Collaborative optimization of shared energy storage based on prosumers’ decision-making in a stochastic game framework

doi:10.19799/j.cnki.2095-4239.2025.0054

Abstract

Abstract:

The development of shared-energy-storage operations has gradually become a key approach for prosumers to promote peer-to-peer (P2P) energy trading and enhance economic benefits. However, the uncertainty in prosumers' transaction behaviors and their complex interactions with shared-energy-storage systems complicate the optimization of P2P trading and shared-energy-storage operations. To address this challenge, this study proposes a collaborative optimization method for shared energy storage based on prosumers' decision-making within a stochastic game framework. To manage the notable uncertainty in multiprosumer trading interactions and maximize prosumers' economic benefits, a P2P trading decision-making model grounded in stochastic game theory is developed. The model employs a Markov decision process to represent the multistage trading behaviors of prosumers within the stochastic game, thereby reducing the influence of uncertainty on P2P trading. The optimal trading price is determined by incorporating a supply-demand ratio pricing mechanism, enabling the optimization of trading strategies. The optimized prosumer group is treated as a coalition that trades with shared energy storage. By considering the operational characteristics of shared energy storage, the model further optimizes its charging and discharging strategies to maximize economic benefits. This collaborative optimization between prosumers and shared energy storage resolves the coordination problem, ultimately maximizing economic benefits for both parties. Based on the proposed model, simulations are conducted and compared with traditional noncooperative game methods. The simulation results validate the advantages of the proposed method.

Key words: stochastic game, peer-to-peer trading, shared energy storage, collaborative optimization, supply-demand ratio pricing mechanism

CLC Number:

TM 73

Shuai ZHANG, Tao ZHANG, Wei PEI, Tengfei MA, Hao XIAO, Jie SHI, Chuanxin HE. Collaborative optimization of shared energy storage based on prosumers’ decision-making in a stochastic game framework[J]. Energy Storage Science and Technology, 2025, 14(8): 3216-3228.

Figures/Tables 10

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产消者	非合作博弈/元	随机博弈/元	增长率/%
产消者1	38162.83	39528.04	3.58
产消者2	39909.36	40471.46	1.41
产消者3	41851.06	43156.33	3.12
产消者4	41492.36	42609.72	2.69