As the penetration of distributed renewable energy sources, such as wind power and photovoltaic power, increases rapidly in the distribution network, the resulting uncertainty poses significant challenges to the power system. In order to enhance power quality and power system economy, this paper proposes a bilevel optimization model for energy storage in distribution networks based on comprehensive sensitivity. The model achieves economic-technical multi-objective equilibrium through bilevel synergy. First, the comprehensive sensitivity of each node is calculated, thus allowing the impact of energy storage configuration on voltage distribution and network loss to be considered in full. The nodes with the better effect of improving power quality after accessing energy storage are then screened out, thus avoiding the large-scale solution of the storage siting problem. Subsequently, a bilevel optimal configuration model of energy storage is established, with consideration given to the dual objectives of economy and technology of the power system. The outer layer of this model aims to maximize the benefit of energy storage configuration, while the inner layer has the objective of minimizing load and voltage fluctuations. The model is then solved by the improved whale optimization algorithm–multi-objective particle swarm optimization algorithm. The final stage of the research process involved the validation of the proposed optimal energy storage allocation method, with a focus on its effectiveness and applicability under varying levels of renewable energy penetration. To this end, the IEEE 33-node distribution network was selected as the case study.
Guo et al. (Sat,) studied this question.