Design and Analysis of a Peak Time Estimation Framework for Vehicle Occurrences at Solar Photovoltaic and Grid-Based Battery-Swappable Charging Stations

Fawad Azeem, Bakhtawar Irshad, Hasan A. Zidan, Ghous Bakhsh Narejo, Muhammad Imtiaz Hussain () and Tareq Manzoor
Additional contact information
Fawad Azeem: Energy Research Center, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan
Bakhtawar Irshad: Department of Food Biotechnology and Environmental Science, Kangwon National University, Chuncheon 24341, Republic of Korea
Hasan A. Zidan: College of Engineering and Information Technology, Ajman University, Ajman 346, United Arab Emirates
Ghous Bakhsh Narejo: Department of Electronic Engineering, NED University of Engineering and Technology, Karachi 76500, Pakistan
Muhammad Imtiaz Hussain: Agriculture and Life Sciences Research Institute, Kangwon National University, Chuncheon 24341, Republic of Korea
Tareq Manzoor: Energy Research Center, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan

Sustainability, 2023, vol. 15, issue 23, 1-16

Abstract: Due to global environmental impacts, the electric vehicle (EV) adoption rate is increasing. However, unlike conventional petrol vehicles, EVs take a considerable time to charge. EVs on the road with different battery charging statuses and driving demographics may cause uncertain peak time arrivals at charging stations. Battery-swappable charging stations are a quick and easier way to replace uncharged batteries with charged ones. However, charging due to uncertain EV arrival causes higher charging profiles posing load to the grid, management of charged and discharged batteries, and peak time charging tariffs. These challenges hinder the wide operation of battery-swappable charging stations. Nevertheless, a pre-assessment of peak hours using EV demographics can reduce congestion. In recent literature surveys for battery-swappable charging stations, spot congestion has not been given much attention, which has a direct influence on the sizing and operation of battery-swappable charging stations. This research study is focused on estimating peak time events using a novel integrated techno-economic assessment framework. A fuzzy-based parametric assessment tool is developed that identifies the factors that influence higher congestion events. Based on the peak event assessment, grid, and solar PV-based generation is optimized using mixed integer linear programming. In the final step, an environment analysis of a swappable charging station is performed. Furthermore, the results achieved using the proposed framework for battery-swappable charging stations (BSCSs) were compared with fast-charging (FC) stations. FC can economically perform well if integrated with solar PV systems; however, the capital cost is 80% greater than the BSCSs designed under the proposed framework. The operational cost of BSCSs is 39% higher than FC stations as they use 29% higher grid units than FC stations due to night operations under congestion.

Keywords: battery-swappable charging; spot congestion; fuzzy-based decision; uncertain peak charging times (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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