出租
可再生能源
储能
分布式数据存储
热能储存
分布式发电
计算机科学
需求响应
分布式计算
数学优化
工程类
土木工程
电气工程
数学
电
功率(物理)
生态学
物理
生物
量子力学
作者
Yanrong Wang,Jiajia Chen,Yanlei Zhao,Bei Xu
出处
期刊:Energy
[Elsevier BV]
日期:2024-05-22
卷期号:301: 131721-131721
被引量:6
标识
DOI:10.1016/j.energy.2024.131721
摘要
The increasing uncertainty and volatility of net load caused by the high penetration of renewable energy leads to higher demand tariffs for industrial park and potentially impacts their economic benefits. To tackle these issues, this paper develops a novel business mode to enable rental energy storage sharing among multiple users within an industrial park, and propose a robust optimization and demand defense-based iterative bi-layer planning framework. The upper layer focuses on the maximization of the investment profitability of shared rental energy storage by developing a robust information gap decision theory optimization. Meanwhile, the lower layer is dedicated to enhancing the demand defense ability of shared rental energy storage in real-time operation through the formulation of a distributed model predictive control. After that, the synchronous alternating direction multiplier method with consistency theory is derived for solving the distributed optimization. Numerical results demonstrate that the proposed shared rental energy storage is 6.391% and 7.714% more economical than shared and self-built energy storage, respectively. Moreover, the iterative bi-layer planning enables flexible energy storage capacity configuration, reduces the impact of net load uncertainty, improves the ability of demand defense, and enhances the system's overall economy.
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