University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > A Range of Methods for Electricity Consumption Forecasting

A Range of Methods for Electricity Consumption Forecasting

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Mustapha Amrani.

Stochastic Processes in Communication Sciences

For Electricit de France the forecast of electricity consumption is a fundamental problem which has been studied for the last twenty years. It is necessary to be able to provide customers and at the same time, optimize the production at different horizons of time. Results of operating models that use non linear regression or ARMAX methods are satisfying with 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.

For 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 often 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.

In 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 present the method used, we will show some practical results and we will discuss the benefits and drawbacks of it.(adaptive Kalmann, GAM , combining algoritms, KWF , Bayesian Methods, ..)

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity