Open Access

ARTICLE

Coordinated Pricing Technique of P2P Transactions and Shared Energy Storage Leasing for Network-Constrained Microgrid Optimization Dispatching

Fan Sun¹, Li Wang¹, Min Yang¹, Xiaoyu Shao¹, Qiang Hao^2,*
1 State Grid Anhui Economic Research Institute, Hefei, China
2 School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China
* Corresponding Author: Qiang Hao. Email:
(This article belongs to the Special Issue: Active System Support, Resilience, and Electricity Markets of Large-Scale Renewable Energy Systems)

Energy Engineering https://doi.org/10.32604/ee.2026.085963

Received 21 May 2026; Accepted 15 July 2026; Published online 24 July 2026

Abstract

With the rapid increase in distributed energy penetration, pricing mechanisms for P2P energy trading and shared energy storage leasing in microgrids often fail to reflect distribution network constraints, battery degradation, and the opportunity cost of ancillary services. This paper proposes a method for coordinated pricing and optimal dispatch of P2P transactions and shared energy storage leasing that takes network constraints into account. Firstly, a baseline P2P transaction price is established based on the internal supply-demand ratio, and node voltage sensitivity, line power flow margin and network loss effects are incorporated to form a dynamic inter-node P2P price that accounts for network constraints. Secondly, a virtual energy storage account model for multi-user leasing is developed to enable the unified allocation and independent metering of shared energy storage capacity at the user side, thereby supporting energy storage leasing settlement. Furthermore, a shared energy storage leasing pricing model is developed that accounts for energy storage degradation, the opportunity cost of ancillary services, and grid operating conditions, ensuring that the leasing price comprehensively reflects these costs as well as distribution network security constraints. Finally, validation is performed using an enhanced IEEE 33-node system. The results demonstrate that the proposed collaborative pricing mechanism can simultaneously improve the local utilization of PV power and the utilization efficiency of shared energy storage, whilst reducing users’ overall energy costs, increasing revenue for energy storage operators, and ensuring that node voltages and line power flows meet safe operation constraints.

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Keywords

P2P trading; shared energy storage; collaborative pricing; microgrid optimization and dispatch

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