دانلود مقاله ISI انگلیسی شماره 142878
ترجمه فارسی عنوان مقاله

پیش بینی تقاضای برق وسایل نقلیه الکتریکی با تجزیه و تحلیل الگوهای شارژ مصرف کننده

عنوان انگلیسی
Forecasting electricity demand of electric vehicles by analyzing consumers charging patterns
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
142878 2018 16 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Transportation Research Part D: Transport and Environment, Volume 62, July 2018, Pages 64-79

ترجمه کلمات کلیدی
الگوی شارژ خودرو الکتریکی، تقاضای برق، تجهیزات تامین برق الکتریکی، ترجیح مصرف کننده، آزمایش انتخابی گسسته،
کلمات کلیدی انگلیسی
Electric vehicle charging pattern; Electricity demand; Electric vehicle supply equipment; Consumer preference; Discrete choice experiment;
پیش نمایش مقاله
پیش نمایش مقاله  پیش بینی تقاضای برق وسایل نقلیه الکتریکی با تجزیه و تحلیل الگوهای شارژ مصرف کننده

چکیده انگلیسی

The spread of electric vehicles (EVs) and their increasing demand for electricity has placed a greater burden on electricity generation and the power grid. In particular, the problem of whether to expand the electricity power stations and distribution facilities due to the construction of EV charging stations is emerging as an immediate issue. To effectively meet the demand for additional electricity while ensuring the stability of the power grid, there is a need to accurately predict the charging demands for EVs. Therefore, this study estimates the changes in electricity charging demand based on consumer preferences for EVs, charging time of day, and types of electric vehicle supply equipment (EVSE) and elucidates the matters to be considered for constructing EV infrastructure. The results show that consumers mainly preferred charging during the evening. However, when we considered different types of EVSEs (public and private) in the analysis, people preferred to charge at public EVSEs during the day. During peak load time, people tended to prefer charging using fast public EVSEs, which shows that consumers considered the tradeoffs between the full charge time and the price for charging. Based on these findings, this study provides key political implications for policy makers to consider in taking preemptive measures to adjust the electricity supply infrastructure.