Linear Regression Models to Forecast Electricity Consumption in Italy

被引:65
|
作者
Bianco, V. [1 ]
Manca, O. [1 ]
Nardini, S. [1 ]
机构
[1] Univ Naples 2, DIAM, I-81031 Aversa, CE, Italy
关键词
electricity consumption; energy; forecasting; Italian electricity demand; linear regression; VARIABLES;
D O I
10.1080/15567240903289549
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The influence of economic and demographic variables on the annual electricity consumption in Italy has been investigated in order to develop a simple and data light electricity consumption forecasting model, to be used as part of more complex planning tools. The time period considered for the historical data is from 1970-2007. Multiple and single regression models are developed using historical electricity consumption, gross domestic product (GDP), GDP per capita, and population. Annual electricity consumption was strongly related to the selected variables, with adjusted regression coefficients, adj. R-2, equal to 0.990 for residential consumption, 0.961 for non-residential consumption, and 0.981 for total consumption. Comparisons with national forecasts showed that the developed regressions are congruent with the official projections, with +/- 5% error considered acceptable in relation to the considered time span.
引用
下载
收藏
页码:86 / 93
页数:8
相关论文
共 50 条
  • [1] Electricity consumption forecasting in Italy using linear regression models
    Bianco, Vincenzo
    Manca, Oronzio
    Nardini, Sergio
    ENERGY, 2009, 34 (09) : 1413 - 1421
  • [2] Electricity Consumption Forecast of Hunan Province Using Combined Model Based on Multivariate Linear Regression and BP Neural Network
    Li, Yan
    Dai, Shuyu
    Niu, Dongxiao
    PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON MECHATRONICS, COMPUTER AND EDUCATION INFORMATIONIZATION (MCEI 2017), 2017, 75 : 651 - 655
  • [3] Dynamic Regression Prediction Models for Customer Specific Electricity Consumption
    Shaqiri, Fatlinda
    Korn, Ralf
    Truong, Hong-Phuc
    ELECTRICITY, 2023, 4 (02): : 185 - 215
  • [4] Forecast on Vietnam Electricity Consumption to 2030
    Nguyen Hoang Minh Vu
    Nguyen Truong Phuc Khanh
    Vo Viet Cuong
    Phan Thi Thanh Binh
    2017 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (ICELTICS), 2017, : 72 - 77
  • [5] Forecast on 2030 Vietnam Electricity Consumption
    Nguyen, Vu H. M.
    Nguyen, Khanh T. P.
    Vo, Cuong V.
    Phan, Binh T. T.
    ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH, 2018, 8 (03) : 2869 - 2874
  • [6] Functional linear regression with functional response: Application to prediction of electricity consumption
    Antoch, Jaromir
    Prchal, Lubos
    De Rosa, Maria Rosaria
    Sarda, Pascal
    FUNCTIONAL AND OPERATORIAL STATISTICS, 2008, : 23 - +
  • [7] Electricity consumption prediction with functional linear regression using spline estimators
    Antoch, Jaromir
    Prchal, Lubos
    De Rosa, Maria Rosaria
    Sarda, Pascal
    JOURNAL OF APPLIED STATISTICS, 2010, 37 (12) : 2027 - 2041
  • [8] Forecast of electricity consumption in the Cameroonian residential sector by Grey and vector autoregressive models
    Guefano, Serge
    Tamba, Jean Gaston
    Azong, Tchitile Emmanuel Wilfried
    Monkam, Louis
    ENERGY, 2021, 214
  • [9] Forecast of fruit impact bruising by linear, non-linear and logistic regression models
    Menesatti, P
    Paglia, G
    Solaini, S
    Zanella, A
    Stainer, R
    PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON COMPUTER MODELLING IN FRUIT RESEARCH AND ORCHARD MANAGEMENT, 2002, (584): : 153 - 162
  • [10] Prediction of Building Electricity Consumption Based on Joinpoint-Multiple Linear Regression
    Yang, Hao
    Ran, Maoyu
    Zhuang, Chaoqun
    ENERGIES, 2022, 15 (22)