Auteur : André Mampuya Nzita

Co-auteurs :  Guyh Dituba Ngoma and Clément N’zau Umba-di-Mbudi

Résumé :

The global transition toward sustainable energy systems has increased interest in small hydropower plants because of their low environmental impact and their ability to provide decentralized renewable electricity. However, the performance of these systems remains strongly dependent on hydraulic efficiency, flow regulation, and energy management strategies. In this context, optimization methods used in pumping and hydraulic distribution systems may also improve hydropower operations. This study reviews and compares results reported in the literature concerning the application of metaheuristic algorithms to hydraulic and hydropower systems. The objective is to critically analyze previous studies and identify the most efficient optimization approaches under hydraulic and energy constraints. The methodology is based on a comparative literature review of published scientific studies, focusing on algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Ant Colony Optimization (ACO), NSGA-II, MOPSO, and hybrid optimization methods. The analysis considers convergence speed, energy efficiency, hydraulic performance, robustness, and operational stability. The reviewed studies show that hybrid and multiobjective methods generally provide better optimization results. PSO ensures rapid convergence, whereas NSGA-II is more suitable for multiobjective problems. Further experimental validation and standardized benchmarking are recommended to develop reliable optimization frameworks for small hydropower plants.

Keywords : Intelligent Optimization, Small Hydropower Plants, Metaheuristic Algorithms, Energy Efficiency, Hydraulic Systems, Pumping Systems.