Using Complex Surveys to Estimate the L1‐Median of a Functional Variable: Application to Electricity Load Curves |
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Authors: | Mohamed Chaouch Camelia Goga |
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Affiliation: | 1. Département ICAME, EDF Recherche & Développement, Clamart, France E‐mail: mohamed.chaouch@edf.fr;2. Institut de Mathématiques de Bourgogne, Université de Bourgogne, Dijon, France E‐mail: camelia.goga@u‐bourgogne.fr |
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Abstract: | Mean profiles are widely used as indicators of the electricity consumption habits of customers. Currently, in Électricité De France (EDF), class load profiles are estimated using point‐wise mean profiles. Unfortunately, it is well known that the mean is highly sensitive to the presence of outliers, such as one or more consumers with unusually high‐levels of consumption. In this paper, we propose an alternative to the mean profile: the L 1 ‐ median profile which is more robust. When dealing with large data sets of functional data (load curves for example), survey sampling approaches are useful for estimating the median profile avoiding storing the whole data. We propose here several sampling strategies and estimators to estimate the median trajectory. A comparison between them is illustrated by means of a test population. We develop a stratification based on the linearized variable which substantially improves the accuracy of the estimator compared to simple random sampling without replacement. We suggest also an improved estimator that takes into account auxiliary information. Some potential areas for future research are also highlighted. |
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Keywords: | Horvitz‐Thompson estimator k‐means algorithm post‐stratification stratified sampling substitution estimator variance estimation |
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