Title
Local Short and Middle Term Electricity Load Forecasting With Semi-Parametric Additive Models.
Abstract
Electricity load forecasting faces rising challenges due to the advent of innovating technologies such as smart grids, electric cars and renewable energy production. For distribution network managers, a good knowledge of the future electricity consumption stands as a central point for the reliability of the network and investment strategies. In this paper, we suggest a semi-parametric approach based on generalized additive models theory to model electrical load over more than 2200 substations of the French distribution network, and this at both short and middle term horizons. These generalized additive models estimate the relationship between load and the explanatory variables: temperatures, calendar variables, etc. This methodology has been applied with good results on the French grid. In addition, we highlight the fact that the estimated functions describing the relations between demand and the driving variables are easily interpretable, and that a good temperature prediction is important.
Year
DOI
Venue
2014
10.1109/TSG.2013.2278425
IEEE Trans. Smart Grid
Keywords
Field
DocType
load forecasting,power consumption,power distribution planning,power distribution reliability,power grids,statistical analysis,French distribution network,future electricity consumption,investment strategy,local short term electricity load forecasting,middle term electricity load forecasting,network reliability,power grid,semiparametric additive models,Electricity networks,Load forecasting,generalized additive model,semi-parametric model,time series
Econometrics,Economics,Smart grid,Load balancing (electrical power),Electrical load,Additive model,Electricity,Probabilistic forecasting,Generalized additive model,Grid
Journal
Volume
Issue
ISSN
5
1
1949-3053
Citations 
PageRank 
References 
17
1.16
2
Authors
3
Name
Order
Citations
PageRank
Yannig Goude1445.38
Raphael Nedellec2171.50
Nicolas Kong3171.16