Multi-strategy Enhanced Dwarf Mongoose Optimization Algorithm for Microgrid Optimal Scheduling Problem
Weiping Meng, Shijian Chen, Yongquan Zhou · International Journal of Intelligent Information Systems · 2025
A microgrid is an autonomous system that can realize self-control, protection, and management and is composed of distributed power sources, energy storage devices, loads, and control and protection devices. To achieve low operation costs, this paper a multi-strategy enhanced dwarf mongoose optimization algorithm (EDMO) for microgrid scheduling problem is proposed. In EDMO, the convergence speed is accelerated by introducing the golden Sine strategy, which generally makes it difficult to find new excellent solutions at a later stage, lead to a reduction in the population diversity and limiting the development capability, as well as introducing adaptive t-distribution variation to increase the population diversity and the introduction Lévy flight to enhance the algorithm's ability to jump out of the local optimum. The EDMO was compared with other nine algorithms applied to the microgrid optimal scheduling problem. The experimental results show that the proposed EDMO can achieved the lowest total cost, exhibits good performance and robustness, and is an effective method for solving the microgrid scheduling problem.