Improving Seagull Algorithm for Optimal Scheduling of Energy Microgrid Considering Demand Response

Microgrids, as self-contained energy systems, possess great potential in facilitating renewable energy consumption and optimizing energy structures. This paper introduces a model for energy dispatch in microgrids that incorporates demand-side response, utilizing a sigmoid continuum and the chaotic seagull optimization algorithm (SCCSOA). The objective is to tackle the multi-constrained and non-linear operational characteristics of microgrids. The enhanced algorithm leverages a chaotic sequence to initialize the seagull population, while employing the sigmoid function to guide the seagull search process. This approach significantly improves the algorithm's global search capability. Furthermore, a golden sine mechanism is introduced to enhance the local search efficiency in the later stages of the algorithm. The effectiveness of the improved algorithm in microgrid systems is verified through arithmetic simulations that analyze optimization results for different scheduling strategies, thus demonstrating its adaptability.