An Intelligent Recommendation for Intelligently Accessible Charging Stations: Electronic Vehicle Charging to Support a Sustainable Smart Tourism City

Pannee Suanpang (), Pitchaya Jamjuntr, Phuripoj Kaewyong, Chawalin Niamsorn and Kittisak Jermsittiparsert ()
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Pannee Suanpang: Faculty of Science & Technology, Suan Dusit University, Bangkok 10300, Thailand
Pitchaya Jamjuntr: Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand
Phuripoj Kaewyong: Faculty of Science & Technology, Suan Dusit University, Bangkok 10300, Thailand
Chawalin Niamsorn: Faculty of Management Sciences, Suan Dusit University, Bangkok 10300, Thailand
Kittisak Jermsittiparsert: Faculty of Education, University of City Island, Famagusta 9945, Cyprus

Sustainability, 2022, vol. 15, issue 1, 1-18

Abstract: The world is entering an era of awareness of the preservation of natural energy sustainability. Therefore, electric vehicles (EVs) have become a popular alternative in today’s transportation system as they have zero emissions, save energy, and reduce pollution. One of the most significant problems with EVs is an inadequate charging infrastructure and spatially and temporally uneven charging demands. As such, EV drivers in many large cities frequently struggle to find suitable charging locations. Furthermore, the recent emergence of deep reinforcement learning has shown great promise for improving the charging experience in a variety of ways over the long term. In this paper, a Spatio-Temporal Multi-Agent Reinforcement Learning (STMARL) (Master) framework is proposed for intelligently public-accessible charging stations, taking into account several long-term spatio-temporal parameters. When compared to a random selection recommendation system, the experimental results demonstrate that an STMARL (master) framework has a long-term goal of lowering the overall charging wait time ( CWT ), average charging price ( CP ), and charging failure rate ( CFR ) of EVs.

Keywords: electric vehicle; intelligent recommendation system; electronic vehicle charging; smart tourism; destination; smart city (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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