A novel hybrid many optimizing liaisons gravitational search algorithm approach for AGC of power systems
AUTOMATIKA(2020)
摘要
A hybrid Many Optimizing Liaisons Gravitational Search Algorithm (hMOL-GSA)-based fuzzy PID controller is proposed in this work for Automatic Generation Control problem. MOL is a simplified version of particle swarm optimization which ignores the particle best position consequently simplifying the algorithm. The proposed method is employed to tune the fuzzy PID parameters. The outcomes are equated with some newly proposed methods like Artificial Bee Colony (ABC)-based PID for the identical test systems to validate the supremacy of GSA and proposed hMOL-GSA techniques. Further, the design task has been carried out in a three-area test system and the outcomes are equated with newly proposed Firefly Algorithm (FA) optimized PID and Teaching Learning-Based Optimization (TLBO) tuned PIDD controller for the identical system. Better system response has been observed with proposed hMOL-GSA method. Finally, sensitivity study is being carried out and robustness of the proposed method is established.
更多查看译文
关键词
MATLAB/SIMULINK,automatic generation control,fuzzy logic controller,gravitational search algorithm,many optimizing liaisons
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络