A Cooperative Game Approach for Optimal Design of Shared Energy Storage System

Author:

Wang Qin1,Zeng Jincan1,Cheng Beibei2,Liu Minwei3,Huang Guori1,Liu Xi1,He Gengsheng1,Yao Shangheng1,Wang Peng2,Li Longxi45

Affiliation:

1. Energy Development Research Institute, China Southern Power Grid, Guangzhou 510663, China

2. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China

3. Planning & Research Center for Power Grid, Yunnan Power Grid Corp., Kunming 650011, China

4. School of Economics and Management, China University of Geosciences, Wuhan 430074, China

5. Center for Energy and Environmental Management and Decision-Making, China University of Geosciences, Wuhan 430074, China

Abstract

The energy sector’s long-term sustainability increasingly relies on widespread renewable energy generation. Shared energy storage embodies sharing economy principles within the storage industry. This approach allows storage facilities to monetize unused capacity by offering it to users, generating additional revenue for providers, and supporting renewable energy prosumers’ growth. However, high investment costs and long payback periods often hinder the development of battery storage. To address this challenge, we propose a shared storage investment framework. In this framework, a storage investor virtualizes physical storage equipment, enabling prosumers to access storage services as though they owned the batteries themselves. We adopt a cooperative game approach to incorporate storage sharing into the design phase of energy systems. To ensure a fair distribution of cooperative benefits, we introduce a benefit allocation mechanism based on contributions to energy storage sharing. Utilizing realistic data from three buildings, our simulations demonstrate that the shared storage mechanism creates a win–win situation for all participants. It also enhances the self-sufficiency and self-consumption of renewable energy. This paper provides valuable insights for shared storage investors regarding optimal design and benefit allocation among multiple stakeholders.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

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