Controller for DC MotorIAES-IJPEDS
Conventional speed controllers of DC motors suffer from being not adaptive; this is because of the nonlinearity in the motor model due to saturation. Structure of DC motor speed controller should vary according to its operating conditions, so that the transient performance is acceptable. In this paper an adaptive and optimal Neuro-Genetic controller is used to control a DC motor speed. GA will be used first to obtain the optimal controller parameter for each load torque and motor reference speed. The data obtained from GA is used to train a neural network; the inputs for the neural network are the load torque and the motor reference speed and the outputs are the controller parameters. This neural network is used on line to adapt the controller parameters according to operating conditions. This controller is tested with a sudden change in the operating conditions and could adapt itself for the conditions and gave an optimal transient performance.
Tuning of different controlling techniques for magnetic suspending system usi...IJECEIAES
In this paper, design of proportional- derivative (PD) controller, pseudo-derivative-feedback (PDF) controller and PDF with feedforward (PDFF) controller for magnetic suspending system have been presented. Tuning of the above controllers is achieved based on Bat algorithm (BA). BA is a recent bio-inspired optimization method for solving global optimization problems, which mimic the behavior of micro-Bats. The weak point of the standard BA is the exploration ability due to directional echolocation and the difficulty in escaping from local optimum. The new improved BA enhances the convergence rate while obtaining optimal solution by introducing three adaptations namely modified frequency factor, adding inertia weight and modified local search. The feasibility of the proposed algorithm is examined by applied to several benchmark problems that are adopted from literature. The results of IBA are compared with the results collected from standard BA and the well-known particle swarm optimization (PSO) algorithm. The simulation results show that the IBA has a higher accuracy and searching speed than the approaches considered. Finally, the tuning of the three controlling schemes using the proposed algorithm, standard BA and PSO algorithms reveals that IBA has a higher performance compared with the other optimization algorithms.
MAXIMUM POWER POINT TRACKING WITH ARTIFICIAL NEURAL NET WORKIAEME Publication
Fossil fuels’ rapid depletion and need to protect the environment has left us to think upon alternatives and solutions to curb the excess use of conventional sources and shift focus on the renewable energy. In this paper we have designed a prototype model inclusive of techniques that support the need to harness the solar energy.
AN EFFICIENT ALGORITHM FOR WRAPPER AND TAM CO-OPTIMIZATION TO REDUCE TEST APP...IAEME Publication
System-on-Chip (SOC) designs composed of many embedded cores are ubiquitous in today’s integrated circuits. Each of these cores requires to be tested separately after manufacturing of the SoC. That’s why, modular testing is adopted for core-based SoCs, as it promotes test reuse and permits the cores to be tested without comprehensive knowledge about their internal structural details. Such modular testing triggers the need of a special test access mechanism (TAM) to build communication between core I/Os and TAM and promises to minimize overall test time. In this paper, various issues are analyzed to optimize the Wrapper and TAM, which comprises the optimal partitioning of TAM width, assignment of cores to partitioned TAM width etc.
Impact analysis of actuator torque degradation on the IRB 120 robot performan...IJECEIAES
Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Alienor method applied to induction machine parameters identification IJECEIAES
This paper presents an identification method to estimate simultaneously the electrical and mechanical induction machine (IM) parameters by using only the measured current and the corresponding phase voltage. This identification method is based on the output error and uses the multidimensional Alienor global optimization method as a minimization technique. Alienor method is essentially based on converting multivariable problem to monovariable one. To improve the Alienor method performance, the reducing transformation is proposed and compared with the genetic algorithm (GA). Firstly, the identification method is verified using the simulated data. Secondly, the validation is then confirmed by measured data from one machine. The corresponding computed transient and steady state currents agree well with the measured data. The results obtained show the superiority of the proposed Alienor method versus GA in terms of computing time.
Comparison of cascade P-PI controller tuning methods for PMDC motor based on ...IJECEIAES
In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.
