Change Detection in Electricity Consumption Patterns Utilizing Adaptive Information Theoretic Algorithms
نویسندگان
چکیده
The high-resolution data on electricity consumption, recorded by smart meters at customers' premises, are valuable sources of operational information and consumption patterns. In addition, characterization plays an undeniable role in the implementation demand response (DR) programs, as any changes patterns could affect DR programs. Therefore, accurate algorithm for detecting is very useful not only but also other fields, such load forecasting peak shaving. This article proposes a reliable procedure For this reason, adaptive introduced to improve clustering quality determining optimum number clusters, using locally weighted entropy-based segmentation. Moreover, considering records different time slots features, another feature selection based mutual concept. proposed method evaluated applying real dataset provided Irish Social Science Data Archive. results corroborate efficiency procedure.
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ژورنال
عنوان ژورنال: IEEE Systems Journal
سال: 2021
ISSN: ['1932-8184', '1937-9234', '2373-7816']
DOI: https://doi.org/10.1109/jsyst.2020.3011313