期刊
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 12, 期 1, 页码 387-399出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2020.3001015
关键词
Batteries; Optimization; Charging stations; Biological system modeling; Planning; Electric vehicles; Centralized charging station with PV; echelon battery system; natural aggregation algorithm; rolling horizon optimization; second-life batteries
资金
- National Natural Science Foundation of China [51807011, U1766210]
- Hunan Provincial Natural Science Foundation [2018JJ3536]
- China Studies Centre, The University of Sydney, Australia
The CCS-PV-EBS system utilizes retired batteries to support centralized charging services, with an operation strategy based on rolling horizon and multi-objective optimization method. The proposed Multi-Objective Natural Aggregation Algorithm (MONAA) effectively solves the model, as validated through extensive numerical simulations.
Centralized Charging Station (CCS) provides a convenient charging and maintenance platform for providing battery charging and delivery services to serve Electric Vehicles (EVs)' battery swapping demands at battery swapping points. This article proposes an operational planning framework for a CCS with integration of photovoltaic solar power sources and an Echelon Battery System (EBS) comprising batteries retired from EVs (known as CCS-PV-EBS). The system is characterized by secondary using retired batteries to support the centrally charging services to the serving batteries. A rolling horizon-based operation strategy is proposed for the CCS-PV-EBS, which consists of a battery charging demand determination process and a multi-objective optimization process. An effective solving approach based on Multi-Objective Natural Aggregation Algorithm (MONAA) is developed for the proposed model. Extensive numerical simulations are conducted to validate the proposed method.
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