Rizky Ajie Aprilianto, Deyndrawan Sutrisno, Dwi Bagas Nugroho, Wildan Hazballah Arrosyid, Alfan Maulana, Siva Khaaifina Rachmat, Abdrabbi Bourezg, Tiang Jun-Jiat, Abdelbasset Azzouz
The aim of this work is to explore a load frequency control (LFC) strategy in micro hydro power plants (MHPPs). Using MATLAB/Simulink, we examined several variants of genetic algorithms (GAs), including Roulette, Tournament, and Uniform, which are utilized to optimize tuning proportional integral derivative (PID) parameters by addressing the problem of instability caused by load variations. The performances are compared with conventional PID methods and other advanced techniques like particle swarm optimization (PSO), adaptive neuro-fuzzy inference system (ANFIS), and artificial neural networks (ANN) algorithms for both single and dual-area MHPP systems. The results show that the GA-optimized PID controller with the roulette wheel achieves the fastest settling time of 0.3 s and the smallest undershoot of 0.015 pu in the single area. Also, optimizing GA demonstrates superior performance in the dual area, with the fastest settling times of 2.5 s for both Roulette and Uniform. In contrast, PSO is slower than GA, and conventional PID requires a much longer settling time of 19.8 s, a similar result occurring in the dual area. These findings confirm the effectiveness of the GA-optimized PID controller, especially the Roulette variant, as a reliable and fast solution for maintaining frequency stability in MHPPs. © 2026 by the authors.
Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Semarang, Semarang, 50229, Indonesia; Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, ITS, Surabaya, 60111, Indonesia; Department of Mechanical Engineering, Dubai Men’s Campus, Higher Colleges of Technology, P.O. Box, Dubai, 15825, United Arab Emirates; Centre for Wireless Technology, CoE for Intelligent Network, Faculty of Artificial Intelligence & Engineering, Multimedia University, Persiaran Multimedia, Selangor, Cyberjaya, 63100, Malaysia; Laboratory of Electronics, Advanced Signal Processing, and Microwave, LESM, Department of Telecommunications, Saida University, Saida, 20000, Algeria
