Key performance‐cost tradeoffs in smart electric vehicle charging with distributed generation

Abstract

Growing penetration of Electric Vehicles (EV) and Distributed Generation (DG) is driving sharper peaks in demand and supply, which, if poorly managed, manifest as over- or undervoltage and disrupt grid service quality. Smart charging schemes reschedule EV charging load according to factors such as grid stability, price signals, etc. It remains unclear how to do this while meeting the diverging needs and expectations of multiple concerned participants. This paper proposes two smart charging schemes for secondary voltage control in the distribution network and analyses performance-cost trade-offs relating to key players in the Smart Grid. To support these schemes, a distributed communications architecture is designed that jointly minimises traffic burden, computation load and investment in Information and Communications Technology (ICT) hardware. Scheme I (Smart Curtailment), curtails load and DG for peak shaving. Scheme II (Smart Correction) optimises cost-efficiency for subscribing users by maximising power transfer during off-peak hours or when renewable energy is high. Performance of both schemes is consolidated statistically under almost 6 months of practical input profiles. Dramatic improvements in EV & DG capacity are demonstrated and key performance-cost trade-offs relating to Voltage Control, Peak Shaving, User Inconvenience, CO2 Emissions and ICT Deployment Cost are identified.