Power grid energy storage system planning method based on optimized butterfly algorithm

In response to the power supply security of power grid system caused by a large number of clean energy connected to the distribution network, based on the grid side energy storage investors, the butterfly optimization algorithm is improved by combining the dynamic switching probability coordination algorithm and the dynamic Gaussian mutation strategy. A Distributed Energy Storage System (DESS) planning for power grid is constructed. The results showed that the research model had high stability and convergence accuracy, which was superior to comparison algorithms. When two DESS power stations were connected to nodes 4 and 32, with rated powers of 1.63 MW and 1.78 MW, and rated capacities of 5.71 MWh and 7.33 MWh, the annual benefits of capacity decision, location decision, and system were 783,000 RMB, 394,400 RMB, and 388,600 RMB, respectively. This showed that the research method could help operators obtain the maximum equal life return and meet their investment expectations. Before connecting to DESS, the overall voltage deviation of each typical state decreased by 5.28 p.u., 5.79 p.u., 2.84 p.u., and 2.37 p.u., and the overall active power loss of the daily power grid decreased by 1.41 MW, 1.83 MW, 1.79 MW, and 1.68 MW, respectively, indicating significant optimization effects. The research results indicate that the proposed solution can improve the overall stability and economy of the power grid, with strong applicability. This is of great significance for leveraging the supportive role of energy storage in safe operation and promoting the large-scale application of energy storage systems.