Neuro-Genetic Adaptive Optimal Controller for DC MotorIAES-IJPEDS
Conventional speed controllers of DC motors suffer from being not adaptive; this is because of the nonlinearity in the motor model due to saturation. Structure of DC motor speed controller should vary according to its operating conditions, so that the transient performance is acceptable. In this paper an adaptive and optimal Neuro-Genetic controller is used to control a DC motor speed. GA will be used first to obtain the optimal controller parameter for each load torque and motor reference speed. The data obtained from GA is used to train a neural network; the inputs for the neural network are the load torque and the motor reference speed and the outputs are the controller parameters. This neural network is used on line to adapt the controller parameters according to operating conditions. This controller is tested with a sudden change in the operating conditions and could adapt itself for the conditions and gave an optimal transient performance.
Tuning of different controlling techniques for magnetic suspending system usi...IJECEIAES
In this paper, design of proportional- derivative (PD) controller, pseudo-derivative-feedback (PDF) controller and PDF with feedforward (PDFF) controller for magnetic suspending system have been presented. Tuning of the above controllers is achieved based on Bat algorithm (BA). BA is a recent bio-inspired optimization method for solving global optimization problems, which mimic the behavior of micro-Bats. The weak point of the standard BA is the exploration ability due to directional echolocation and the difficulty in escaping from local optimum. The new improved BA enhances the convergence rate while obtaining optimal solution by introducing three adaptations namely modified frequency factor, adding inertia weight and modified local search. The feasibility of the proposed algorithm is examined by applied to several benchmark problems that are adopted from literature. The results of IBA are compared with the results collected from standard BA and the well-known particle swarm optimization (PSO) algorithm. The simulation results show that the IBA has a higher accuracy and searching speed than the approaches considered. Finally, the tuning of the three controlling schemes using the proposed algorithm, standard BA and PSO algorithms reveals that IBA has a higher performance compared with the other optimization algorithms.
MAXIMUM POWER POINT TRACKING WITH ARTIFICIAL NEURAL NET WORKIAEME Publication
Fossil fuels’ rapid depletion and need to protect the environment has left us to think upon alternatives and solutions to curb the excess use of conventional sources and shift focus on the renewable energy. In this paper we have designed a prototype model inclusive of techniques that support the need to harness the solar energy.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Effects of Different Parameters on Power System Transient Stability StudiesPower System Operation
The transient stability studies plays a vital role in
providing secured operating configurations in power systems.
This paper shows an analysis of the effects of various parameters
on the transient stability studies of power system. The various
parameters for which the analysis is presented include the Fault
Clearing Time (FCT), Fault location, load increasing, machine
damping coefficient D, and Generator Armature Resistance
GAR. Under the condition that the power system is subjected to a
three-phase short-circuit fault, the Critical Clearing Time (CCT)
is calculated using numerical integration method. The analysis
has been carried out on the IEEE 30-bus test system. From this
analysis, we can conclude the importance of these different
parameters on power system transient stability studies.
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Comparison between neural network and P&O method in optimizing MPPT control f...IJECEIAES
The demand for renewable energy has increased because it is considered a clean energy and does not result in any pollution or emission of toxic gases that negatively affect the environment and human health also requiring little maintenance, and emitting no noise, so it is necessary to develop this type of energy and increase its production capacity. In this research a design of maximum power point tracking (MPPT) control method using Neural Network (NN) for photovoltaic system is presented. First we design a standalone PV system linked to dc boost chopper with MPPT by perturbation and observation P&O technique, and then a design of MPPT by using ANN for the same system is presented. Comparative between two control methods are studied. The results explained in constant and adjustable weather settings such as irradiation and temperature. The results exposed that the proposed MPPT by ANN control can improve the PV array efficiency by reduce the oscillation around the MPP that accure in P&O method and so decreases the power losses. As well as decrease the the overshot that accure in transient response, and hence improving the performance of the solar cell.
Adaptive Fuzzy Logic Control of Wind Turbine EmulatorIJPEDS-IAES
In this paper, a Wind Turbine Emulator (WTE) based on a separately excited direct current (DC) motor is studied. The wind turbine was emulated by controlling the torque of the DC motor. The WTE is used as a prime mover for Permanent Magnet Synchronous Machine (PMSM). In order to extract maximum power from the wind, PI and Fuzzy controllers were tested. Simulation results are given to show performance of proposed fuzzy control system in maximum power points tracking in a wind energy conversion system under various wind conditions. The strategy control was implemented in simulation using MATLAB/Simulink.
Necessary of Compensation, Methods of Compensation, Phase Lead Compensation, Phase Lag Compensation, Phase Lag Lead Compensation, and Comparison between lead and lag compensators.
