Hybrid Management of Distributed PVs and BESSs in Unbalanced Distribution Networks Based on Day-ahead Optimization and Real-time Droop Control

To improve the operation of unbalanced active distribution networks, and address the battery energy storage system (BESS) scheduling and the rooftop photovoltaic (PV) integration problems, this study proposes a two-stage optimal control strategy, based on the combination of day-ahead BESS dispatching and Q-V real-time droop control. Specifically, a multi-objective day-ahead scheduling optimization model is presented firstly, with the objectives of network loss, voltage deviation, load curve variance and VUF deviation. The day-ahead BESS dispatching problem above is jointly solved by the direct load flow (DLF) method and particle swarm optimization (PSO) algorithm. On this basis, the real-time Q-V droop control is introduced to cope with local voltage violations due to load and PV forecast errors, considering of the reactive capability of distributed BESS and PV inverters. Finally, the proposed hybrid BESS control strategy is tested by detailed simulations on an Australian distribution network.