A new-fangled adaptive mutation breeder genetic optimization of global multi-machine power system stabilizer

• Published in: International journal of electrical power & energy systems Vol. 44; no. 1; pp. 249 - 258
• Main Authors: Mary Linda, M., Kesavan Nair, N.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.01.2013; Elsevier
• Subjects: Adaptive algorithms; Adaptive Mutation Breeder Genetic Algorithm (ABGA); Adaptive Mutation Breeder Genetic Algorithm Power System Stabilizer (ABGAPSS); Adaptive systems; Applied sciences; Breeder Genetic Algorithm (BGA); Conventional Genetic Algorithm (CGA); Conventional Genetic Algorithm Power System Stabilizer (CGAPSS); Conventional Power System Stabilizer (CPSS); Disturbances. Regulation. Protection; Electric power generation; Electrical engineering. Electrical power engineering; Electrical power engineering; Exact sciences and technology; Genetic algorithms; Mutations; Optimization; Power networks and lines; Robustness; Tuning; Conventional Power System Stabilizer (CPSS); Breeder Genetic Algorithm (BGA); Adaptive Mutation Breeder Genetic Algorithm (ABGA); Adaptive Mutation Breeder Genetic Algorithm Power System Stabilizer (ABGAPSS); Conventional Genetic Algorithm Power System Stabilizer (CGAPSS); Conventional Genetic Algorithm (CGA); Performance evaluation; System configuration; Stabilizator; Evolutionary algorithm; Power system stability; Three phase fault; Implementation; Optimization; Electronic packaging; Robustness; System Stabilizer (CGAPSS); Electric fault; Adaptive Mutation Breeder Genetic; Conventional Genetic Algorithm Power; Algorithm (ABGA); Tuning; Operating conditions; Multimachine power system; Algorithm Power System Stabilizer (ABGAPSS); Genetic algorithm; Soldered joint; System simulation; Effectiveness factor
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2012.06.005

► We model a Power System Stabilizer to minimize the overshoot of low frequency oscillations. ► Different Evolutionary techniques are applied for the design process. ► Three test systems are considered and the simulation results are compared wth the conventional techniques. This paper presents the design and implementation of Power System Stabilizers in a multimachine power system based on innovative evolutionary algorithm overtly as Breeder Genetic Algorithm with Adaptive Mutation. For the analysis purpose a Conventional Power System Stabilizer was also designed and implemented in the same system. Simulation results on multimachine systems subjected to small perturbation and three phase fault radiates the effectiveness and robustness of the proposed Power System Stabilizers over a wide range of operating conditions and system configurations. The results have shown that Adaptive Mutation Breeder Genetic Algorithms are well suited for optimal tuning of Power System Stabilizers and they work better than conventional Genetic Algorithm, since they have been designed to work on continuous domain. This proposed Power System Stabilizer is demonstrated through a weakly connected three multi-machine test systems.