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Coordinated planning of electrochemical energy storages at both transmission and distribution sides under the electricity market environment

Yunpeng XiaoState Key Laboratory of Electrical Insulation and Power Equipment, Xi'an, 710049, ChinaTao HuElectric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang, 330096, ChinaBo GaoSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, ChinaYingxue LiEconomic and Technology Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang, 330043, ChinaEshchanov Baxtiyor RuzumbayevichTashkent State University of EconomicsAkmal AkhatovDepartment of Applied Mathematics and Informatics, Samarkand State University, Samarkand, 140100, Uzbekistan
2026en
ABI

Annotatsiya

In the process of constructing the new power system dominated by renewable energy sources, the demand for electrochemical energy storage deployment is continuously expanding. With the ongoing decline in storage costs and the gradual improvement of electricity market mechanisms, energy storage planning needs to adapt to the market-oriented environment. However, current coordinated transmission and distribution-side storage planning has not yet accounted for the influence of electricity market factors, leading to biased planning outcomes. To address this, this paper proposes a coordinated planning method for transmission and distribution-side electrochemical energy storage that incorporates wholesale-retail electricity price pass-through. First, a coordinated planning framework for transmission and distribution-side storage is established, considering both the physical and value coupling of the two networks. Second, planning models for the transmission and distribution sides are constructed separately. On the transmission side, the storage planner is the independent storage investor, and a bi-level model is formulated with the upper level representing storage investment decisions and the lower level simulating electricity energy market clearing. On the distribution side, all prosumers within the same distribution network are regarded as the storage investors, and a cooperative game model based on generalized Nash bargaining theory is developed. Third, an iterative method is employed to solve the proposed coordinated planning model, and a bisection-based heuristic algorithm is introduced to prevent possible oscillations during the iteration process. Finally, case study results demonstrate that the proposed coordinated transmission and distribution-side storage planning method can achieve globally optimal allocation of storage resources and effectively capture the interactions between resource endowment changes on both sides and market price signals.

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