Multi-Time-Scale Resource Allocation Based on Long-Term Contracts and Real-Time Rental Business Models for Shared Energy Storage Systems

被引:2
作者
Zhuang, Yuxuan [1 ]
Li, Zhiyi [1 ]
Tan, Qipeng [2 ]
Li, Yongqi [2 ]
Wan, Minhui [2 ]
机构
[1] Zhejiang Univ, Coll Elect Engn, Hangzhou, Peoples R China
[2] China Southern Power Grid Power Generat Co, Energy Storage Res Inst, Guangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Capacity allocation; long-term contracts; shared energy storage system; stochastic programming; COMMUNITY; MANAGEMENT; OPERATION;
D O I
10.35833/MPCE.2023.000744
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The push for renewable energy emphasizes the need for energy storage systems (ESSs) to mitigate the unpre-dictability and variability of these sources, yet challenges such as high investment costs, sporadic utilization, and demand mismatch hinder their broader adoption. In response, shared energy storage systems (SESSs) offer a more cohesive and efficient use of ESS, providing more accessible and cost-effective energy storage solutions to overcome these obstacles. To enhance the profitability of SESSs, this paper designs a multi-time-scale resource allocation strategy based on long-term contracts and real-time rental business models. We initially construct a life cycle cost model for SESS and introduce a method to estimate the degradation costs of multiple battery groups by cycling numbers and depth of discharge within the SESS. Subsequently, we design various long-term contracts from both capacity and energy perspectives, establishing associated models and real-time rental models. Lastly, multi-time-scale resource allocation based on the decomposition of user demand is proposed. Numerical analysis validates that the business model based on long-term contracts excels over models operating solely in the real-time market in economic viability and user satisfaction, effectively reducing battery degradation, and leveraging the aggregation effect for SESS can generate an additional increase of 10.7% in net revenue.
引用
收藏
页码:454 / 465
页数:12
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