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Theses

Functional time series modeling and application to representation and analysis of multi-site electric load curves for energy management

Abstract : The analysis of electrical load curves collected by smart meters is a key step for many energy management tasks ranging from consumption forecasting and load monitoring to customers characterization and segmentation. In this context, researchers from EDF R&D are interested in extracting significant information from the daily electrical load curves in order to compare the consumption behaviors of different buildings. The strategy followed by the group which hosted my doctorate is to use physical and deterministic models based on information such as the room size, the insulating materials or weather data, or to extract hand-designed patterns from the electrical load curves based on the knowledge of experts. Given the growing amount of data collected, the interest of the group in statistical or data-driven methods has increased significantly in recent years. These approaches should provide new solutions capable of exploiting massive data without relying on expensive processing and expert knowledge. My work fits directly into this trend by proposing two modeling approaches: the first approach is based on functional time series and the second one is based on non-negative tensor factorization. This thesis is split into three main parts. In the first part, we present the industrial context and the practical objective of the thesis, as well as an exploratory analysis of the data and a discussion on the two modeling approaches proposed. In the second part, we follow the first modeling approach and provide a thorough study of the spectral theory for functional time series. Finally, the second modeling approach based on non-negative tensor factorization is presented in the third part.
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Submitted on : Monday, May 9, 2022 - 12:17:30 PM
Last modification on : Tuesday, May 10, 2022 - 3:09:58 AM

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  • HAL Id : tel-03662412, version 1

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Amaury Durand. Functional time series modeling and application to representation and analysis of multi-site electric load curves for energy management. Electric power. Institut Polytechnique de Paris, 2022. English. ⟨NNT : 2022IPPAT018⟩. ⟨tel-03662412⟩

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