A Stackelberg Game-based robust optimization for user-side energy storage configuration and power pricing

With the rapid development of demand-side management, battery energy storage is considered to be an important way to promote the flexibility of the user-side system. In this paper, a Stackelberg game (SG) based robust optimization for user-side energy storage configuration and basic electricity price decisions is proposed. Firstly, this paper put forward a two-stage energy management framework considering the interactive relationship between the supplier-side system and the user-side system. Secondly, based on the two-part electricity price mechanism, a bi-level optimal sizing of user-side energy storage is established in which robust dispatching is considered to deal with the uncertainty of renewable energy. Thus, a three-layer optimization model of pricing on the power supply side-basic scenario configuration on the user side-worst-case scenario scheduling on the user side is formulated. Through relaxing the state variables of energy storage in the configuration and scheduling models and combining Karush-Kuhn-Tucher conditions, the user-side model is transformed into a single-layer problem. A distributed algorithm based on the method of bisection is used to solve the two-stage SG problem. The simulation results demonstrate the basic electricity price and energy storage configuration suggestions and prove the superiority of the proposed method.

Automated summary

With the rapid development of demand-side management, battery energy storage is seen as crucial for improving flexibility on the user side. This paper introduces a Stackelberg game-based robust optimization approach for user-side energy storage configuration and electricity price decisions. By considering the interactive relationship between the supplier-side system and the user-side system, a two-stage energy management framework is proposed. A bi-level optimal sizing model is established based on a two-part electricity price mechanism, which incorporates robust dispatching to handle renewable energy uncertainties. The simulation results validate the effectiveness of the proposed method by providing electricity price and energy storage configuration recommendations.