scholarly journals Local Search-based Non-dominated Sorting Genetic Algorithm for Optimal Design of Multimachine Power System Stabilizers

2021 ◽  
Vol 11 (3) ◽  
pp. 7283-7289
Author(s):  
F. A. Alshammari ◽  
G. A. Alshammari ◽  
T. Guesmi ◽  
A. A. Alzamil ◽  
B. M. Alshammari ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Power System ◽  
Local Search ◽  
Operating Conditions ◽  
Power System Stabilizers ◽  
Local Optima ◽  
Electromechanical Oscillations ◽  
Search Mechanism ◽  
Wide Range ◽  
Metaheuristic Techniques

This study presents a metaheuristic method for the optimum design of multimachine Power System Stabilizers (PSSs). In the proposed method, referred to as Local Search-based Non-dominated Sorting Genetic Algorithm (LSNSGA), a local search mechanism is incorporated at the end of the second version of the non-dominated sorting genetic algorithm in order to improve its convergence rate and avoid the convergence to local optima. The parameters of PSSs are tuned using LSNSGA over a wide range of operating conditions, in order to provide the best damping of critical electromechanical oscillations. Eigenvalue-based objective functions are employed in the PSS design process. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation proved that the proposed controller provided competitive results compared to other metaheuristic techniques.

scholarly journals Pi Power System Controller: Eigenstructure – Based Design and Sensitivities

2021 ◽  
Vol 15 ◽  
pp. 84-89
Author(s):  
A. El kashlan ◽  
Shady El kashlan
Keyword(s):  
Power System ◽  
Operating Conditions ◽  
System Control ◽  
System Matrix ◽  
Power System Stabilizers ◽  
Power System Control ◽  
Response Characteristics ◽  
Wide Range ◽  
Parameter Variations ◽  
The Right

Significant advances in power system control design techniques that can take into consideration plants linearized around a number of operating conditions. Most of these techniques are based on eigenspectrum analysis which has numerous advantages. A wealth of applications of eigenstructure assignment are available in the literature and showed that new applications have been found and parametric solution of eigenspectrum assignment can be used successfully to design feedback controllers. The use of supplementary controller added to the automatic voltage regulator (AVR) is a practical effective way to supply additional positive damping to system oscillations via power system stabilizers. The present paper utilizes eigenspectrum analysis in the practical design of proportional integral (PI) type power system stabilizers, in order to achieve good steady state as well as transient response characteristics. Eigenspectrum analysis is attractive since it takes into account freedom in determining feedback gains and provides the frequencies and the damping at each frequency for the entire system in a single calculation. Moreover sensitivity of eigenvalues and eigenvectors with respect to parameter variations are assessed so as to provide information to improve setting parameters for power system damping and stability, without ignoring the operating conditions. The results of eigenvalue/eigenvector sensitivity are tangible for analysis with a wide range of parameter variations and is presented through the right and left eigenvectors of the system matrix and also through Taylor series analysis.

A Simple Design Approach for Excitation Controller and Power System Stabilizer

2010 ◽  
Author(s):  
G. Fusco ◽  
M. Russo
Keyword(s):  
Power System ◽  
Transient Stability ◽  
Short Circuit ◽  
Design Procedure ◽  
Voltage Regulation ◽  
Operating Conditions ◽  
Power System Stabilizer ◽  
Simple Design ◽  
Wide Range ◽  
System Stabilizer

This paper proposes a simple design procedure to solve the problem of controlling generator transient stability following large disturbances in power systems. A state-feedback excitation controller and power system stabilizer are designed to guarantee robustness against uncertainty in the system parameters. These controllers ensure satisfactory swing damping and quick decay of the voltage regulation error over a wide range of operating conditions. The controller performance is evaluated in a case study in which a three-phase short-circuit fault near the generator terminals in a four-bus power system is simulated.

Development of a Hybrid Artificial Neural Network and Genetic Algorithm Model for Regime Identification of Slurry Transport in Pipelines

2009 ◽  
Vol 4 (1) ◽  
Author(s):  
Sandip K Lahiri ◽  
Kartik Chandra Ghanta
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Operating Conditions ◽  
Misclassification Error ◽  
Wide Range ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Pipeline Design ◽  
Hybrid Artificial Neural Network

Four distinct regimes were found existent (namely sliding bed, saltation, heterogeneous suspension and homogeneous suspension) in slurry flow in pipeline depending upon the average velocity of flow. In the literature, few numbers of correlations has been proposed for identification of these regimes in slurry pipelines. Regime identification is important for slurry pipeline design as they are the prerequisite to apply different pressure drop correlation in different regime. However, available correlations fail to predict the regime over a wide range of conditions. Based on a databank of around 800 measurements collected from the open literature, a method has been proposed to identify the regime using artificial neural network (ANN) modeling. The method incorporates hybrid artificial neural network and genetic algorithm technique (ANN-GA) for efficient tuning of ANN meta parameters. Statistical analysis showed that the proposed method has an average misclassification error of 0.03%. A comparison with selected correlations in the literature showed that the developed ANN-GA method noticeably improved prediction of regime over a wide range of operating conditions, physical properties, and pipe diameters.

scholarly journals A Modified Genetic Algorithm with Local Search Strategies and Multi-Crossover Operator for Job Shop Scheduling Problem

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5440 ◽  
Author(s):  
Monique Simplicio Viana ◽  
Orides Morandin Junior ◽  
Rodrigo Colnago Contreras
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Crossover Operator ◽  
Local Optima ◽  
Shop Scheduling ◽  
Solution Methods

