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Hybrid Energy Storage System Optimization With Battery Charging and Swapping Coordination

计算机科学 储能 网格 可再生能源 智能电网 电池(电) 分布式计算 数学优化 工程类 电气工程 功率(物理) 几何学 数学 量子力学 物理
作者
Xinjiang Chen,Yu Yang,Jie Song,Jianxiao Wang,Guannan He
出处
期刊:IEEE Transactions on Automation Science and Engineering [Institute of Electrical and Electronics Engineers]
卷期号:21 (3): 4094-4105 被引量:8
标识
DOI:10.1109/tase.2023.3292189
摘要

Battery storage is a key technology for distributed renewable energy integration. Wider applications of battery storage systems call for smarter and more flexible deployment models to improve their economic viability. Here we propose a hybrid energy storage system (HESS) model that flexibly coordinates both portable energy storage systems (PESSs) and stationary energy storage systems (SESSs) in a grid. PESSs are batteries and power conversion systems loaded on vehicles that travel between grid nodes with price differences to alleviate grid congestion. PESSs can charge/discharge at grid nodes or swap (part of) batteries with SESSs for profit maximization. We introduce a spatiotemporal decision-making framework for HESS including the planning of SESS and the on-demand dispatch of PESS. We propose a two-phase decision-making algorithm (TPDM), where the first phase uses a spatiotemporal cost-effectiveness aggregation method to determine the optimal SESS location; the second phase shapes a low-complexity solution space by arc destroying and repairing. The results show that HESS achieves significant arbitrage benefit improvement in 86.3% of the operating periods through a year compared with SESS and PESS alone. Compared with commercial solver, the proposed TPDM, on average, can reduce the computational time by 95.5% with an optimality of 1.04%. Note to Practitioners —Battery storage and electric vehicles (EVs) play a crucial role in renewable energy integration and in shaping a low-carbon and sustainable energy and transportation systems. To achieve efficient and scalable management of battery storage across energy and transportation systems, we incorporate the portable energy storage (i.e., batteries transported by vehicles) and stationary energy storage (i.e., batteries placed at grids), into a hybrid energy storage system (HESS), and develop efficient planning framework and scheduling algorithms. Specifically, the proposed methods can provide decision supports for the owners of battery assets to determine the optimal SESS location and for the high-quality coordination of battery charging, swapping, and routing in a HESS. Our methods also have potentials in the on-demand applications of battery storage and EVs across energy and transportation systems, such as ancillary services, grid investment deferral, and battery trading and sharing.
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