The long term price elastic demand of hydrogen - A multi-model analysis for Germany

被引:0
|
作者
Weissenburger, Bastian [1 ,2 ]
Wietschel, Martin [1 ]
Lux, Benjamin [1 ]
Rehfeldt, Matthias [1 ]
机构
[1] Fraunhofer Inst Syst & Innovat Res ISI, Breslauer Str 48, D-76139 Karlsruhe, Germany
[2] Swiss Fed Inst Technol, Inst Energy & Proc Engn, Energy Syst Anal, Clausiusstr 33, CH-8092 Zurich, Switzerland
关键词
Hydrogen demand; Price sensitivity; Energy system modelling; Hydrogen price; MODELING MARKET DIFFUSION; WORLD DRIVING DATA; ELECTRIC VEHICLES; ENERGY EFFICIENCY; TECHNOLOGY;
D O I
10.1016/j.esr.2024.101432
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Hydrogen and its derivatives are important components to achieve climate policy goals, especially in terms of greenhouse gas neutrality. There is an ongoing controversial debate about the applications in which hydrogen and its derivatives should be used and to what extent. Typically, the estimation of hydrogen demand relies on scenario -based analyses with varying underlying assumptions and targets. This study establishes a new framework consisting of existing energy system simulation and optimisation models in order to assess the long-term price -elastic demand of hydrogen. The aim of this work is to shift towards an analysis of the hydrogen demand that is primarily driven by its price. This is done for the case of Germany because of the expected high hydrogen demand for the years 2025-2045. 15 wholesale price pathways were established, with final prices in 2045 between 56 <euro>/MWh and 182 <euro>/MWh. The results suggest that - if climate targets are to be achieved - even with high hydrogen prices (252 <euro>/MWh in 2030 and 182 <euro>/MWh in 2045) a significant hydrogen demand in the industry sector and the energy conversion sector is expected to emerge (318 TWh). Furthermore, the energy conversion sector has a large share of price sensitive hydrogen demand and therefore its demand strongly increases with lower prices. The road transportation sector will only play a small role in terms of hydrogen demand, if prices are low. In the decentralised heating for buildings no relevant demand will be seen over the considered price ranges, whereas the centralised supply of heat via heat grids increases as prices fall.
引用
收藏
页数:19
相关论文
共 50 条
  • [41] A multi-model fusion based non-ferrous metal price forecasting
    College of Electronic and Information Engineering, Tongji University, Shanghai
    201804, China
    不详
    410000, China
    Resour. Policy,
  • [42] A MULTI-MODEL ANALYSIS OF THE REGIONAL AND SECTORAL ROLES OF BIOENERGY IN NEAR- AND LONG-TERM CO2 EMISSIONS REDUCTION
    Calvin, Katherine
    Wise, Marshall
    Klein, David
    McCollum, David
    Tavoni, Massimo
    Van der Zwaan, Bob
    Van Vuuren, Detlef P.
    CLIMATE CHANGE ECONOMICS, 2013, 4 (04)
  • [43] Nodal price uncertainty analysis considering random failures and elastic demand
    Wang, YXP
    Ding, Y
    2004 IEEE PES POWER SYSTEMS CONFERENCE & EXPOSITION, VOLS 1 - 3, 2004, : 174 - 178
  • [44] The Future Demand for Long-term Carers in Germany: Model Calculations for the Federal Lander until 2020
    Pohl, Carsten
    COMPARATIVE POPULATION STUDIES, 2010, 35 (02) : 379 - 399
  • [45] Insights on Germany's Future Congestion Management from a Multi-Model Approach
    Hladik, Dirk
    Fraunholz, Christoph
    Kuhnbach, Matthias
    Manz, Pia
    Kunze, Robert
    ENERGIES, 2020, 13 (16)
  • [46] Endogenous third-degree price discrimination in Hotelling model with elastic demand
    Zhang, Tong
    Huo, Yixue
    Zhang, Xin
    Shuai, Jie
    JOURNAL OF ECONOMICS, 2019, 127 (02) : 125 - 145
  • [47] Endogenous third-degree price discrimination in Hotelling model with elastic demand
    Tong Zhang
    Yixue Huo
    Xin Zhang
    Jie Shuai
    Journal of Economics, 2019, 127 : 125 - 145
  • [48] An analysis of multi-model ensembles for seasonal climate predictions
    Yan, Xiaoqin
    Tang, Youmin
    QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 2013, 139 (674) : 1179 - 1198
  • [49] Multi-model probabilistic analysis of the lifecycle cost of buildings
    Gavrilovic, Stevan
    Haukaas, Terje
    SUSTAINABLE AND RESILIENT INFRASTRUCTURE, 2020,
  • [50] The "urban meteorology island": a multi-model ensemble analysis
    Karlicky, Jan
    Huszar, Peter
    Novakova, Tereza
    Belda, Michal
    Svabik, Filip
    Doubalova, Jana
    Halenka, Tomas
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2020, 20 (23) : 15061 - 15077