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Long-Term Electricity Investments Accounting for Demand and Supply Side Flexibility


  • Marañón-Ledesma, Hector
  • Tomasgard, Asgeir


Short-term Electricity Demand Response (DR) is an emerging technology in Europe's Electricity markets that will introduce a new degree of flexibility. The objective of this work is to analyze to what extent the untapped DR potential can facilitate an optimal transition to an European low emission power system. The benefits of DR consists of a reduction in peak load consumption, which leads to reduction in capacity investments, production and consumption savings, reduced congestion phases, reliable integration of intermittent renewable resources and supply and demand flexibility. The capabilities of DR are studied in the European Model for Power Investment with (High Shares of) Renewable Energy (EMPIRE), which is an electricity sector model with a time span of 30 years ending in 2050. The model is two-stage stochastic that includes uncertainty at the operational level and energy economics dynamics at a strategic level. The main contribution of this article is designing the investment-operation DR module within the EMPIRE framework. It models several classes of shiftable and curtailable loads in residential, commercial and industrial sectors, including flexibility periods, operational costs and endogenous DR investments, for 31 European countries. The results show that DR capacity substitutes partially flexible supply side capacity from peak gas plants and battery storage, in addition to enabling more solar PV production.

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  • Marañón-Ledesma, Hector & Tomasgard, Asgeir, 2019. "Long-Term Electricity Investments Accounting for Demand and Supply Side Flexibility," MPRA Paper 93341, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:93341

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    References listed on IDEAS

    1. Zerrahn, Alexander & Schill, Wolf-Peter, 2015. "On the representation of demand-side management in power system models," Energy, Elsevier, vol. 84(C), pages 840-845.
    2. Wiese, Frauke & Schlecht, Ingmar & Bunke, Wolf-Dieter & Gerbaulet, Clemens & Hirth, Lion & Jahn, Martin & Kunz, Friedrich & Lorenz, Casimir & Mühlenpfordt, Jonathan & Reimann, Juliane & Schill, Wolf-P, 2019. "Open Power System Data – Frictionless data for electricity system modelling," Applied Energy, Elsevier, vol. 236(C), pages 401-409.
    3. Ottesen, Stig Odegaard & Tomasgard, Asgeir, 2015. "A stochastic model for scheduling energy flexibility in buildings," Energy, Elsevier, vol. 88(C), pages 364-376.
    4. Müller, F.L. & Jansen, B., 2019. "Large-scale demonstration of precise demand response provided by residential heat pumps," Applied Energy, Elsevier, vol. 239(C), pages 836-845.
    5. Seljom, Pernille & Lindberg, Karen Byskov & Tomasgard, Asgeir & Doorman, Gerard & Sartori, Igor, 2017. "The impact of Zero Energy Buildings on the Scandinavian energy system," Energy, Elsevier, vol. 118(C), pages 284-296.
    6. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    7. Vallés, Mercedes & Bello, Antonio & Reneses, Javier & Frías, Pablo, 2018. "Probabilistic characterization of electricity consumer responsiveness to economic incentives," Applied Energy, Elsevier, vol. 216(C), pages 296-310.
    8. Pfenninger, Stefan & Staffell, Iain, 2016. "Long-term patterns of European PV output using 30 years of validated hourly reanalysis and satellite data," Energy, Elsevier, vol. 114(C), pages 1251-1265.
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    Cited by:

    1. Dranka, Géremi Gilson & Ferreira, Paula, 2019. "Review and assessment of the different categories of demand response potentials," Energy, Elsevier, vol. 179(C), pages 280-294.

    More about this item


    Demand Response; Flexibility; Linear Stochastic Optimization; Demand Side Management; European Power System; Energy Economics;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • L97 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Utilities: General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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