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1.清华大学电机工程与应用电子技术系,北京市 100084
2.青海大学能源与电气工程学院,青海省西宁市 810016
Received:14 April 2025,
Revised:2025-05-18,
Online First:05 August 2025,
Published:10 December 2025
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TIAN Xin,CHEN Laijun,SUN Yingcong,et al.Shared Energy Storage Service Mechanism Based on Time-slot Capacity Leasing and Energy Trading[J].Automation of Electric Power Systems,2025,49(23):17-26.
田欣,陈来军,孙英聪等.基于时段容量租赁与能量交易的共享储能服务机制[J].电力系统自动化,2025,49(23):17-26. DOI: 10.7500/AEPS20250414003.
TIAN Xin,CHEN Laijun,SUN Yingcong,et al.Shared Energy Storage Service Mechanism Based on Time-slot Capacity Leasing and Energy Trading[J].Automation of Electric Power Systems,2025,49(23):17-26. DOI: 10.7500/AEPS20250414003.
共享储能模式不仅可以充分发挥储能的灵活调节优势,而且可进一步降低运营成本和提升经济效益,但如何向用户提供更为灵活的共享服务则是关键问题。针对该问题,提出了基于时段容量租赁及能量交易的共享储能两阶段服务机制。在“资源分配”的第1阶段,储能运营商根据新能源场站提出的需求,决策储能在容量租赁及能量交易服务之间的资源分配;在“多轮投中标”的第2阶段,由场站与储能运营商对储能服务进行需求及供给的多轮迭代决策。其中,容量租赁及能量交易价格分别由租赁时长及能量供需比决定。在此基础上,分别建立了新能源场站及储能运营商的决策优化模型,并对模型进行线性化后求解。仿真结果表明,所提机制能够提升参与者的经济效益,且所提定价策略提高了场站参与共享储能交易的积极性。
The shared energy storage mode not only fully leverages the flexible regulation advantages of energy storage
but also further reduces operation costs and enhances economic benefits. However
how to provide users more flexible shared services is a key issue. To address this issue
a two-stage service mechanism for shared energy storage based on time-slot capacity leasing and energy trading is proposed. In the first stage of “resource allocation”
the energy storage operator decides the resource allocation of energy storage between capacity leasing and energy trading services according to the demands proposed by renewable energy stations. In the second stage of “multi-round bidding-winning”
the stations and energy storage operators engage in multiple rounds of iterative decision-making regarding the demand and supply of energy storage services. Among them
the prices for capacity leasing and energy trading are determined by the leasing duration and the energy supply to demand ratio
respectively. On this basis
decision optimization models are established for both the renewable energy stations and the energy storage operators
and the models are solved after linearization. Simulation results show that the proposed mechanism can enhance the economic benefits of participants
while the proposed pricing strategy increases the enthusiasm of stations to participate in shared energy storage tradings.
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