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Modelling of sectoral energy demand through energy intensities in MEDEAS integrated assessment model

Producción Científica The estimation of future energy demand is a key factor for the development of effective alternative policies towards a low carbon economy. This paper describes a novel method to estimate the energy demand in the new integrated assessment framework MEDEAS based on the projection of sectoral final energy intensities. The dynamic of each of the sectoral final energy intensity is broken down into (1) improvement in energy efficiency and (2) substitution of the final energy. The speed of changes in these factors depend on physical supply-demand unbalances in the market, climate mitigation and other energy saving policies and the perception of scarcity of the different economic agents. The simulated case studies in MEDEAS-World under the narrative of the Business-as-usual (BAU) scenario have allowed validating the model's robustness and showing the potentiality of its application. European Union's Horizon 2020 research and innovation programme under grant agreement No 691287 Ministerio de Economía, Industria y Competitividad (Project FJCI-2016-28833)
- University of Valladolid Spain
- "UNIVERSIDAD DE VALLADOLID Spain
Energía, Energy industries. Energy policy. Fuel trade, Energy intensity, 5312.05 Energía, HD9502-9502.5
Energía, Energy industries. Energy policy. Fuel trade, Energy intensity, 5312.05 Energía, HD9502-9502.5
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).21 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
