Electricity consumption forecasting in Italy using linear regression models

被引:399
作者
Bianco, Vincenzo [1 ]
Manca, Oronzio [1 ]
Nardini, Sergio [1 ]
机构
[1] Univ Naples 2, DIAM, I-81031 Aversa, CE, Italy
关键词
Electricity consumption; Forecasting; Elasticity; Linear regression; ENERGY-CONSUMPTION; OECD-COUNTRIES; DEMAND; COINTEGRATION; VARIABLES; TURKEY; SECTOR;
D O I
10.1016/j.energy.2009.06.034
中图分类号
O414.1 [热力学];
学科分类号
摘要
The influence of economic and demographic variables on the annual electricity consumption in Italy has been investigated with the intention to develop a long-term consumption forecasting model. The time period considered for the historical data is from 1970 to 2007. Different regression models were developed, using historical electricity consumption, gross domestic product (GDP), gross domestic product per capita (GDP per capita) and population. A first part of the paper considers the estimation of GDP, price and GDP per capita elasticities of domestic and non-domestic electricity consumption. The domestic and non-domestic short run price elasticities are found to be both approximately equal to -0.06, while long run elasticities are equal to -0.24 and -0.09, respectively. On the contrary, the elasticities of GDP and GDP per capita present higher values. In the second part of the paper, different regression models, based on co-integrated or stationary data, are presented. Different statistical tests are employed to check the validity of the proposed models. A comparison with national forecasts, based on complex econometric models, such as Markal-Time, was performed, showing that the developed regressions are congruent with the official projections, with deviations of +/-1% for the best case and +/-11% for the worst. These deviations are to be considered acceptable in relation to the time span taken into account. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1413 / 1421
页数:9
相关论文
共 30 条
[1]  
AbdelAal RE, 1997, ENERGY, V22, P911, DOI 10.1016/S0360-5442(97)00019-4
[2]   Electricity consumption and associated GHG emissions of the Jordanian industrial sector: Empirical analysis and future projection [J].
Al-Ghandoor, A. ;
Al-Hinti, I. ;
Jaber, J. O. ;
Sawalha, S. A. .
ENERGY POLICY, 2008, 36 (01) :258-267
[3]   Electricity demand for Sri lanka: A time series analysis [J].
Amarawickrama, Himanshu A. ;
Hunt, Lester C. .
ENERGY, 2008, 33 (05) :724-739
[4]   Demand elasticity increase for reducing social welfare losses due to transfer capacity restriction: A test case on Italian cross-border imports [J].
Bruno, S ;
De Benedictis, M ;
La Scala, M ;
Wangensteen, I .
ELECTRIC POWER SYSTEMS RESEARCH, 2006, 76 (6-7) :557-566
[5]  
CESI, 2005, FOR EL DEM YEARS 201
[6]   Economic variables and electricity consumption in Northern Cyprus [J].
Egelioglu, F ;
Mohamad, AA ;
Guven, H .
ENERGY, 2001, 26 (04) :355-362
[7]   COINTEGRATION AND ERROR CORRECTION - REPRESENTATION, ESTIMATION, AND TESTING [J].
ENGLE, RF ;
GRANGER, CWJ .
ECONOMETRICA, 1987, 55 (02) :251-276
[8]   Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey [J].
Erdogdu, Erkan .
ENERGY POLICY, 2007, 35 (02) :1129-1146
[9]  
*EUR, 2008, EN STAT PRIC 1985 20
[10]  
FERRARI A, 2003, UTILITIES POL, V13, P247