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• W3139810680 endingPage "106967" @default.
• W3139810680 startingPage "106967" @default.
• W3139810680 abstract "• A novel system promoting electric vehicles and distributed renewables is introduced. • A optimization model manages battery charging/discharging, battery swapping, and VRP. • A method based on Exhaustive Search and Genetic Algorithm solves the NP-hard problem. Emerging nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources and battery storage. And if nanogrids can supply fully-charged batteries (FBs) to a battery swapping station (BSS), it will help establish a novel renewable-energy-to-vehicle system. Following such an idea, this paper considers multiple nanogrids with a BSS as a battery swapping-charging system (BSCS), in which trucks collect FBs from individual nanogrids to the BSS to serve electric vehicles (EVs). In this way, the BSCS can bring together a local range of energy carriers to enhance energy supply cleanliness and promote transportation electrification. The system-level operation framework of the BSCS is introduced, and then a joint optimal scheduling model of it is established based on several effective progressing technologies. The model is formulated based on the mixed-integer linear programming (MILP) and solved by a heuristic method involving Exhaustive Search and Genetic Algorithm. Case studies demonstrate the effectiveness of the employed approach, and they also illustrate the potential benefits of BSCS applications in exploring local energy trading, market mechanisms, and business models." @default.
• W3139810680 created "2021-04-13" @default.
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• W3139810680 date "2021-09-01" @default.
• W3139810680 modified "2023-10-17" @default.
• W3139810680 title "Optimal scheduling for electric vehicle battery swapping-charging system based on nanogrids" @default.
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• W3139810680 doi "https://doi.org/10.1016/j.ijepes.2021.106967" @default.
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