کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
704682 1460872 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison and clustering analysis of the daily electrical load in eight European countries
ترجمه فارسی عنوان
مقایسه و تجزیه و تحلیل خوشه ای بار الکتریکی روزانه در هشت کشور اروپایی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
چکیده انگلیسی
This paper illustrates and compares the ability of several clustering algorithms to correctly associate a given aggregate daily electrical load curve with its corresponding day of the week. In particular, popular clustering algorithms like the Fuzzy c-Means, Spectral Clustering and Expectation Maximization are compared, and it is shown that the best results are obtained if the daily data are compressed with respect to a single feature, namely the so-called “Morning Slope”. Such a feature-based clustering appears to outperform the clustering results obtained upon using other classic features, and also with respect to using other conventional compression methods, such as the Principal Component Analysis, in all the examined European countries. This result is particularly interesting, as this feature provides a direct physical interpretation that can be used to obtain insights on the structure of the daily load profiles.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Electric Power Systems Research - Volume 141, December 2016, Pages 114-123
نویسندگان
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