The present work deals to investigate the performance of linear switched reluctance motor designed for a sliding door application. The objective of this paper is to develop an analytical model in order to predict the dynamic behaviour of the studied motor. Firstly, the characteristics of the proposed motor in open loop operation was computed.Secondly, the effect of the load on the response of the motor was investigated. In this context, a two technoque in open loop were adopted to solve the error positioning with load and to damp the oscillation observed in the characteristics of the motor in order to obtain a smooth motion.
Experimental dataset to develop a parametric model based of DC geared motor i...IJECEIAES
This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC Geared motor in feeder machine. The experimental was conducted to measure the input (voltage) and output (speed) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is Time, Man Square Error (MSE) and Average Time. One of the best model has been chosen based on the optimum parameters.
Modeling and Simulation of VSI Fed Induction Motor Drive in Matlab/Simulink IJECEIAES
The theory of reference frames and switching functions are effective in analyzing the performance of the induction motor fed from VSI (Voltage Source Inverter). In this work, mathematical model of Adjustable Speed Drive (ASD) is developed by taking synchronous reference frame equations for induction motor, switching function concept for VSI and non-switching concept for diode bridge rectifier. Simulation model of induction machine is implemented using dq0 axis transformations of the stator and rotor variables in the arbitrary reference frame. The corresponding equations are given in the beginning and then the developed model is implemented using MATLAB/Simulink. In this work, the proposed model is implemented using basic function blocks. The performance of induction motor is analysed for different frequencies. The developed model is tested for the steady state behavior of machine drive. The proposed mathematical model is validated by the simulation results.
Control of Wind Energy Conversion System and Power Quality Improvement in the...ijeei-iaes
For the purpose of better utilization and to have control over varying wind speeds we use variable speed wind turbines. The performance mainly depends on the system operating point. In this paper we implement extremum seeking (ES) which is a non-model based approach for maximum power extraction in the region between cut-in speed and rated speed. The convergence of the system depends mainly on the system dynamics so we go for non-linear control based on field oriented approach and also feedback linearization. For achieving maximum power at all wind speeds the outer loop of ES is used to tune the turbine speed in the sub rated region. By adjusting the voltage magnitude and electrical frequency through matrix converter we can achieve a fast transient response. The transient response can be improved by providing inner loop control based on field oriented control. Through this we can avoid magnetic saturation in the induction generator
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Effects of Different Parameters on Power System Transient Stability StudiesPower System Operation
The transient stability studies plays a vital role in
providing secured operating configurations in power systems.
This paper shows an analysis of the effects of various parameters
on the transient stability studies of power system. The various
parameters for which the analysis is presented include the Fault
Clearing Time (FCT), Fault location, load increasing, machine
damping coefficient D, and Generator Armature Resistance
GAR. Under the condition that the power system is subjected to a
three-phase short-circuit fault, the Critical Clearing Time (CCT)
is calculated using numerical integration method. The analysis
has been carried out on the IEEE 30-bus test system. From this
analysis, we can conclude the importance of these different
parameters on power system transient stability studies.
Improving efficiency of Photovoltaic System with Neural Network Based MPPT Co...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Comparison between neural network and P&O method in optimizing MPPT control f...IJECEIAES
The demand for renewable energy has increased because it is considered a clean energy and does not result in any pollution or emission of toxic gases that negatively affect the environment and human health also requiring little maintenance, and emitting no noise, so it is necessary to develop this type of energy and increase its production capacity. In this research a design of maximum power point tracking (MPPT) control method using Neural Network (NN) for photovoltaic system is presented. First we design a standalone PV system linked to dc boost chopper with MPPT by perturbation and observation P&O technique, and then a design of MPPT by using ANN for the same system is presented. Comparative between two control methods are studied. The results explained in constant and adjustable weather settings such as irradiation and temperature. The results exposed that the proposed MPPT by ANN control can improve the PV array efficiency by reduce the oscillation around the MPP that accure in P&O method and so decreases the power losses. As well as decrease the the overshot that accure in transient response, and hence improving the performance of the solar cell.
