NDLI: Assessment of transformation strategies for the German power sector under the uncertainty of demand development and technology availability

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Assessment of transformation strategies for the German power sector under the uncertainty of demand development and technology availability

Content Provider	Semantic Scholar
Author	Ludig, Sylvie Schmid, Eva Haller, Markus Bauer, Nico
Copyright Year	2014
Abstract	The long-term energy strategy issued by the German government in 2010 and 2011 embraces a substantial reduction of CO2 emissions and high shares of renewable energy in electricity production, along with energy e ciency improvements and an accelerated nuclear phase-out. While several studies illustrate scenarios reaching these targets, there are substantial uncertainties pertaining to key assumptions, particularly long-term electricity demand and the large-scale availability of o shore wind and carbon capture and storage (CCS). This paper explores conditions under which model-based scenarios for the German electricity sector comply with the o cial targets for CO2 emission reductions and renewable shares. We apply the energy system model LIMES-D, which allows for a joint optimization of generation and transmission capacities. The results indicate that reducing electricity demand plays a crucial role for attaining the government's targets. Scenarios for which either o shore wind or CCS is not available show an even stronger need for a decreasing electricity demand to reach the targets and a di erent pattern of transmission capacity expansion than is the case with full technology availability. Hence, a broad technology portfolio could in turn hedge against future power demand increases that may challenge the joint attainment of the German decarbonization and renewable energy targets.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://edoc.gfz-potsdam.de/pik/get/6797/0/e133c336ff03f354866e2eb31b09c42f/6797oa.pdf
Language	English
Access Restriction	Open
Subject Keyword	Carbon Dioxide Emission - Male genitalia finding Energy Systems Language Mathematical optimization
Content Type	Text
Resource Type	Article

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