期刊
ENERGY
卷 196, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.117058
关键词
Energy demand forecast; Regression analysis; TIMES model; MATLAB
资金
- Basilicata ESF Operative Programme Public Notice: Promozione della ricerca e dell'innovazione e sviluppo di relazioni con il sistema produttivo regionale D.D. [796/2013]
- Italian Ministry of Education, University and Research [84/Ric 2012]
- Cohesion Fund 2007-2013 of the Basilicata Regional authority
A reliable energy supply is fundamental to ensure energy security and support the mitigation of climate change by promoting the use of renewable sources and reducing carbon emissions. Energy system analysis provides a sound methodology to assess energy needs, allowing to investigate the energy system behavior and to individuate the optimal energy-technology configurations for the achievement of strategic energy and environmental policy targets. In this framework, the estimation of future trends of exogenous variables such as energy demand has a fundamental importance to obtain reliable and effective solutions, contributing remarkably to the accuracy of models' input data. This study illustrates an application of regression analysis to predict energy demand trends in end use sectors. The proposed procedure is applied to characterize statistically the relationships between population and gross domestic product (independent variables) and energy demands of Residential, Transport and Commercial in order to determine the energy demand trends over a long-term horizon. The effectiveness of linear and nonlinear regression models for energy demand forecasting has been validated by classical statistical tests. Energy demand projections have been tested as input data of the bottom-up TIMES model in two applications (the TIMES-Basilicata and TIMES-Italy models) confirming the validity of the forecasting approach. (C) 2020 Elsevier Ltd. All rights reserved.
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