Adaptive Fuzzy Logic Control of Wind Turbine EmulatorIJPEDS-IAES
In this paper, a Wind Turbine Emulator (WTE) based on a separately excited direct current (DC) motor is studied. The wind turbine was emulated by controlling the torque of the DC motor. The WTE is used as a prime mover for Permanent Magnet Synchronous Machine (PMSM). In order to extract maximum power from the wind, PI and Fuzzy controllers were tested. Simulation results are given to show performance of proposed fuzzy control system in maximum power points tracking in a wind energy conversion system under various wind conditions. The strategy control was implemented in simulation using MATLAB/Simulink.
Necessary of Compensation, Methods of Compensation, Phase Lead Compensation, Phase Lag Compensation, Phase Lag Lead Compensation, and Comparison between lead and lag compensators.
The present work deals to investigate the performance of linear switched reluctance motor designed for a sliding door application. The objective of this paper is to develop an analytical model in order to predict the dynamic behaviour of the studied motor. Firstly, the characteristics of the proposed motor in open loop operation was computed.Secondly, the effect of the load on the response of the motor was investigated. In this context, a two technoque in open loop were adopted to solve the error positioning with load and to damp the oscillation observed in the characteristics of the motor in order to obtain a smooth motion.
Experimental dataset to develop a parametric model based of DC geared motor i...IJECEIAES
This paper presents the application of a System Identification based on Particle Swarm Optimization (PSO) technique to develop parametric model of experimental dataset of DC Geared motor in feeder machine. The experimental was conducted to measure the input (voltage) and output (speed) data. The actual data is used to be optimized using PSO algorithm. The parameter emphasized is Time, Man Square Error (MSE) and Average Time. One of the best model has been chosen based on the optimum parameters.
Modeling and Simulation of VSI Fed Induction Motor Drive in Matlab/Simulink IJECEIAES
The theory of reference frames and switching functions are effective in analyzing the performance of the induction motor fed from VSI (Voltage Source Inverter). In this work, mathematical model of Adjustable Speed Drive (ASD) is developed by taking synchronous reference frame equations for induction motor, switching function concept for VSI and non-switching concept for diode bridge rectifier. Simulation model of induction machine is implemented using dq0 axis transformations of the stator and rotor variables in the arbitrary reference frame. The corresponding equations are given in the beginning and then the developed model is implemented using MATLAB/Simulink. In this work, the proposed model is implemented using basic function blocks. The performance of induction motor is analysed for different frequencies. The developed model is tested for the steady state behavior of machine drive. The proposed mathematical model is validated by the simulation results.
Control of Wind Energy Conversion System and Power Quality Improvement in the...ijeei-iaes
For the purpose of better utilization and to have control over varying wind speeds we use variable speed wind turbines. The performance mainly depends on the system operating point. In this paper we implement extremum seeking (ES) which is a non-model based approach for maximum power extraction in the region between cut-in speed and rated speed. The convergence of the system depends mainly on the system dynamics so we go for non-linear control based on field oriented approach and also feedback linearization. For achieving maximum power at all wind speeds the outer loop of ES is used to tune the turbine speed in the sub rated region. By adjusting the voltage magnitude and electrical frequency through matrix converter we can achieve a fast transient response. The transient response can be improved by providing inner loop control based on field oriented control. Through this we can avoid magnetic saturation in the induction generator
A brief introduction on the principles of particle swarm optimizaton by Rajorshi Mukherjee. This presentation has been compiled from various sources (not my own work) and proper references have been made in the bibliography section for further reading. This presentation was made as a presentation for submission for our college subject Soft Computing.
Design of power system stabilizer for damping power system oscillationsIOSRJEEE
The problem of the poorly damped low-frequency (electro-mechanical) oscillations of power systems has been a matter of concern to power engineers for a long time, because they limit power transfers in transmission lines and induce stress in the mechanical shaft of machines. Due to small disturbances, power systems experience these poorly damped low-frequency oscillations. The dynamic stability of power systems are also affected by these low frequency oscillations. With proper design of Power System Stabilizer (PSS), these oscillations can be well damped and hence the system stability is enhanced. The basic functions of the PSS is to add a stabilizing signal that compensates the oscillations of the voltage error of the excitation system during the dynamic/transient state, and to provide a damping component when it’s on phase with rotor speed deviation of machine. Studies have shown that PSS are designed to provide additional damping torque, for different operation point normal load, heavy load and leading to improve power system dynamic stability.
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.
