Abstract：To comprehensively consider the benefits of both the supply and demand sides in the scheduling process of a microgrid, an island microgrid dual-layer optimal scheduling model considering demand response is established. The upper level optimizes the output of each unit with the goal of maximizing the net revenue of the microgrid. The lower level optimizes the load curve with the goal of maximizing residents’ overall comfort. An improved dung beetle optimizer is used to solve the dual-layer optimization model. The population is initialized using a sinusoidal mapping and optimized with quasi-oppositional learning to increase population diversity. During the update phase, the Harris hawks’ besiege strategy and adaptive t-distribution perturbation are introduced to enhance the optimization capability and improve the solution quality. The superiority of the improved algorithm is verified by comparing its convergence on test functions with other algorithms. The case study results show that the improved algorithm not only improves the system’s economic benefits but also enhances the users’ electricity and energy comfort. Comparing the results with those obtained by the original dung beetle optimizer confirms the effectiveness of the im-proved method.
2025, Vol. 26 
