High-penetration grid-connected photovoltaic (PV) systems can lead to reverse power flow, which can cause adverse effects, such as voltage over-limits and increased power loss, and affect the safety, reliability and economic operations of the distribution network. Reasonable energy storage optimization allocation and operation can effectively mitigate these disadvantages. In this paper, the optimal location, capacity and charge/discharge strategy of the energy storage system were simultaneously performed based on two objective functions that include voltage deviations and active power loss. The membership function and weighting method were used to combine the two objectives into a single objective. An energy storage optimization model for a distribution network considering PV and load power temporal changes was thus established, and the improved particle swarm optimization algorithm was utilized to solve the problem. Taking the Institute of Electrical and Electronic Engineers (IEEE)-33 bus system as an example, the optimal allocation and operation of the energy storage system was realized for the access of high penetration single-point and multi-point PV systems in the distribution network. The results of the power flow optimization in different scenarios were compared. The results show that using the proposed approach can improve the voltage quality, reduce the power loss, and reduce and smooth the transmission power of the upper-level grid.
Adaptive Day-Ahead Prediction of Resilient Power Distribution Network Partitions