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Electricity load level detail in computational general equilibrium – Part I – Data and calibration

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  • Rodrigues, Renato
  • Linares, Pedro

Abstract

The growing importance of the electricity sector in many economies, and of energy and environmental policies, requires a detailed consideration of these sectors and policies in computable general equilibrium (CGE) models, including both technological and temporal aspects. This paper presents the first attempt to our knowledge at building temporal disaggregation into a CGE model, while keeping technological detail. This contribution is coupled with some methodological improvements over existing technology-rich CGE models. The model is able to account for the indirect effects characteristic of CGE models while also mimicking the detailed behavior of the electricity operation and investment present before only in bottom-up detailed models. The present paper is the first of two parts and focuses on the bottom-up top-down calibration methodology needed to build such a model. Part II will present the CGE model applied to the evaluation of an energy policy with temporal consequences.

Suggested Citation

  • Rodrigues, Renato & Linares, Pedro, 2014. "Electricity load level detail in computational general equilibrium – Part I – Data and calibration," Energy Economics, Elsevier, vol. 46(C), pages 258-266.
    • Handle: RePEc:eee:eneeco:v:46:y:2014:i:c:p:258-266
    DOI: 10.1016/j.eneco.2014.09.016
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    References listed on IDEAS

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    7. Rodrigues, Renato & Linares, Pedro, 2015. "Electricity load level detail in computational general equilibrium – part II – welfare impacts of a demand response program," Energy Economics, Elsevier, vol. 47(C), pages 52-67.
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    Cited by:

    1. Rodrigues, Renato & Linares, Pedro, 2015. "Electricity load level detail in computational general equilibrium – part II – welfare impacts of a demand response program," Energy Economics, Elsevier, vol. 47(C), pages 52-67.
    2. Pablo Pintos & Pedro Linares, 2016. "Assessing the EU ETS with an Integrated Model," Working Papers 01-2016, Economics for Energy.
    3. Jieting Yin & Qingyou Yan & Kaijie Lei & Tomas Baležentis & Dalia Streimikiene, 2019. "Economic and Efficiency Analysis of China Electricity Market Reform Using Computable General Equilibrium Model," Sustainability, MDPI, vol. 11(2), pages 1-22, January.
    4. Carlos Benavides & Luis Gonzales & Manuel Diaz & Rodrigo Fuentes & Gonzalo García & Rodrigo Palma-Behnke & Catalina Ravizza, 2015. "The Impact of a Carbon Tax on the Chilean Electricity Generation Sector," Energies, MDPI, vol. 8(4), pages 1-27, April.
    5. Nishiura, Osamu & Krey, Volker & Fricko, Oliver & van Ruijven, Bas & Fujimori, Shinichiro, 2024. "Integration of energy system and computable general equilibrium models: An approach complementing energy and economic representations for mitigation analysis," Energy, Elsevier, vol. 296(C).
    6. Xavier Labandeira & José M. Labeaga & Xiral López-Otero, 2019. "New Green Tax Reforms: Ex-Ante Assessments for Spain," Sustainability, MDPI, vol. 11(20), pages 1-25, October.
    7. Peng Ou & Ruting Huang & Xin Yao, 2016. "Economic Impacts of Power Shortage," Sustainability, MDPI, vol. 8(7), pages 1-21, July.

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    More about this item

    Keywords

    Computable general equilibrium (CGE); Calibration;

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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