Shared energy storage configuration in distribution networks: A multi-agent tri-level programming approach

Yulong Xie, Lee Li, Tianyu Hou, Kang Luo, Zhenyu Xu, Mingcheng Dai and Lixiong Zhang

Applied Energy, 2024, vol. 372, issue C, No S0306261924011541

Abstract: Shared energy storage has the potential to decrease the expenditure and operational costs of conventional energy storage devices. However, studies on shared energy storage configurations have primarily focused on the peer-to-peer competitive game relation among agents, neglecting the impact of network topology, power loss, and other practical factors on energy storage configuration. Additionally, they do not differentiate between various roles of agents, such as shared energy storage operators, electricity consumers, and distribution network operators. To address the challenges presented by the complex interest structures, diverse usage patterns, and potentially sensitive location associated with shared energy storage, we present a multi-agent model for shared energy storage services that takes into account the perspectives of different actors in distribution networks. We develop a tri-level programming model for the optimal allotment of shared energy storage and employ a combination of analytical and heuristic methods to solve it. A case study demonstrates that our model can attain effective allocation of shared energy storage, take into account the interests of multiple parties, and converge well. We examine the impacts of different energy storage service patterns on distribution network operation modes and compare the benefits of shared and non-shared energy storage patterns. By analyzing data on the cost of operating distribution networks, voltage stability, and distributed power consumption, we investigate the potential advantages of the multi-agent distributed shared energy storage service pattern in distribution networks. Our research provides valuable insights into implementing shared energy storage on a large scale in distribution networks.

Keywords: Shared energy storage; Distributed energy storage; Tri-level programming; Multi-agent decision; Power flow optimization; Kkt conditions; Heuristic algorithm (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261924011541
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:372:y:2024:i:c:s0306261924011541

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2024.123771

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().