Bi-Directional Nano Grid Design for Organizations with Plug-In Electric Vehicle Charging at Workplace

Jawad, Muhammad; Qureshi, Muhammad Bilal; Nadeem, Ahsan; Ali, Sahibzada Muhammad; Shabbir, Noman; Rafiq, Muhammad

doi:10.1109/eit.2018.8500191

Cited by 4 publications

(1 citation statement)

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“…The electrical characteristics of recently manufactured EV and their usage in percentage in the simulations are given in Table 2 [ 32 ]. Moreover, the level 2 battery charging mechanism is adopted in the simulations [ 33 ]. The initial SoC of an arrived EV is considered as being equally distributed in the interval [0.1–0.4], whereas charging efficiency

of each EV is set to be 0.9 [ 34 ].…”

Section: Resultsmentioning

confidence: 99%

A Cost-Effective Electric Vehicle Intelligent Charge Scheduling Method for Commercial Smart Parking Lots Using a Simplified Convex Relaxation Technique

Jawad¹,

Qureshi

Ali

et al. 2020

Sensors

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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.

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of each EV is set to be 0.9 [ 34 ].…”

Section: Resultsmentioning

confidence: 99%