scholarly journals Reinforcement Learning Based Algorithm for the Maximization of EV Charging Station Revenue

Author(s):  
Stoyan Dimitrov ◽  
Redouane Lguensat
Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6255
Author(s):  
Ki-Beom Lee ◽  
Mohamed A. Ahmed ◽  
Dong-Ki Kang ◽  
Young-Chon Kim

This paper proposes an optimal route and charging station selection (RCS) algorithm based on model-free deep reinforcement learning (DRL) to overcome the uncertainty issues of the traffic conditions and dynamic arrival charging requests. The proposed DRL based RCS algorithm aims to minimize the total travel time of electric vehicles (EV) charging requests from origin to destination using the selection of the optimal route and charging station considering dynamically changing traffic conditions and unknown future requests. In this paper, we formulate this RCS problem as a Markov decision process model with unknown transition probability. A Deep Q network has been adopted with function approximation to find the optimal electric vehicle charging station (EVCS) selection policy. To obtain the feature states for each EVCS, we define the traffic preprocess module, charging preprocess module and feature extract module. The proposed DRL based RCS algorithm is compared with conventional strategies such as minimum distance, minimum travel time, and minimum waiting time. The performance is evaluated in terms of travel time, waiting time, charging time, driving time, and distance under the various distributions and number of EV charging requests.


Author(s):  
Mohammad Shahidehpour ◽  
Tao Qian ◽  
Chengcheng Shao ◽  
Xuliang Li ◽  
Xiuli Wang ◽  
...  

Systems ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 19
Author(s):  
Mahdi Boucetta ◽  
Niamat Ullah Ibne Hossain ◽  
Raed Jaradat ◽  
Charles Keating ◽  
Siham Tazzit ◽  
...  

Exponential technological-based growth in industrialization and urbanization, and the ease of mobility that modern motorization offers have significantly transformed social structures and living standards. As a result, electric vehicles (EVs) have gained widespread popularity as a mode of sustainable transport. The increasing demand for of electric vehicles (EVs) has reduced the some of the environmental issues and urban space requirements for parking and road usage. The current body of EV literature is replete with different optimization and empirical approaches pertaining to the design and analysis of the EV ecosystem; however, probing the EV ecosystem from a management perspective has not been analyzed. To address this gap, this paper develops a systems-based framework to offer rigorous design and analysis of the EV ecosystem, with a focus on charging station location problems. The study framework includes: (1) examination of the EV charging station location problem through the lens of a systems perspective; (2) a systems view of EV ecosystem structure; and (3) development of a reference model for EV charging stations by adopting the viable system model. The paper concludes with the methodological implications and utility of the reference model to offer managerial insights for practitioners and stakeholders.


Author(s):  
Rata Mihai ◽  
Rata Gabriela ◽  
Filote Constantin ◽  
Afanasov Ciprian ◽  
Raboaca Maria Simona
Keyword(s):  

Solar Energy ◽  
2020 ◽  
Vol 205 ◽  
pp. 170-182
Author(s):  
Ahmed A.S. Mohamed ◽  
Ahmed El-Sayed ◽  
Hamid Metwally ◽  
Sameh I. Selem

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