PPO-based Pricing Method for Shared Energy Storage System

Li, Xiangyu; Liu, Hangyue; Li, Chaojie; Chen, Guo; Wen, Shiping

doi:10.1109/isgtasia54193.2022.10003511

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…Game theory is one of the standard tools for analyzing the economics of complex sequential strategy models. By using game theory, the cooperation and competition among multiple stakeholders in RIESs can be clarified, and the enthusiasm of each stakeholder to participate in energy transactions can be fully utilized [16][17][18]. References [19,20] consider the multiple uncertainties caused by the emergence of large-scale producer-consumer clusters.…”

Section: Introductionmentioning

confidence: 99%

Optimization Operation Strategy for Shared Energy Storage and Regional Integrated Energy Systems Based on Multi-Level Game

Yang,

Chen,

Yan

et al. 2024

Energies

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Regional Integrated Energy Systems (RIESs) and Shared Energy Storage Systems (SESSs) have significant advantages in improving energy utilization efficiency. However, establishing a coordinated optimization strategy between RIESs and SESSs is an urgent problem to be solved. This paper constructs an operational framework for RIESs considering the participation of SESSs. It analyzes the game relationships between various entities based on the dual role of energy storage stations as both energy consumers and suppliers, and it establishes optimization models for each stakeholder. Finally, the improved Differential Evolution Algorithm (JADE) combined with the Gurobi solver is employed on the MATLAB 2021a platform to solve the cases, verifying that the proposed strategy can enhance the investment willingness of energy storage developers, balance the interests among the Integrated Energy Operator (IEO), Energy Storage Operator (ESO) and the user, and improve the overall economic efficiency of RIESs.

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Section: Introductionmentioning

confidence: 99%

Optimization Operation Strategy for Shared Energy Storage and Regional Integrated Energy Systems Based on Multi-Level Game

Yang,

Chen,

Yan

et al. 2024

Energies

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“…In this game planning model, the electricity price, the location, and the capacity of the charging station were regarded as the decision variables to optimize the objective functions of both participants. The study in reference [28] proposed a method for setting a capacity subsidy based on the Stackelberg game. The energy storage station, as the leader, formulated its capacity strategy according to the electricity price, while the grid, as the follower, optimized electricity prices based on the capacity of the station.…”

Section: Introductionmentioning

confidence: 99%

Optimal planning strategy for EV charging stations considering travel demands based on non‐cooperative game theory

Zhu

Zhang

Dong

et al. 2022

IET Generation Trans & Dist

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In this paper, an optimal planning strategy is proposed for EV charging stations by considering travel demand based on non‐cooperative game theory. In the proposed methodology, a realistic and stochastic charging demand distribution was obtained with the travel chain of an EV and the associated probability density function. Based on the charging demand of EV owners and a multi‐operator scenario, a two‐stage effective and practical charging station planning model was established. The first stage of the planning model optimized the location of charging stations to decrease the total deadhead mileage of the EVs with the cooperation of the charging station operators. In the second stage, the operators were committed to increasing their economic benefits by developing a charging station capacity strategy in the framework of the non‐cooperative game. Furthermore, the combination of an adaptive mutation particle swarm optimization algorithm (AMPSO) and approximate Nash equilibrium had a better effect in reducing the difficulty of solving the game model and obtaining an optimal planning strategy. Finally, the results of the case study demonstrated the effectiveness of the proposed methodology for improving the charging experience of the EV owners and achieving a balance of benefits among multiple charging station operators.

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