Assessing the value of demand response in a decarbonized energy system – A large-scale model application

Steffi Misconel, Christoph Zöphel and Dominik Möst

Applied Energy, 2021, vol. 299, issue C, No S0306261921007364

Abstract: This paper presents extensive insights on the value of applying demand response (DR) in a system perspective against the background of two strongly contrasting decarbonization pathways for a decentralized and centralized European energy system with a 100% renewable share and sector coupling. The pathways are characterized by structural differences concerning the combination of installed renewable capacities, the acceptance for activated demand response potentials and different electricity, heat and hydrogen demands. The objective is to determine the potential role of demand response and its impact on the optimal combinations of flexibility options in a decentralized vs. centralized scenario framework model-endogenously. Therefore, openly available data and hourly time series of country-specific demand response potentials are implemented into a large-scale linear optimization model. Sensitivities concerning varying shares of demand response availability are used to identify main influencing factors on selected components of the electricity system such as the capacity and generation mix, storage requirements, renewable integration and their market value factors, CO2 emissions and total system costs. Model results show a higher reduction of total system costs and CO2 emissions per activated demand response unit in the photovoltaic dominated decentralized scenario (–55 MEUR/GWDR, –0.045 MtCO2/GWDR), compared to the wind dominated centralized scenario (–39 MEUR/GWDR, –0.037 MtCO2/GWDR). The outcomes conclude that the daily photovoltaic feed-in characteristics have a higher correlation with the time pattern of load shifting and shedding demand response appliances than wind feed-in characteristics.

Keywords: Demand response; Flexibility option; 100% renewable energy system; Decarbonized power system; Power system optimization model (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (11)

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DOI: 10.1016/j.apenergy.2021.117326

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