A two-stage optimization approach-based energy storage sharing strategy selection for limited rational users

In the context of energy storage sharing, as participants' awareness of privacy protection grows, obtaining information will become increasingly challenging, potentially leading decision-making energy storage users to exhibit traits of 'limited rationality'. Existing single energy storage sharing strategies models face challenges in providing adaptable sharing options to limited rational users. To this end, we first introduce a multi-strategies sharing model for energy storage, which integrates capacity sharing and energy prop trading. Following that, we develop a two-stage optimization approach to formulate the selection of sharing strategies for limited rational users. In Stage 1, the energy storage determines the pricing for sharing strategies, adopting both cost-based and demand-based approaches to measure shared capacity and traded energy. In Stage 2, each limited rational user chooses their optimal sharing strategies through a multi-strategy set evolutionary game model rooted in the logit protocol. We jointly solve for the evolutionary and price equilibrium of the two-stage optimization problem to obtain the optimal stabilization strategy. The simulation results demonstrate the effectiveness of the proposed model. Compared to the capacity sharing model, it not only results in a 6.8 % increase in net profit, reduces the payback period from 10.5 years to 7.8 years, but also reduces the energy costs for the users. Moreover, the model provides the most suitable sharing strategy for limited rational users, avoiding idealized conclusions.