Control of EV Charging Points for Thermal and Voltage Management of LV Networks

Abstract

High penetrations of domestic electric vehicles (EVs) in U.K. low voltage (LV) networks may result in significant technical problems. This paper proposes an implementable, centralized control algorithm, currently being trialed in 9 U.K. residential LV networks, that uses limited information to manage EV charging points to mitigate these technical problems. Two real U.K. LV networks are used to quantify the potential impacts of different EV penetration levels and to demonstrate the effectiveness of the control algorithm (using different control cycles) for simultaneous thermal and voltage management. Monte Carlo simulations (adopting 1-min resolution data) are undertaken to cater for domestic and EV demand uncertainties. Results for these LV networks show that problems may occur for EV penetrations higher than 20%. More importantly, they highlight that even for a 100% penetration and control cycles of up to 10 min, the control algorithm successfully mitigates problems on the examined LV networks. Crucially, to determine effects on the comfort of EV users, a metric is introduced and discussed. The results of different control settings are presented to analyze potential adaptations of the control strategy. Finally, a comparison with an optimization framework highlights that the proposed algorithm is as effective while using limited information.Index Terms-Electric vehicles, low voltage networks, real-time control, thermal management, voltage management.

Quantitive analysis of electric vehicle flexibility: A data-driven approach

“…Brady et al [14] use a probabilistic charging module to translate the travel patterns of EVs into the respective power demand of 95 the vehicles. Quiròs-Tortòs et al [15] and Navarro-Espinosa et al [16] use the probability distribution of start charging time and energy demanded during a connection of charging sessions in a one-year EV trial in Ireland to obtain the EV load demand and assess their impact in the low voltage distribution grid.…”

“…That extra capacity would only be required to meet the increased peak demand 15 and therefore is used very infrequently [1]. Integration of information technology into the power grid (in the smart grid paradigm) alleviates this challenge by enabling the exploitation of demand side flexibility to reshape the consumption to meet the supply or network constraints (i.e., by flattening demand or by balancing against renewable generation).…”

Multitime scale coordinated scheduling for electric vehicles considering photovoltaic/wind/battery generation in microgrid

“…According to statistical data, a car's daily parking rate is typically above 90%. 9 To address this issue, an effective scheduling strategy for EVs can be adapted by means of a vehicle-to-grid (V2G) system to enhance the ability of the power system to accept intermittent energy (wind and PV power) and improve the economy and security of the system operations. 5 Because wind and photovoltaic (PV) energy sources exhibit strong randomness, the output power of an individual wind or PV power generation system is very unstable and cannot be controlled in accordance with typical requirements.…”

“…7,8 However, because of the temporal and spatial randomness of the charging and discharging of EV, the large-scale adoption of EVs in a power grid will also introduce great uncertainty into the safe and economic operations of the whole system. 9 To address this issue, an effective scheduling strategy for EVs can be adapted by means of a vehicle-to-grid (V2G) system to enhance the ability of the power system to accept intermittent energy (wind and PV power) and improve the economy and security of the system operations. [10][11][12] At present, some scholars have studied the coordinated scheduling of the charging loads of EVs and renewable energy sources.…”

Risk Evaluation of Distribution Networks Considering Residential Load Forecasting with Stochastic Modeling of Electric Vehicles

“…The study concluded that peak load factor is substantially increased by applying level 2 power charging. Unbalancing issues resulted from the massive single‐phase charging of EVs are not considered for assessment of realistic EV charging model in the aforementioned studies . Moreover, problems associated with added EV charging demand with location are not analyzed in terms of customers with voltage issues.…”