Optimization method for island and reef hybrid power generation systems' power capacity based on adaptive ant colony algorithm

Abstract

Objectives Aiming to address the existing challenges in the power capacity configuration of island and reef hybrid power generation systems, this paper proposes an optimization method based on the adaptive ant colony algorithm (ACA). MethodsAn ACA is used as the core optimization tool to configure the power capacity of an island and reef hybrid power generation system. The process of ants foraging is simulated by employing the ACA and using the power generation of renewable energy as dynamic pheromones in the search space. The optimal solution is then found through global search, achieving the full utilization of renewable energy. Taking Wai Lingding Island as the target island, a 'wind-solar-diesel-storage' microgrid hybrid power generation system model is constructed, and the ACA is used to optimize its capacity configuration. ResultsThe simulation results of the algorithm indicate that, compared to the improved Grey Wolf algorithm and Artificial Bee Colony algorithm, the ACA can effectively reduce the operational costs and environmental pollution of the microgrid hybrid power generation system, while ensuring the stability of the power supply. ConclusionsThe results of this study can effectively increase the power supply stability of the microgrid hybrid power generation system, reduce operating costs and environmental pollution, and thus achieve efficient utilization of energy resources.

Keywords

• hybrid power generation system
• adaptive ant colony algorithm (aca)
• capacity configuration
• dynamic pheromone
• economy