Hierarchical energy management for community microgrids with integration of second‐life battery energy storage systems and photovoltaic solar energy. Issue 2 (26th December 2021)

• Record Type: Journal Article
• Authors: Deng, Youjun; Zhang, Yongxi; Luo, Fengji; Mu, Yunfei
• Is Part Of: IET energy systems integration. Volume 4:Issue 2(2022)
• Page Start: 206
• Page End: 219
• Publication Date: 2021-12-26
• Subjects: microgrid -- residential community -- second‐life battery energy storage system -- smart grid; Power resources -- Periodicals; Energy conservation -- Periodicals; Power resources; Energy conservation; Periodicals; 333.79
• DOI: 10.1049/esi2.12055
• Languages: English
• ISSNs: 2516-8401

Abstract

Abstract: It is recognized by academia and industry that second‐life batteries retired from electric vehicles still have use values and can be effectively used for supporting less demanding applications. At present, there lacks investigation on the applications of re‐using retired batteries on serving residential sector's energy management. Motivated by this, this paper studies the scenario of assembling retired batteries to be second‐life battery energy storage systems (SL‐BESSs) and using them to serve the energy demand of residential communities in an affordable manner. Based on an established SL‐BESS model, a two‐level community energy management framework is proposed, which optimizes the schedules of a SL‐BESS and other energy resources in a community subjected to a variety of short‐term operational objectives. In the upper level, a many‐objective optimization model is formulated, which comprehensively integrates four objectives covering the community's multi‐scale operational considerations. A NSGA‐III‐based solving approach is developed to find the non‐dominated solutions of the model. In the lower level, the optimal community scale load reshaping decisions and energy costs obtained from the upper level are allocated to individual houses. Extensive numerical case studies are conducted, and the results show that the proposed system can realize better trade‐off among the different operational considerations with less computational cost.