Comparative Analysis of Power System Stabilizer using Artificial Intelligence...ijsrd.com
Power system stabilizers (PSSs) are used to enhance the damping during low frequency oscillations. The paper presents study of power system stabilizer using fuzzy logic and neural network to enhance stability of single machine infinite bus system. In this paper basic problem of conventional power system stabilizer for stability enhancement is defined which is traditionally used. Artificial intelligence techniques provide one alternative for stability enhancement and speed deviation (Δw). The proposed method using Artificial intelligence techniques achieves better improvement than conventional power system stabilizer. Fuzzy logic rules were developed for triangular membership function of input and output variables. Neuro controller is implemented and it is compared with reference model. The system is simulated in SIMULINK environment and the performances of conventional, Fuzzy based and Neural network based power system stabilizers are compared.
Model based PI power system stabilizer design for damping low frequency oscil...ISA Interchange
This paper explores a two-level control strategy by blending a local controller with a centralized controller for the low frequency oscillations in a power system. The proposed control scheme provides stabilization of local modes using a local controller and minimizes the effect of inter-connection of sub-systems performance through a centralized control. For designing the local controllers in the form of proportional-integral power system stabilizer (PI-PSS), a simple and straight forward frequency domain direct synthesis method is considered that works on use of a suitable reference model which is based on the desired requirements. Several examples both on one machine infinite bus and multi-machine systems taken from the literature are illustrated to show the efficacy of the proposed PI-PSS. The effective damping of the systems is found to be increased remarkably which is reflected in the time-responses; even unstable operation has been stabilized with improved damping after applying the proposed controller. The proposed controllers give remarkable improvement in damping the oscillations in all the illustrations considered here and as for example, the value of damping factor has been increased from 0.0217 to 0.666 in Example 1. The simulation results obtained by the proposed control strategy are favorably compared with some controllers prevalent in the literature.
Neural Network-Based Stabilizer for the Improvement of Power System Dynamic P...TELKOMNIKA JOURNAL
This paper develops an adaptive control coordination scheme for power system stabilizers (PSSs)
to improve the oscillation damping and dynamic performance of interconnected multimachine power
system. The scheme was based on the use of a neural network which identifies online the optimal
controller parameters. The inputs to the neural network include the active- and reactive- power of the
synchronous generators which represent the power loading on the system, and elements of the reduced
nodal impedance matrix for representing the power system configuration. The outputs of the neural
network were the parameters of the PSSs which lead to optimal oscillation damping for the prevailing
system configuration and operating condition. For a representative power system, the neural network has
been trained and tested for a wide range of credible operating conditions and contingencies. Both
eigenvalue calculations and time-domain simulations were used in the testing and verification of the
performance of the neural network-based stabilizer.
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.
Power System MIMO Identification for Coordinated Design of PSS and TCSC Contr...Reza Pourramezan
Authors: Reza Pourramezan, Sadegh Vaez-Zadeh, and Hamid Reza Nourzadeh
Published in 2007 IEEE Power Engineering Society General Meeting (PES)
DOI: 10.1109/PES.2007.385692
Comparison of Different Design Methods for Power System Stabilizer Design - A...ijsrd.com
In the past two decades, the utilization of supplementary excitation control signals for improving the dynamic stability of power systems has received much attention. In recent years, several approaches based on intelligent control and optimization techniques have been applied to PSS design problem. This paper introduces a review on the techniques applied on the conventional PSS design only. Power System Stabilizer (PSS) is the most cost effective approach of increase the system positive damping, improve the steady-state stability margin, and suppress the low-frequency oscillation of the power system. A PSS has to perform well under operating point variations. This paper introduces a review on the techniques applied on the conventional PSS design only. The techniques could be mainly classified into linear and nonlinear.
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.
