Optimal Allocation of Energy Storage in Distribution Network Based on Improved Parrot Algorithm

With the large-scale access of renewable energy sources in distribution networks, the intermittency and randomness of their outputs have brought challenges such as deterioration of voltage stability and increase in line losses to distribution networks. Energy storage is an effective means to solve these challenges, but its access location and capacity size have an important impact on the reliability and economy of distribution network operation. To address this issue, this paper proposes a multi-objective optimisation model for minimising the node voltage deviation, the average annual operating cost of the distribution network, and the investment cost of the energy storage system, taking into account the reliability and economy of the distribution network operation, and solves it by using the improved parrot algorithm. To address the problems of the standard parrot algorithm, this paper proposes the improvement strategies of population initialisation and adaptive probability factor based on Latin hypercubic sampling strategy. The analyses of the algorithms are partially simulated using the improved IEEE-33 nodal distribution system, and the results show that compared with the standard PO algorithm, the improved parrot algorithm can effectively reduce the nodal voltage deviation and the distribution network operation cost, and achieve the dynamic balanced optimization of the operation benefit and the energy storage investment cost.