Distribution Network Power Flow Constrained Shared Energy Storage Configuration for Industrial Consumers Based on Generalized Nash Bargaining Theory

Shared energy storage (SES) provides a new direction for the commercial application of energy storage (ES). This paper studies on the scenario where large industrial energy consumers cooperate to invest and operate the SES, and establishes a SES cooperative game model based on the generalized Nash bargaining (GNB) theory. Taking the rated capacity and the rated power of the SES as the decision variables, this paper considers the total net benefits of each consumer during the whole life cycle of the SES as well as the power flow’s dynamic variation of the distribution network caused by the power interactions among the consumers and the SES. Since the original problem is coupled with the power flow constraints of the distribution network and it belongs to a highly nonlinear mixed integer programming problem (MINLP) with power terms, hard to be solved directly. Therefore, the original model is processed in two aspects: the original problem is equivalently transformed into two consecutive subproblems of collective benefit maximization and cooperative benefit allocation to solve sequentially; then the distribution network power flow is approximately modelled in linearization. Finally, based on a case where four large industrial energy consumers are intended to co-invest in the SES in an 18-bus distribution network, this paper verifies the effectiveness of the model proposed by setting four comparative scenarios. The results show that the SES configuration method for industrial consumers proposed in this paper can not only distribute the benefits more fairly according to the consumers’ contributions to guarantee their enthusiasms for cooperation, but also comprehensively consider the chain reaction of the network-load-storage, making the configuration results more realistic and practical. From the perspective of economy, the way of co-investment in the SES proposed in this paper fully exploits the differences between different energy consumption behaviors, leading to significant economic benefits, which provides a new idea for large industrial users to conduct energy consumption management. © 2023 Power System Technology Press. All rights reserved.