Improved Multi-objective Dung Beetle Optimizer Based on Non-dominated Sorting for Optimizing Microgrid Scheduling with Clean Energy

In order to solve the problem of intra-network distribution of power resources in microgrid containing clean energy, it is necessary to coordinate the optimization of economic cost and low carbon energy saving, and the existing multi-objective Dung Beetle Optimizer (DBO) algorithm lacked the optimization ability. An improved multiobjective DBO based on non-dominated sorting (NSIDBO) was proposed. Firstly, a microgrid system containing wind-fuel storage and physical constraints of each device was constructed, and a multi-objective cost function based on economy and low carbon was established. Secondly, the Tent mapping based on the disturbance factor was designed, and three parameters were added on this basis to increase the mapping distribution range and improve the initial population diversity. Then, a new type of non-dominated sorting was introduced to find the optimal Pareto front. The roll tracking optimization strategy was designed, and the dynamic step size updated the ball roller to increase the global exploration ability and optimization accuracy of DBO. Finally, an adaptive internal division mechanism was designed to update the proportion of rolling balls and dung beetles, which further improved the convergence of the algorithm. Simulation experiments are conducted on typical 24-hour daily load data provided by IEEE-RTS. The results show that compared with the five comparison algorithms, the proposed NSIDBO method has better comprehensive performance and plays a guiding role in realizing safe and stable control operation of the microgrid. © 2024 Peking University. All rights reserved.