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EV Overnight Charging Strategy in Residential Sector: Case of Winter Season in Quebec

Alben Cardenas, Cristina Guzmán, Wilmar H. Martinez · 2021 · 17 citationsRead the paper

Electric Vehicle (EV) technologies offer a leading-edge solution for clean transportation and have evolved substantially in recent years. The growing market and policies of governments predict EV massive penetration shortly; however, their large deployment faces some resistances such as the high prices compared to Internal Combustion Engine (ICE) cars, the required infrastructure, the liability for novelty and standardisation. During winter periods of cold countries, since the use of heating systems increases, the peak power may produce stress to the grid. This fact, combined with EVs high penetration, during charging periods inside of high consumption hours might overload the network, becoming a threat to its stability. This article presents a framework to evaluate load shifting strategies to reschedule the EV charging to lower grid load periods. The undesirable “rebound” effect of load shifting strategies is confirmed, leading us to our EV local overnight charging strategy (EV-ONCS). Our strategy combines the forecast of residential demand using probabilistic distribution from historical consumption, prediction of the EV expected availability to charge and the charging strategy itself. EV-ONCS avoids demand rebound of classic methods and allows a peak-to-average ratio reduction demonstrating the relief for the grid with very low implementation cost.

What the full text shows

Theory or simulation

The EV-ONCS strategy reduces the peak-to-average ratio (PAR) of aggregated power demand compared to the baseline (no EV) scenario. — 16% reduction in cases 1, 2, and 3; 21% reduction in case 4 (Residential sector during winter in Quebec (January 20-25, 2020))
Classic load-shift strategies fail to improve grid balance and can create a 'rebound' effect where peak power is simply relocated. — PAR increased by 10% to 53% over baseline in cases 2, 3, and 4 (High EV penetration and low outdoor temperatures)
Integration of EVs without management strategies significantly increases peak demand. — PAR increased by 16% to 53% over baseline across four scenarios (Residential sector during winter in Quebec)

Setup: Simulation of residential power demand in Quebec during January 2020, testing four scenarios of EV fleet composition (varying battery size and charging power).
How: The researchers developed a simulation framework using Gaussian-core kernel models to forecast residential demand and EV availability. They compared a baseline, a standard load-shift strategy, and a proposed local overnight charging strategy (EV-ONCS).
Limitations: Requires chargers with bidirectional and modulated power capabilities. · Emission reduction results are specific to Quebec's hydropower-dominant grid and require re-evaluation for other jurisdictions.

Summarized by Gemma 4 from the open-access full text · 8 Oct 2026. Read it