An Electric Vehicle Charge Scheduling Approach Suited to Local and Supplying Distribution Transformers

• Published in: Energies (Basel) 2020-07, Vol.13 (13), p.3486
• Main Authors: Kurniawan, Teguh, Baguley, Craig A., Madawala, Udaya K., Suwarno, Suwarno, Hariyanto, Nanang, Adianto, Yuana
• Format: Article
• Language: English
• Subjects: Automobiles; Case studies; charge scheduling; Computer simulation; Data processing; distribution transformer; Driver behavior; Electric vehicles; Embedded systems; Fuzzy logic; Fuzzy systems; Load; Load distribution; Mitigation; Monte Carlo simulation; Peak load; Residential areas; Smart buildings; Stress concentration; Voltage; Voltage stability
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en13133486

Distribution networks with high electric vehicle (EV) penetration levels can experience transformer overloading and voltage instability issues. A charge scheduling approach is proposed to mitigate against these issues that suits smart home settings in residential areas. It comprises measurement systems located at distribution transformers that communicate directly with fuzzy logic controller (FLC) systems embedded within EV supply equipment (EVSE). This realizes a reduction in data processing requirements compared to more centralized control approaches, which is advantageous for distribution networks with large numbers of transformers and EV scheduling requests. A case study employing the proposed approach is presented. Realistic driver behavior patterns, EV types, and multivariate probabilistic modeling were used to estimate EV charging demands, daily travel mileage, and plug-in times. A Monte Carlo simulation approach was developed to obtain EV charging loads. The effectiveness of mitigation in terms of reducing distribution transformer peak load levels and losses, as well as improving voltage stability is demonstrated for a distribution network in Jakarta, Indonesia.