Maximizing Power Generation in Variable Speed Micro-Hydro with Power Point Tracking

• Published in: 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) pp. 1 - 6
• Main Authors: Tan, Min Keng, Javinez, Norafe Maximo, Lim, Kit Guan, Haron, Ahmad Razani, Ibrahim, Pungut, Kin Teo, Kenneth Tze
• Format: Conference Proceeding
• Language: English
• Published: IEEE 13-09-2022
• Subjects: genetic algorithm; maximum power point tracking; perturb-and-observe; variable speed micro-hydro
• DOI: 10.1109/IICAIET55139.2022.9936859

Conventional variable speed micro-hydro control systems suffer from non-optimal input control. The controllers estimate the changes in flow rate without anticipating the global maximum power curve. As such, this paper aims to explore and develop a feasible maximum power point tracker (MPPT) with perturb and observe (P&O) and genetic algorithm (GA) in providing optimal power generation for variable speed micro-hydro system. This research first introduces a mathematical model for an experimental variable speed micro-hydro platform and then simulates the micro-hydro in MATLAB. Conventional P&O MPPT algorithm used fixed perturbation size which requires large computation time when the perturbation size is small and suffers from power fluctuation issues when the perturbation size is large. Thus, a GA-based P&O MPPT algorithm with adaptive perturbation size is proposed to provide a large perturbation size during transient response and a small perturbation size at a steady state. The simulation results showed that the proposed GA-based P&O MPPT algorithm was able to track the global maximum power point (MPP).