It is not uncommon for today’s problems to fall within the scope of the well-known class of NP-Hard problems. These problems generally do not have an analytical solution, and it is necessary to use meta-heuristics to solve them. The Job Shop Scheduling Problem (JSSP) is one of these problems, and for its solution, techniques based on Genetic Algorithm (GA) form the most common approach used in the literature. However, GAs are easily compromised by premature convergence and can be trapped in a local optima. To address these issues, researchers have been developing new methodologies based on local search schemes and improvements to standard mutation and crossover operators. In this work, we propose a new GA within this line of research. In detail, we generalize the concept of a massive local search operator; we improved the use of a local search strategy in the traditional mutation operator; and we developed a new multi-crossover operator. In this way, all operators of the proposed algorithm have local search functionality beyond their original inspirations and characteristics. Our method is evaluated in three different case studies, comprising 58 instances of literature, which prove the effectiveness of our approach compared to traditional JSSP solution methods.

Eigenvalue Assignments in Multimachine Power Systems using Multi-Objective PSO Algorithm

2015 ◽  
Vol 4 (3) ◽  
pp. 33-48 ◽  
Author(s):  
Yosra Welhazi ◽  
Tawfik Guesmi ◽  
Hsan Hadj Abdallah
Keyword(s):  
Power Systems ◽  
Optimal Parameter ◽  
Pso Algorithm ◽  
Operating Conditions ◽  
Performance Indices ◽  
Power System Stabilizers ◽  
Nonlinear Simulation ◽  
Multi Objective ◽  
Electromechanical Modes ◽  
Wide Range

Applying multi-objective particle swarm optimization (MOPSO) algorithm to multi-objective design of multimachine power system stabilizers (PSSs) is presented in this paper. The proposed approach is based on MOPSO algorithm to search for optimal parameter settings of PSS for a wide range of operating conditions. Moreover, a fuzzy set theory is developed to extract the best compromise solution. The stabilizers are selected using MOPSO to shift the lightly damped and undamped electromechanical modes to a prescribed zone in the s-plane. The problem of tuning the stabilizer parameters is converted to an optimization problem with eigenvalue-based multi-objective function. The performance of the proposed approach is investigated for a three-machine nine-bus system under different operating conditions. The effectiveness of the proposed approach in damping the electromechanical modes and enhancing greatly the dynamic stability is confirmed through eigenvalue analysis, nonlinear simulation results and some performance indices over a wide range of loading conditions.

scholarly journals Two cases studies of Model Predictive Control approach for hybrid Renewable Energy Systems

AIMS Energy ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 1241-1259
Author(s):  
Lei Liu ◽  
◽  
Takeyoshi Kato ◽  
Paras Mandal ◽  
Alexey Mikhaylov ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Model Predictive Control ◽  
Power System ◽  
Predictive Control ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
First Case ◽  
Control Scheme ◽  
Wide Range ◽  
Simulation Results

<abstract><p>This work presents a load frequency control scheme in Renewable Energy Sources(RESs) power system by applying Model Predictive Control(MPC). The MPC is designed depending on the first model parameter and then investigate its performance on the second model to confirm its robustness and effectiveness over a wide range of operating conditions. The first model is 100% RESs system with Photovoltaic generation(PV), wind generation(WG), fuel cell, seawater electrolyzer, and storage battery. From the simulation results of the first case, it shows the control scheme is efficiency. And base on the good results of the first case study, to propose a second case using a 10-bus power system of Okinawa island, Japan, to verify the efficiency of proposed MPC control scheme again. In addition, in the second case, there also applied storage devices, demand-response technique and RESs output control to compensate the system frequency balance. Last, there have a detailed results analysis to compare the two cases simulation results, and then to Prospects for future research. All the simulations of this work are performed in Matlab®/Simulink®.</p></abstract>

Simulation And Analysis of An Intelligent Power System Stabilizer Using Fuzzy Logic

2020 ◽  
Vol 27 (4) ◽  
pp. 70-86
Author(s):  
firas AlDurze ◽  
sura Abdullah
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Synchronous Machine ◽  
Operating Conditions ◽  
Superior Performance ◽  
Power System Stabilizer ◽  
Operation Conditions ◽  
Wide Range ◽  
Simulation Results ◽  
System Stabilizer

The basic aim of the power system stabilizer is to damp the fluctuations that occur on the rotating axis of the synchronous generator that result from noise or disturbance on the power system. This is achieved by producing an appropriate damping torque for these fluctuations across the excitation circuit of the generator and for a wide range of operation conditions. The study describes the types of power system stabilizers and giving an mathematical model of the power system that consists of a synchronous machine connected to the infinite bus though transmission lines. This has been achieved by simulating the electric and mechanical equations of power systems and proposing a methodological approach to design a Fuzzy Logic Power System Stabilize (FPSS) relaying in the design on the (Matlab/Fuzzy logic toolbox).Speed deviation (Δω) and acceleration (∆ώ) of the synchronous machine are chosen as the input signals to the fuzzy controller in order to achieve a good dynamic performance .The complete range for the variation of each of the two controller inputs is represented by a 7×7 decision table, i.e. 49 rules using proportional derivative like fuzzy logic. The power system (SMIB) was tested with the presence and absence of the excitation system, then (CPSS) was added, and then (FPSS).The simulation results of the proposed fuzzy logic on )SMIB( gave a better dynamic response, decreased the settling time and good performance of the stabilizer in damping the fluctuations that arise in the speed of rotation of the generator and its active power in various operating conditions when proposed (FPSS) is compared with conventional PSS. The simulation results proved the superior performance of the proposed (FPSS).

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