Energy Storage Sharing for Multiple Services Provision: A Computable Combinatorial Auction Design

Bo Wei, Wenfei Liu, Chong Shao, Yong Yang, Yanbing Su and Zhaoyuan Wu ()
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Bo Wei: State Grid Gansu Electric Power Company, Lanzhou 730030, China
Wenfei Liu: State Grid Gansu Electric Power Research Institute, Lanzhou 730070, China
Chong Shao: State Grid Gansu Electric Power Company, Lanzhou 730030, China
Yong Yang: State Grid Gansu Electric Power Research Institute, Lanzhou 730070, China
Yanbing Su: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Zhaoyuan Wu: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China

Sustainability, 2023, vol. 15, issue 16, 1-19

Abstract: Given the profound integration of the sharing economy and the energy system, energy storage sharing is promoted as a viable solution to address the underutilization of energy storage and the challenges associated with cost recovery. While energy storage sharing offers various services for system operation, a significant question remains regarding the development of an optimal allocation model for shared energy storage in diverse application scenarios and the proposal of efficient solving algorithms. This paper presents the design of a computable combinatorial mechanism aimed at facilitating energy storage sharing. Leveraging the distinct characteristics of buyers and sellers engaged in energy storage sharing, we propose a combinatorial auction solving algorithm that prioritizes and incorporates the offers of shared energy storage, accounting for temporal variations in the value of energy resources. The numerical results demonstrate that the proposed solving algorithm achieves a computation time reduction of over 95%, adequately meeting the practical requirements of industrial applications. Importantly, the proposed method maintains a high level of computational accuracy, ranging from 92% to 98%, depending on the participants and application scenarios. Hopefully, our work is able to provide a useful reference for the further mechanism design for energy storage sharing.

Keywords: computational algorithms design; combinatorial auction; energy storage sharing; multiple services provision (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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