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Integration of Power Generation Capacity Expansion in an Applied General Equilibrium Model

Author

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  • Gauthier de Maere d'Aertrycke

    (GDF-SUEZ, Center of Expertise in Economic Modelling and Studies, Fondazione Eni Enrico Mattei (FEEM) and Euro-Mediterranean Center on Climate Change (CMCC))

  • Olivier Durand-Lasserve

    (GDF-SUEZ, Center of Expertise in Economic Modelling and Studies)

  • Marco Schudel

    (GDF-SUEZ, Center of Expertise in Economic Modelling and Studies)

Abstract

This paper presents a version of a hybrid (top-down bottom-up), multi-region multi-period forward looking applied general equilibrium model, MERGE, that includes a capacity expansion submodel of the electricity sector with demand represented by various time segments. This model is solved numerically using the decomposition method proposed by Bohringer and Rutherford (2006). In the decomposition, the bottom-up (energy) submodel of MERGE is embedded in a quadratically constrained program (QCP) that maximizes a welfare function calibrated on a linear approximation, around a benchmark point, of aggregated energy and capital demand . This latter is provided by constraining energy supply in a nonlinear programming problem (NLP) that essentially contains the MERGE top-down (macro) submodel. The method is illustrated with a simulation that provides projections of load duration curves and hours of activity of various electricity technologies.

Suggested Citation

  • Gauthier de Maere d'Aertrycke & Olivier Durand-Lasserve & Marco Schudel, 2014. "Integration of Power Generation Capacity Expansion in an Applied General Equilibrium Model," Working Papers 2014.71, Fondazione Eni Enrico Mattei.
    • Handle: RePEc:fem:femwpa:2014.71
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    References listed on IDEAS

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    1. Kenneth C. Hoffman & Dale W. Jorgenson, 1977. "Economic and Technological Models for Evaluation of Energy Policy," Bell Journal of Economics, The RAND Corporation, vol. 8(2), pages 444-466, Autumn.
    2. Sebastian Rausch & Thomas Rutherford, 2010. "Computation of Equilibria in OLG Models with Many Heterogeneous Households," Computational Economics, Springer;Society for Computational Economics, vol. 36(2), pages 171-189, August.
    3. Schafer, Andreas & Jacoby, Henry D., 2005. "Technology detail in a multisector CGE model: transport under climate policy," Energy Economics, Elsevier, vol. 27(1), pages 1-24, January.
    4. Manne, Alan & Mendelsohn, Robert & Richels, Richard, 1995. "MERGE : A model for evaluating regional and global effects of GHG reduction policies," Energy Policy, Elsevier, vol. 23(1), pages 17-34, January.
    5. DURAND-LASSERVE, Olivier & Pierru , Axel & SMEERS, Yves, 2012. "Sensitivity of policy simulation to benchmark scenarios in CGE models: illustration with carbon leakage," LIDAM Discussion Papers CORE 2012063, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Messner, Sabine & Schrattenholzer, Leo, 2000. "MESSAGE–MACRO: linking an energy supply model with a macroeconomic module and solving it iteratively," Energy, Elsevier, vol. 25(3), pages 267-282.
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    Cited by:

    1. Andersen, Kristoffer S. & Termansen, Lars B. & Gargiulo, Maurizio & Ó Gallachóirc, Brian P., 2019. "Bridging the gap using energy services: Demonstrating a novel framework for soft linking top-down and bottom-up models," Energy, Elsevier, vol. 169(C), pages 277-293.
    2. Durand-Lasserve, Olivier & Almutairi, Hossa & Aljarboua, Abdullah & Pierru, Axel & Pradhan, Shreekar & Murphy, Frederic, 2023. "Hard-linking a top-down economic model with a bottom-up energy system for an oil-exporting country with price controls," Energy, Elsevier, vol. 266(C).

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