Wind power optimization using modified memetic algorithm

Abstract

This research paper introduces an approach for optimizing the design of wind turbines to enhance their electrical output. To efficiently convert wind energy into electrical energy, a specific turbine design is essential. The study employs a modified shuffled frog-leaping algorithm (MSFLA), an improved variant of the memetic algorithm, to determine the optimal wind power coefficient by adjusting rotor speed at various wind velocities (including rated, cut-in, and cut-out speeds). MSFLA combines global and local search techniques, following divide-and-conquer principles, to achieve better results. By imposing specific turbine constraints, the simulation demonstrates that the wind power coefficient can be increased under optimized conditions.