DYNAMIC STABILITY ANALYSIS (Small Signal Stability) – 1
Small-Signal Stability of Multi-machine Systems
Special techniques for analysis of very large systems
Characteristics of Small-Signal Stability Problems
Local problems
Global problems
DYNAMIC STABILITY ANALYSIS – 2
Introduction
Overview of the Proposed Method
Generating Unit
Synchronous Machine
Calculation of Equilibrium State Conditions
Excitation and Governor Control Systems
Excitation System
Turbine-Governor System
Combined Model of Generating Unit
A Novel Technique for Tuning PI-controller in Switched Reluctance Motor Drive...IJECEIAES
This paper presents, an optimal basic speed controller for switched reluctance motor (SRM) based on ant colony optimization (ACO) with the presence of good accuracies and performances. The control mechanism consists of proportional-integral (PI) speed controller in the outer loop and hysteresis current controller in the inner loop for the three phases, 6/4 switched reluctance motor. Because of nonlinear characteristics of a SRM, ACO algorithm is employed to tune coefficients of PI speed controller by minimizing the time domain objective function. Simulations of ACO based control of SRM are carried out using MATLAB /SIMULINK software. The behavior of the proposed ACO has been estimated with the classical Ziegler- Nichols (ZN) method in order to prove the proposed approach is able to improve the parameters of PI chosen by ZN method. Simulations results confirm the better behavior of the optimized PI controller based on ACO compared with optimized PI controller based on classical Ziegler-Nichols method.
1. International Journal of Engineering Inventions
e-ISSN: 2278-7461, p-ISSN: 2319-6491
Volume 2, Issue 6 (April 2013) PP: 102-106
www.ijeijournal.com Page | 102
Multi Machine Power System Stabilizer Design Using Particle
Swarm Optimization Technique
S. Sasi Rekha
Master of Engineering,
Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College, Chennai, India.
ABSTRACT: In this paper, multi objective design of multi-machine Power System Stabilizers (PSSs) using
Particle Swarm Optimization (PSO) is presented. The stabilizers are tuned to simultaneously shift the lightly
damped and undammed electro-mechanical modes of all machines to a prescribed zone in the s-plane. A multi
objective problem is formulated to optimize a composite set of objective functions comprising the damping
factor, and the damping ratio of the lightly damped electromechanical modes. The PSSs parameters tuning
problem is converted to an optimization problem which is solved by PSO with the eigen value-based multi
objective function. The proposed PSO based PSSs is tested on a multi machine power system under different
operating conditions and disturbances through eigen value analysis and some performance indices to illustrate
its robust performance. The eigen value sensitivity analysis has been used for PSS design in many literatures
under deterministic system operating conditions. To consider the effect of more system operating factors, the
technique of probabilistic eigen value analysis was proposed and has been applied for the parameter design of
power system damping controllers. In the probabilistic eigen value analysis the system stability is enhanced by
shifting the distribution ranges of the critical eigen values to the left side of the complex plane. A new approach
for the optimal decentralized design of PSSs with output feedback is investigated in.
Key words: Eigen value analysis, Genetic Algorithm, Particle Swarm Optimization, Power System Stabilizers.
I. Introduction
STABILITY of power systems is one of the most important aspects in electric system operation. This
arises from the fact that the power system must maintain frequency and voltage in the desired level, under any
disturbance, the development of interconnection of large electric power systems; there have been spontaneous
system oscillations at very low frequencies in the order of 0.2 to 3.0Hz. Moreover, low-frequency oscillations
present limitations on the power-transfer capability.
To enhance the system damping, the generators are equipped with power system stabilizers (PSSs) that
provide supplementary feedback stabilizing signals in the excitation systems. The robustness nature of the CPSS
is due to the fact that the torque-reference voltage and transfer function remains approximately invariant over a
wide range of operating conditions. A gradient procedure for optimization process which requires of PSS
parameters at different operating conditions is presented in this optimization process requires computations of
sensitivity factors and eigenvectors at each iteration. This gives rise to heavy computational burden and slow
convergence. Though the conventional methods content with a good solution it could not able to locate or
identify the global optimum. Consequently, heuristic methods are widely used for global optimization problems.
Recently, global optimization techniques like genetic algorithms (GA), evolutionary programming, Tabu
search, simulated annealing and rule based bacteria foraging have been applied for PSS parameter optimization.
These evolutionary algorithms are heuristic population-based search procedures that incorporate random
variation and selection operators. Although,these methods seem to be good methods for the solution of PSS
parameter optimization problem. However, when the system has a highly epistatic objective function (i.e. where
parameters being optimized are highly correlated), and number of parameters to be optimized is large, then they
have degraded efficiency to obtain global optimum solution and also simulation process use a lot of computing
time. Moreover, in the robust PSS design was formulated as a single objective function problem, and not all PSS
parameter were considered adjustable. In order to overcome these drawbacks, a Particle Swarm Optimization
(PSO) based PSS (PSOPSS) is proposed in this paper. In this study, PSO technique is used for optimal tuning of
PSS parameter to improve optimization synthesis and the speed of algorithms convergence PSO is a novel
population based metaheuristic, which utilize the swarm intelligence generated by the cooperation and
competition between the particles in a swarm and has emerged as a useful tool for engineering optimization. It
has also been found to be robust in solving problems featuring non-linearing.
