Research on the optimal allocation of shared energy storage in distribution networks considering the network reconfiguration and equivalence of distributed photovoltaic clusters

Shared Energy Storage System (ESS) plays a crucial role in addressing distributed Photovoltaic (PV) curtailment and mitigating distribution network investment costs. To this end, this paper proposes an optimal configuration strategy for shared ESS that considers both the equivalent modeling of distributed PV clusters and distribution network reconfiguration. Firstly, a distributed PV cluster equivalent model was developed, which simultaneously considers electrical distance and active power balance, to facilitate the clustering and equivalencing of distributed PV systems. Secondly, an optimization model for the allocation of shared ESS, considering network reconfiguration and PV clustering results, is proposed. This model minimizes investment costs and maximizes PV energy consumption, while comprehensively considering operational constraints related to PV, ESS, and distribution network reconfiguration. Thirdly, to address the challenge of model solving, a chaotic neural network algorithm is developed by integrating chaotic local search and quasi-oppositional-based learning methods to solve the proposed mixed-integer nonlinear optimization model. Finally, the effectiveness of the proposed method is demonstrated through several case studies based on the IEEE test systems, and the obtained Pareto optimal frontier can provide effective guidance for investors.