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A framework for electric vehicle charging-point network optimization

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4 Author(s)
Dong, J. ; IBM Research Division, China Research Laboratory, Beijing, China ; Xie, M. ; zhao, l. ; Shang, D.

Electric vehicles (EVs) are often suggested as an effective green energy technology to reduce gasoline consumption and emissions. When preparing for the widespread adoption of EVs, a critical problem is to plan an optimal charging-point network that could best serve the customers as well as save costs. In this paper, a demand-based optimization model of an EV charging-point network is constructed. In the first part of this paper, the main scenarios of using charging points are identified, and charging demand is summarized in terms of “in-travel charging demand” (e.g., roadside charging during a driving break) and “stay charging demand” (e.g., charging when parking for several hours). Then, the spatial distribution of charging demand is analyzed for each type. In the second part of this paper, a charging-point network-optimization model is developed to improve the convenience of charging EVs (i.e., to minimize the average distance for EV charging) as well as minimize total cost. The framework has been successfully applied to the EV charging-network planning project in a city of China, which demonstrated the applicability of this framework in real-world scenarios.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:57 ,  Issue: 1/2 )