2. Multi Machine Power System Stabilizer Design Using Particle Swarm Optimization Technique
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II. Problem Statement
2.1. Power system model
The complex nonlinear model related to an n–machine interconnected power system, can be described
by a set of differential- algebraic equations by assembling the models for each generator, load, and other devices
such as controls in the system and connecting them appropriately via the network algebraic equations. The
generator in the power system is represented by Heffron-Philips model and the problem is to design the
parameters of the power system stabilizers.
2.2. PSS Structure
The operating function of a PSS is to produce a proper torque on the rotor of the machine involved in
such a way that the phase lag between the exciter input and the machine electrical torque is compensated A
widely speed based used conventional PSS is considered and the transfer function. The transfer function of the
ith PSS is given by
σ
0
≥σ
i
Where, σi is the real part of the ith eigen value, and σ0 is a chosen threshold. The value of σ0 represents the
desirable level of system damping. This level can be achieved by shifting the dominant eigen values to the left
of s=σ0 line in the s-plane. This also ensures some degree of relative stability. The condition σi≥σ0 is imposed
on the evaluation of J1 to consider only the unstable or poorly damped modes that mainly belong to the
electromechanical ones. The relative stability is determined by the value of σ0.
Ui Ki
sTW
(1 sT1i) (1sT3i )
Δ ωi (s)
(1 sT2i) (1sT4i )1 sTW
Where, Δωi is the deviation in speed from the synchronous speed.
This type of stabilizer consists of a washout filter, a dynamic compensator. The output signal is fed as a
supplementary input signal, Ui, to the regulator of the excitation system. The washout filter, which essentially is
a high pass filter, is used to reset the steady-state offset in the output of the PSS. The value of the time constant
Tw is usually not critical and it can range from 0.5 to 20 s. In this paper, it is fixed to 10 s. The dynamic
compensator is made up to two lead-lag stages and an additional gain. The adjustable PSS parameters are the
gain of the PSS, Ki, and the time constants, T1i-T4i. The lead-lag block present in the system provides phase
lead compensation for the phase lag that is introduced in the circuit between the exciter input and the electrical
torque. The required phase lead can be derived from the lead-lag block even if the denominator portion
consisting of T2i and T4i gives a fixed lag angle. Thus, to reduce the computational burden here, the values of
T2i and T4i are kept constant at a reasonable value of 0.05 s and tuning of T1i and T3i are undertaken to achieve
the net phase lead required by the system.
2.3. Objective function
1) In this case, the closed loop eigen values are constrained to lie to the left of a vertical line corresponding to
a specified damping factor. The parameters of the PSS may be selected to minimize the following objective
function
2) To limit the maximum overshoot, the parameters of the PSS may be selected to minimize the following
objective function
J1∑ (σ0−σi)2
J2 ∑ (ζ 0 − ζi)
ζi ≤ζ0
Where ζi is the damping ratio of the ith
eigen value. This will place the closed-loop eigen values in a wedge-
shape sector in whichζi≥ζ0.
In the case of J2, ζ0 is the desired minimum damping ratio, which is to be achieved. This is usually the case in
dynamic stability where it is desired to relocate the electromechanical modes of oscillations.
3) The parameters of the PSS may be selected to minimize the following objective function:
J 3 J 1 aJ2
This will place the system closed-loop eigen values in the D-contour sector characterized by σi ≤ σ0 and ζi ≥ ζ0.
3. Multi Machine Power System Stabilizer Design Using Particle Swarm Optimization Technique
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The optimization problem can be stated as:
Minimize Ji subject to:
Ki
min
≤ Ki ≤ Ki
T1i
min
≤ T1i ≤ T1i
max
T3
min
i ≤ T3i ≤ T3
max
i
The proposed approach employs PSO to solve this optimization problem and search for an optimal set
of PSS parameters, Ki , T1i and T3i ; i=1, 2,3.
