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

作　　者：Yuxuan Zhuang Zhiyi Li Qipeng Tan Yongqi Li Minhui Wan 

机构地区：[1]College of Electrical Engineering,Zhejiang University,Hangzhou,China [2]China Southern Power Grid Power Generation Company Energy Storage Research Institute,Guangzhou,China [3]IEEE

出　　处：《Journal of Modern Power Systems and Clean Energy》2024年第2期454-465,共12页现代电力系统与清洁能源学报（英文）

基　　金：supported by National Natural Science Foundation of China(No.U2066601).

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.

关 键 词：Capacity allocation long-term contracts shared energy storage system stochastic programming 

分 类 号：TM91[电气工程—电力电子与电力传动]