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2018 | OriginalPaper | Chapter

Predicting Energy Demand in Spain and Compliance with the Greenhouse Gas Emissions Agreements

Authors : Diego J. Bodas-Sagi, José M. Labeaga

Published in: Modeling, Dynamics, Optimization and Bioeconomics III

Publisher: Springer International Publishing

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Abstract

This paper aims to predict energy demand in Spain for the year 2020 and analyzes whether this country will be able to meet the European Union’s greenhouse gas emission reduction commitment. To this purpose, we use climatic data and some variables to measure the economic activity in Spain. The simulated scenario considers that Spain will begin a process of economic recovery which will result in an increase in industrial activity with stable climatic conditions. Several techniques including Simple Linear Regression, Support Vector Machines or Deep Learning have been proposed to estimate and test the model. The EU agreements imply that by 2020 between 20 and 30% of the consumed energy will come from clean and renewable energy sources. The conclusions for this paper show that Spain may be on track to meet its commitments to Europe.

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Footnotes
1
We try another economic indicators but since the industry is the largest consumer of energy, we believe our parsimonious model can fit better and cover our prediction purposes.
 
2
We denote energy models as we cannot characterize them as demand or supply models. In any case, we acknowledge our interest in predicting energy consumption.
 
Literature
1.
Capros, P., Mantzos, L., Parousos, L., Tasios, N., Klaassen, G., Van Ierland, T.: Analysis of the EU policy package on climate change and renewables. Energy Pol. 39(3), 1476–1485 (2011)CrossRef
2.
3.
López, C.B., Carreras, A., Tafunell, X.: Estadísticas históricas de Espaa: siglos XIX-XX. (3). Fundación BBVA. Madrid (2005)
4.
Tiana, M.: El impacto de la crisis económica sobre la industria espaola. Boletín Económico. Banco de Espaa, Madrid (2012)
5.
6.
Ristinen, R.A., Kraushaar, J.J.: Energy and the Environment. Wiley-VCH, New York (1998)
7.
Labandeira, X., Labeaga, J.M., Lpez-Otero, X.: A meta-analysis on the price elasticity of energy demand. Energy Pol. 102, 549–568 (2017)CrossRef
8.
Wolpert, D.H., Macready, W.G.: No free lunch theorems for search. 10 Technical Report SFI-TR-95-02-010, Santa Fe Institute (1995)
9.
Team, R.C.: R: A language and environment for statistical computing (2013)
10.
James, G., Witten, D., Hastie, T., Tibshirani, R.: An Introduction to Statistical Learning, vol. 6. Springer, New York (2013)CrossRef
11.
12.
Hayashi, F.: Econometrics. Princeton University Press, Princeton (2000)MATH
13.
Neter, J., Kutner, M.H., Nachtsheim, C.J., Wasserman, W.: Applied Linear Statistical Models, vol. 4. Irwin, Chicago (1996)
14.
Cortes, C., Vapnik, V.: Support-vector networks. Mach. learn. 20(3), 273–297 (1995)MATH
15.
16.
Schapire, R.E., Freund, Y., Bartlett, P., Lee, W.S.: Boosting the margin: a new explanation for the effectiveness of voting methods. Ann. Stat. 26, 1651–1686 (1998)MathSciNetCrossRef
17.
Chapelle, O., Vapnik, V.: Model selection for support vector machines. In: NIPS, pp. 230–236 (1999)
18.
19.
Bergstra, J., Bengio, Y.: Random search for hyper-parameter optimization. J. Mach. Learn. Res. 13, 281–305 (2012)MathSciNetMATH
20.
Arel, I., Rose, D.C., Karnowski, T.P.: Deep machine learning-a new frontier in artificial intelligence research [research frontier]. IEEE Comput. Intell. Mag. 5(4), 13–18 (2010)CrossRef
21.
Zhang, G., Patuwo, B.E., Hu, M.Y.: Forecasting with artificial neural networks: the state of the art. Int. J. Forecast. 14(1), 35–62 (1998)CrossRef
22.
Deaton, A., Muellbauer, J.: Economics and Consumer Behavior. Cambridge University Press, Cambridge (1980)CrossRef
Metadata
Title
Predicting Energy Demand in Spain and Compliance with the Greenhouse Gas Emissions Agreements
Authors
Diego J. Bodas-Sagi
José M. Labeaga
Copyright Year
2018
Book
Modeling, Dynamics, Optimization and Bioeconomics III

Print ISBN: 978-3-319-74085-0

Electronic ISBN: 978-3-319-74086-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-74086-7_5

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