Optimized clusters for disaggregated electricity load forecasting

To account for the variation of EDF’s (the French electrical company) portfolio following the liberalization of the electrical market, it is essential to disaggregate the global load curve. The idea is to disaggregate the global signal in such a way that the sum of disaggregated forecasts significantly improves the prediction of the whole global signal. The strategy is to optimize, a preliminary clustering of individual load curves with respect to a predictability index. The optimized clustering procedure is controlled by a forecasting performance via a cross-prediction dissimilarity index. It can be assimilated to a discrete gradient type algorithm. Key-Words

Determination, guidee par les connaissances, d'une loi de pilotage pour un lanceur spatial : analyse de ces connaissances et construction d'un systeme expert

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

PM10 forecasting using mixture linear regression models

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PM10 forecasting using mixture linear regression models

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Mixture of linear regression models for short term PM10 forecasting in Haute Normandie (France)

Mixture of linear regression models is used for the short-term statistical forecasting of the daily mean PM10 concentration. Hourly concentrations of PM10 have been measured in three cities in Haute-Normandie (France): Rouen, Le Havre and Dieppe. The Haute-Normandie region is located at northwest of Paris, near the south side of Manche sea and is heavily industrialized. We consider six monitoring stations reflecting the diversity of situations: urban background, traffic, rural and industrial stations. We have focused our attention on recent data from 2007 to 2011. We forecast the daily mean PM10 concentration by modeling it as a mixture of linear regression models involving meteorological predictors and the average concentration measured on the previous day. The values of observed meteorological variables are used for fitting the models but the corresponding predictions are considered for the test data, leading to realistic evaluations of forecasting performances, which are calculated through a leave-one-out scheme on the four years. We discuss in this paper several methodological issues including estimation schemes, introduction of the deterministic predictions of meteorological models and how to handle the forecasting at various horizons from some hours to one day ahead

PM10 forecasting using mixture linear regression models

International audienceno abstrac

Optimized Clusters for Disaggregated Electricity Load Forecasting

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Eléments de comparaison de prévisions statistiques des pics d'ozone

International audienc