کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6683534 501850 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Day-ahead hourly electricity load modeling by functional regression
ترجمه فارسی عنوان
مدل بار الکتریکی روزانه با استفاده از رگرسیون کاربردی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
چکیده انگلیسی
Short-term load forecasting is important for power system generation planning and operation. For unit commitment and dispatch processes to incorporate uncertainty, a short-term load model must not only provide accurate load predictions but also enable the generation of reasonable probabilistic scenarios or uncertainty sets. This paper proposes a temporal and weather conditional epi-splines based load model (TWE) using functional approximation. TWE models the dependence of load on time and weather separately by functional approximation using epi-splines, conditional on season and area, in each segment of similar weather days. Load data are transformed from various day types to a specified reference day type among similar weather days in the same season and area, in order to enrich the data for capturing the non-weather dependent load pattern. In an instance derived from an Independent System Operator in the U.S., TWE not only provides accurate hourly load prediction and narrow bands of prediction errors, but also yields serial correlations among forecast hourly load values within a day that are similar to those of actual hourly load.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Energy - Volume 170, 15 May 2016, Pages 455-465
نویسندگان
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