2026 Volume 146 Issue 9 Pages 595-602
As the adoption of renewable energy accelerates, utilizing surplus photovoltaic (PV) power for electric vehicle (EV) charging has attracted growing attention. However, EV user charging behavior involves significant uncertainties—such as driving distance and plug-in probability—that cannot be accurately captured by average-based models, leading to potential misestimation of PV surplus absorption. This study constructs a probabilistic framework that models EV charging behavior using data and Monte Carlo simulations, evaluating the PV surplus mitigation rate as a probability density function (PDF). Furthermore, it analyzes how variations in charging timing and user behavior affect the stability of PV absorption, and derives indicators such as the required number of EVs and their standard deviation. These insights contribute to the strategic design of realistic and scalable solutions for social implementation.
The transactions of the Institute of Electrical Engineers of Japan.B
The Journal of the Institute of Electrical Engineers of Japan