A group-based optimization design for PV-BESS in energy-sharing hybrid communities

Abstract

The utilization of a combination of renewable energy and battery energy storage system (BESS) in energy sharing communities can alleviate load pressure on the grid and reduce the overall cost of electricity by improving the efficiency of energy utilization. However, most designs of the BESS in communities neglect the effects of energy-sharing potential, resulting in more energy exchanges between community and the grid and oversized capacity of the BESS. Therefore, this paper proposed a distributed group shared optimization design for grid-connected PV-BESS in a hybrid industrial community, aimed at enhancing energy-sharing potential while minimizing the required storage capacity. Firstly, the buildings in community were divided into four groups to minimize annual operating cost. Then, to reduce the yearly total cost and transmission loss, the capacity of each group was optimized by the genetic algorithm (GA). The results showed that compared to the distributed non-grouping optimization design, the proposed design leveraged the energy-sharing potential of the industrial community, with a 20.7 % reduction of the total battery capacity and a 16.1 % decrease of the total annual cost. The mismatch between PV generation and electricity demand was the main factor affecting grouping and battery capacity allocation. Differences in peak-to-valley tariff ratios have no effect on grouping or battery capacity allocation. When the PV array area increases and the differences in peak-to-valley tariff ratios decrease, the corresponding total optimal battery capacity and annual cost decrease, but transmission loss is increased. This study provides guidance for the shared BESS design and application of community.