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Optimization of configurations and scheduling of shared hybrid electric‑hydrogen energy storages supporting to multi-microgrid system

微电网 储能 计算机科学 分布式发电 热能储存 可再生能源 能源管理 工艺工程 分布式计算 数学优化 工程类 功率(物理) 能量(信号处理) 电气工程 统计 物理 生物 量子力学 数学 生态学
作者
Hongda Deng,Jiangjiang Wang,Yuming Shao,Yuan Zhou,Yihuai Cao,Xutao Zhang,Weihua Li
出处
期刊:Journal of energy storage [Elsevier]
卷期号:74: 109420-109420 被引量:16
标识
DOI:10.1016/j.est.2023.109420
摘要

As the energy structure undergoes transformation and the sharing economy advances, hydrogen energy and shared energy storage will become the new norm for addressing future energy demand and user-side storage applications, in order to better meet the flexibility and sustainability requirements of the energy system. This paper focuses on shared energy storage that links multiple microgrids and proposes a bi-layer optimization configuration method based on a shared hybrid electric‑hydrogen storage station for microgrids, combining cooling, heating, and power systems, to better achieve efficient energy utilization and promote sustainable development. The upper-layer model solves the energy storage station capacity configuration problem, while the lower-layer model solves the optimization operation problem of the multi-microgrid system. The lower-layer model is transformed into a constraint condition of the upper-layer model based on the Karush-Kuhn-Tucher condition of the lower-layer optimization model, and the Big-M method is used to linearize nonlinear problems. The rationality and effectiveness of the proposed bi-layer planning model are verified through analytical examples in three different scenarios. The results showed that compared to individual energy storage, shared power storage achieved an average daily net income of $430.00, reduced battery capacity by 75.94 %, and reduced daily operating costs of the microgrids by 11.53 %. Hybrid energy storage increased the daily net income of the energy storage side by 61.67 %, further reduced battery capacity by 67.13 %, and further reduced daily operating costs of the microgrid by 3.39 %. In addition, the optimal capacity allocation of energy storage systems and the operation optimization of multi microgrid systems have been achieved. The results demonstrate that the proposed hybrid energy storage services can effectively reduce user costs, save energy storage resources, and achieve mutual benefits for both users and energy storage operators.
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