Optimal bidding strategy and profit allocation method for shared energy storage-assisted VPP in joint energy and regulation markets

投标 虚拟发电厂 利润(经济学) 储能 可再生能源 电力市场 计算机科学 夏普里值 业务 环境经济学 分布式发电 微观经济学 经济 工程类 功率(物理) 博弈论 电气工程 物理 量子力学
作者
Tianhan Zhang,Weiqiang Qiu,Zhi Zhang,Zhenzhi Lin,Yi Ding,Yi‐Ting Wang,Lianfang Wang,Li Yang
出处
期刊:Applied Energy [Elsevier BV]
卷期号:329: 120158-120158 被引量:119
标识
DOI:10.1016/j.apenergy.2022.120158
摘要

Renewable energy sources (RES) generating units such as wind power and photovoltaic (PV) units can be aggregated with controllable loads as virtual power plants (VPPs) to jointly participate in energy and regulation markets for extra market revenue. However, the uncertainty of RES limits the market performance of the VPP, which can be solved by energy storage. Due to the flexibility of the energy storage sharing mode, a two-part price-based leasing mechanism of shared energy storage (SES) considering market prices and battery degradation is proposed to provide the short-term use rights of energy storage for the VPP in a new pattern. Then, an SES-assisted real-time output cooperation scheme for the VPP in joint energy and regulation markets is designed to improve the VPP market performance and a joint optimal market bidding model of the VPP with the assistance of the SES is developed to maximize the expected daily profit. Moreover, a profit allocation approach for the SES-assisted VPP based on the improved Shapley value method and the minimizing deviation algorithm (ISV-MDA) is proposed to reflect the real contributions and balance the interests of its participants. Simulations based on data from PJM and NREL Dataset illustrate that RES can significantly improve their profits by participating in the VPP to jointly lease the use rights of SES and participate in joint energy and regulation markets through the cooperation and bidding strategies. In addition, the proposed profit allocation method is more reasonable and more targeted for allocating the cooperation profit than the cooperative game-based methods.
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