Research on multi-energy complementary microgrid scheduling strategy based on improved bat algorithm

Abstract

In order to improve the accuracy of integrated energy microgrid cluster scheduling operation in existing technologies, a scheduling optimization measure based on an improved bat algorithm was proposed in integrated energy system in this study. Firstly, the integrated demand response (IDR) was used to enhance the load-side energy utilization link. Secondly, the front-end data fragments of the integrated energy system are optimized and integrated based on fuzzy clustering and Mahalanobis distance. Finally, the bat algorithm is improved and substituted by increasing the adaptive inertia weight coefficient. In the simulation stage, the operation simulation test of the system was realized by MATLAB. Experiments show that the optimized integration method based on fuzzy clustering and Mahalanobis distance can make the front-end data achieve reliable clustering, and reduce the redundancy by more than 80%. After improving the bat algorithm, not only the MAPE and RMSE error of scheduling prediction can be reduced to 1.52% and 17.45%, but also the total cost of system scheduling operation can be reduced by about 2.5%. This study can improve the accuracy, economy and prediction speed of scheduling prediction, and has a good application prospect in the field of integrated energy scheduling optimization.

Keywords

• Integrated energy
• Fuzzy clustering
• Mahalanobis distance
• Adaptive inertia weight coefficient
• Bat algorithm