Objectives To address the conflicting objectives between “maximizing renewable energy accommodation” and “ensuring power supply reliability” in distributed energy storage systems, a coordinated planning method that balances economic efficiency and resilience is proposed. Methods A dynamic Stackelberg game-driven bi-level planning model is established, integrating Stackelberg game theory with robust optimization to address the cross-level coupling problem between planning and operation. The model coordinates the interests of planning, operation, and market stakeholders to optimize energy storage capacity allocation and charging/discharging strategies, thereby enhancing power supply reliability. Through bi-level optimization, coordination between planning and operation is achieved, and the trade-off between accommodation and supply security is quantified, with Pareto-optimal solutions derived to achieve the lowest investment costs and highest renewable energy accommodation rates. Results A rapid solution algorithm for a bi-level model incorporating multi-objective optimization is developed, and a “dynamic pricing-capacity subsidy” linkage mechanism is proposed. This mechanism effectively balances the conflicting interests among multiple stakeholders in planning and operation. By integrating Stackelberg game theory with robust optimization, the cross-level coupling problem between planning and operation is solved. The simulation cases demonstrate that the proposed bi-level game model significantly outperforms conventional planning methods, validating the long-term economic efficiency of the dynamic game mechanism. Furthermore, a nonlinear trade-off relationship between renewable energy accommodation and power supply security is revealed. Conclusions The bi-level planning model based on accommodation-supply security game coordination can significantly enhance the system’s renewable energy accommodation rate and power supply reliability, while reducing energy storage system investment costs and user electricity costs.

Facing the flexible and adjustable resources inside the intelligent distribution area of distribution network, a Stackelberg game pricing strategy and electric vehicle ( EV) charging management strategy for distribution network operator based on scenario generation method is proposed to guide the user-side flexible resources to realize efficient interaction with the distribution network through market-oriented means. Firstly, based on conditional density networks (CDNs), Gibbs sampling method is used to predict EV load, which takes into account the joint probability distribution of EV users′ charging characteristics, and EV aggregation model is constructed to reduce the model dimension. The distribution locational marginal pricing (DLMP) based on the second-order conical optimal power flow model of distribution network is obtained, and on this basis, the Stackelberg game pricing strategy and user-side incentive mechanism of distribution network operator are constructed. The bi-level Stackelberg game model is transformed into a mixed-integer linear programming problem using the Karush-Kuhn-Tucker (KKT) conditions and optimal duality theory for solution, and finally the global optimal pricing strategy is obtained, and the power allocation module is used to realize the reasonable distribution of charging power for EV users. Simulation results based on improved IEEE 33-node power distribution system verify the effectiveness of the proposed strategy.