An optimization framework for workplace charging strategies |
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| Institution: | 1. Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634, United States;2. Argonne National Laboratory, 9700 S Cass Ave, Bldg 362, Lemont, IL 60439, United States;1. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;2. Department of Civil and Coastal Engineering, University of Florida, 365 Weil Hall, Gainesville, FL 32611, USA;1. Department of Civil and Environmental Engineering, University of California, Davis, CA 95616, United States;2. Department of Mathematics, University of California, Davis, CA 95616, United States;1. Department of Civil Engineering, University of Coimbra, Rua Luis dos Reis Santos, room SA3.4, 3030-788 Coimbra, Portugal;2. Department of Transport and Planning, Delft University of Technology, Stevinweg 1, 2628 CN Delft, Netherlands;3. Department of Mathematics, University of Coimbra, 3001-454 Coimbra, Portugal;1. Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Malaysia;2. Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;3. Department of Management & Humanities, Universiti Teknologi PETRONAS, Malaysia;1. DeGroote School of Business, McMaster University, Hamilton, ON, Canada;2. School of Geography and Earth Sciences, McMaster University, Hamilton, ON, Canada;3. School of Computational Science and Engineering, McMaster University, Hamilton, ON, Canada |
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| Abstract: | The workplace charging (WPC) has been recently recognized as the most important secondary charging point next to residential charging for plug-in electric vehicles (PEVs). The current WPC practice is spontaneous and grants every PEV a designated charger, which may not be practical or economic when there are a large number of PEVs present at workplace. This study is the first research undertaken that develops an optimization framework for WPC strategies to satisfy all charging demand while explicitly addressing different eligible levels of charging technology and employees’ demographic distributions. The optimization model is to minimize the lifetime cost of equipment, installations, and operations, and is formulated as an integer program. We demonstrate the applicability of the model using numerical examples based on national average data. The results indicate that the proposed optimization model can reduce the total cost of running a WPC system by up to 70% compared to the current practice. The WPC strategies are sensitive to the time windows and installation costs, and dominated by the PEV population size. The WPC has also been identified as an alternative sustainable transportation program to the public transit subsidy programs for both economic and environmental advantages. |
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| Keywords: | Workplace charging Optimization Resource allocation |
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