Maximum power tracking of wave energy generation system based on improved sparrow search algorithm
Year: 2025
Type: conference-paper
Abstract: The sparrow search algorithm (SSA) has emerged as a promising swarm intelligence optimization technique, particularly in the context of maximum power point tracking (MPPT) for wave energy generation systems. It has demonstrated significant potential in optimizing power capture efficiency. Building on this foundation, this paper introduces an enhanced variant of the SSA, termed the Firefly Search Perturbation-based Sparrow Search Algorithm (FSSA). By integrating firefly search perturbation, the proposed FSSA aims to further improve the optimization capabilities of the original SSA. Simulation results indicate that FSSA effectively mitigates the risk of the wave energy generation system becoming trapped in local maxima, thereby enhancing its overall energy capture efficiency.
Authors: Ying Lan, Jiayu Huang
Institution: Shanghai Maritime University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409504816