III. PSO Technique
Particle swarm optimization algorithm, which is tailored for optimizing difficult numerical functions
and based on metaphor of human social interaction, It is capable of mimicking the ability of human societies to
process knowledge. It has roots in two main component methodologies. Artificial life(such as bird flocking, fish
schooling and swarming) and, Evolutionary computation. Its key concept is that potential solutions are flown
through hyperspace and are accelerated towards better or more optimum solutions. Its paradigm can be
implemented in simple form of computer codes and is computationally inexpensive in terms of both memory
requirements and speed. It lies somewhere in between evolutionary programming and the genetic algorithms.
Vectors are taken as presentation of particles since most optimization problems are convenient for such variable
presentations. In fact, the fundamental principles of swarm intelligence are adaptability, diverse response,
proximity, quality, and stability. It is adaptive corresponding to the change of the best group value. The higher
dimensional space calculations of the PSO concept are performed over a series of time steps. The population is
responding to the quality factors of the previous best individual values and the previous best group values. As it
is reported in , this optimization technique can be used to solve many of the same kinds of problems as GA, and
does not suffer from some of GAs difficulties. It has also been found to be robust in solving problem featuring
non-linearing, non-differentiability and high-dimensionality. PSO is the search method to improve the speed of
convergence and find the global optimum value of fitness function.
3.1. A Flow Chart of the Proposed PSO technique
4. Multi Machine Power System Stabilizer Design Using Particle Swarm Optimization Technique
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3.2. Case study
Table 1 : Generator Operating Conditions (in PU)
Table 2 : Loading Conditions (in PU)
In this study, the three-machine nine-bus power system is considered. Detail of system data are given in Ref.
To assess the effectiveness and robustness of the proposed method over a wide range of loading conditions,
three different cases designated as nominal, light and heavy loading conditions are considered. The generator
and system loading levels at these cases are given in Tables 1 and 2.
IV. Conclusion
An optimal multi objective design for multi machine power system stabilizers using PSO technique has
been proposed. The stabilizers are tuned to simultaneously shift the lightly damped electromechanical modes of
all plants to a prescribed zone in the s-plane.
A multi objective problem is formulated to optimize a composite set of objective functions comprising
the damping factor, and the damping ratio of the lightly damped electromechanical modes. The design problem
of the robustly PSSs parameters selection is converted into an optimization problem which is solved by a PSO
technique with the eigen value-based multi objective function.
Eigen value analysis give the satisfactory damping on system modes, especially in low-frequency
modes, for the systems with the proposed multi-objective function based tuned PSSs. Time-domain simulations
show that the oscillations of synchronous machines can be quickly and effectively damped for power systems
with the proposed PSSs over a wide range of loading conditions. The system performance characteristics in
terms of ‘ITAE’ and ‘FD’ indices reveal that the proposed multi-objective function based tuned PSSs
demonstrates its superiority in computational complexity, success rate and solution quality.
V. Appendix: Machine Models
δi = ωb(ωi – 1) (A.1)
(A.2)
(A.3)
(A.4)
(A.5)
Tei = E′qiiqi – (xqi – x′di)idi iqi
Gen
Nominal Heavy Light
P Q P Q P Q
G1 0.72 0.27 2.21 1.09 0.36 0.16
G2 1.63 0.07 1.92 0.56 0.80 -0.11
G3 0.85 -0.11 1.28 0.36 0.45 -0.20
Load
Nominal Heavy Light
P Q P Q P Q
A 1.25 0.50 2.00 0.80 0.65 0.55
B 0.90 0.30 1.80 0.60 0.45 0.35
C 1.00 0.35 1.50 0.60 0.50 0.25
~
ωi =
1
Mi
(Pmi – Pei – Di (ωi – 1))
Ėqi =
1
T′doi
(Efdi – (xdi – x′di)idi - E′qi)
Ėfdi =
1
TAi
(KAi (vrefi – vi + ui) - Efd)
5. Multi Machine Power System Stabilizer Design Using Particle Swarm Optimization Technique
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VI. Future Of Work
It’s proposed to implement damping of low frequency oscillations with Multi machine Infinite bus
system using GENITIC ALGORITHM (GA) to the system and the simulated results are compared with and
without power system stabilizer in the future Of work.
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