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SUMMARY:A Range of Methods for Electricity Consumption Forecasting - Bross
 at\, X (EDF\, France)
DTSTART:20130422T130000Z
DTEND:20130422T133000Z
UID:TALK44723@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:For Electricit de France the forecast of electricity consumpti
 on is a fundamental problem which has been studied for the last twenty yea
 rs. It is necessary to be able to provide customers and at the same time\,
  optimize the production at different horizons of time. Results of operati
 ng models that use non linear regression or ARMAX methods are satisfying w
 ith a current accuracy of 1.5% for the forecast of the following day. But\
 , they have to be continually fitted to be adapted to some very difficult 
 periods of time and to the change of consumption.\n\nFor a few years\, due
  to the new competitive environment\, the electrical load curve has become
  less regular. Its shape and level which depended essentially on climatic 
 exogenous variables has become more affected by economical and ecological 
 variables. The data is not always available and the time series used are o
 ften short. So\, we have tried to apply the following alternative methods 
 to answer to problems like adaptivity\, nonstationarity\, parsimony\, lack
  of data\, necessity of forecast interval.\n\nIn this presentation we will
  display the operating models and those different classes of models which 
 we applied to electrical consumption forecast. For each model we will pres
 ent the method used\, we will show some practical results and we will disc
 uss the benefits and drawbacks of it.(adaptive Kalmann\, GAM\, combining a
 lgoritms\, KWF\, Bayesian Methods\, ..)\n\n
LOCATION:Seminar Room 1\, Newton Institute
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