{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T02:43:21Z","timestamp":1773974601320,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,27]],"date-time":"2020-08-27T00:00:00Z","timestamp":1598486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Deployment of efficient and cost-effective parking lots is a known bottleneck for the electric vehicles (EVs) sector. A comprehensive solution incorporating the requirements of all key stakeholders is required. Taking up the challenge, we propose a real-time EV smart parking lot model to attain the following objectives: (a) maximize the smart parking lot revenue by accommodating maximum number of EVs and (b) minimize the cost of power consumption by participating in a demand response (DR) program offered by the utility since it is a tool to answer and handle the electric power usage requirements for charging the EV in the smart parking lot. With a view to achieving these objectives, a linear programming-based binary\/cyclic (0\/1) optimization technique is developed for the EV charge scheduling process. It is difficult to solve the problems of binary optimization in real-time given that the complexity of the problem increases with the increase in number of EV. We deploy a simplified convex relaxation technique integrated with the linear programming solution to overcome this problem. The algorithm achieves: minimum power consumption cost of the EV smart parking lot; efficient utilization of available power; maximization of the number of the EV to be charged; and minimum impact on the EV battery lifecycle. DR participation provide benefits by offering time-based and incentive-based hourly intelligent charging schedules for the EV. A thorough comparison is drawn with existing variable charging rate-based techniques in order to demonstrate the comparative validity of our proposed technique. The simulation results show that even under no DR event, the proposed scheme results in 2.9% decrease in overall power consumption cost for a 500 EV scenario when compared to variable charging rate method. Moreover, in similar conditions, such as no DR event and for 500 EV arrived per day, there is a 2.8% increase in number of EV charged per day, 3.2% improvement in the average state-of-charge (SoC) of the EV, 12.47% reduction in the average time intervals required to achieve final SoC.<\/jats:p>","DOI":"10.3390\/s20174842","type":"journal-article","created":{"date-parts":[[2020,8,27]],"date-time":"2020-08-27T08:05:18Z","timestamp":1598515518000},"page":"4842","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["A Cost-Effective Electric Vehicle Intelligent Charge Scheduling Method for Commercial Smart Parking Lots Using a Simplified Convex Relaxation Technique"],"prefix":"10.3390","volume":"20","author":[{"given":"Muhammad","family":"Jawad","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, CUI Lahore Campus, Lahore 54000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0030-8959","authenticated-orcid":false,"given":"Muhammad Bilal","family":"Qureshi","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, CUI Abbottabad Campus, Abbottabad 22060, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3509-7968","authenticated-orcid":false,"given":"Sahibzada Muhammad","family":"Ali","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, CUI Abbottabad Campus, Abbottabad 22060, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5193-7707","authenticated-orcid":false,"given":"Noman","family":"Shabbir","sequence":"additional","affiliation":[{"name":"Department of Electrical Power Engineering &amp; Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Usman Shahid","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, CUI Abbottabad Campus, Abbottabad 22060, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Afnan","family":"Aloraini","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Qassim University, Al Qassim 1162, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9588-0052","authenticated-orcid":false,"given":"Raheel","family":"Nawaz","sequence":"additional","affiliation":[{"name":"Department of Operations Technology, Events and Technology Management, Manchester Metropolitan University, Manchester M15 6BH, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1016\/j.enpol.2012.06.009","article-title":"Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions","volume":"48","author":"Egbue","year":"2012","journal-title":"Energy Policy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1109\/TPWRS.2010.2057456","article-title":"Modeling of load demand due to EV battery charging in distribution systems","volume":"26","author":"Qian","year":"2011","journal-title":"IEEE Trans. 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