Optimal location and optimized parameters for robust power system stabilizer using honeybee mating optimization
Authors:
- 9 June 2014
- journal article
- research article
- Published by Wiley in Complexity
- Vol. 21 (1) , 242-258
Abstract
A honeybee mating optimization technique is used to tune the power system stabilizer (PSS) parameters and find optimal location of PSSs in this article. The PSS parameters and placement are computed to assure maximum damping performance under different operating conditions. One of the main advantages of the proposed approach is its robustness to the initial parameter settings. The effectiveness of the proposed method is demonstrated on two case studies as; 10‐machine 39‐buses New England (NE) power system in comparison with Tabu Search (TS) and 16 machines and 68 buses‐modified reduced order model of the NE New York interconnected system by genetic algorithm through some performance indices under different operating condition. The proposed method of tuning the PSS is an attractive alternative to conventional fixed gain stabilizer design as it retains the simplicity of the conventional PSS and at the same time guarantees a robust acceptable performance over a wide range of operating and system condition. © 2014 Wiley Periodicals, Inc. Complexity 21: 242–258, 2015Keywords
This publication has 21 references indexed in Scilit:
- A comparative study of Artificial Bee Colony algorithmApplied Mathematics and Computation, 2009
- Determination of optimal hierarchical fuzzy controller parameters according to loading condition with ANNExpert Systems with Applications, 2008
- On the performance of artificial bee colony (ABC) algorithmApplied Soft Computing, 2008
- Robust modified GA based multi-stage fuzzy LFCEnergy Conversion and Management, 2007
- A robust H∞ power system stabilizer design using reduced-order modelsInternational Journal of Electrical Power & Energy Systems, 2006
- A neural power system stabilizer trained using local linear controllers in a gain-scheduling schemeInternational Journal of Electrical Power & Energy Systems, 2005
- Optimal multiobjective design of robust power system stabilizers using genetic algorithmsIEEE Transactions on Power Systems, 2003
- Nonlinear decentralized controller design for multimachine power systems using Hamiltonian function methodAutomatica, 2002
- Coordinated synthesis of PSS parameters in multi-machine power systems using the method of inequalities applied to genetic algorithmsIEEE Transactions on Power Systems, 2000
- Robust tuning of power system stabilizers in multimachine power systemsIEEE Transactions on Power Systems, 2000