期刊
IEEE TRANSACTIONS ON SMART GRID
卷 13, 期 1, 页码 641-653出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2021.3119912
关键词
Batteries; Logistics; Costs; Roads; Predictive models; Load modeling; Data models; Electric vehicles (EVs); photovoltaic generation; logistics delivery service; hierarchical operation management
资金
- National Natural Science Foundation of China [52061635103]
- Key Research and Development Program of Tianjin [20YFYSGX00060]
This paper proposes a two-stage hierarchical operation management method for electric vehicles based on depot solar photovoltaic generation. It aims to minimize energy costs and logistics delivery costs by using forecasted PV power output, and proposes a strategy to correct charging/discharging decisions to minimize power deviation between the depot and upper grid.
Solar photovoltaic (PV) generation is a promising energy cost-saving selection for depots that use electric vehicles (EVs) to deliver goods; however, the intermittency of power output renders it challenging to realize reliable and economical operations. This paper proposes a two-stage hierarchical operation management method of EVs for depots with on-site PV generation. In the day-ahead stage, considering real road networks and battery swapping mode, a coordinated scheduling model of delivery service and charging/discharging for EVs is constructed to minimize the overall energy cost and logistics delivery cost by using the forecasted PV power output. Moreover, an effective solution approach based on the natural aggregation algorithm and Floyd algorithm is developed for the model. In the actual operation stage, a model prediction control (MPC)-based rolling horizon operation strategy is proposed to correct EVs' charging/discharging decisions with the realization of real-time PV power output, aiming at to minimize the deviation in the actual and day-ahead scheduled interactive power between the depot and upper grid. Finally, simulations are conducted to validate the proposed methods.
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