Backcasting policies for carbon reduction in the UK energy system

2009 ◽  
Vol 6 (27) ◽  
pp. 272008
Author(s):  
Paul Ekins ◽  
G Anandarajah
Keyword(s):  
Energy System ◽  
Carbon Reduction ◽  
The Uk

scholarly journals Measuring progress towards carbon reduction in the UK

2008 ◽  
Vol 66 (4) ◽  
pp. 594-604 ◽  
Author(s):  
A. Druckman ◽  
P. Bradley ◽  
E. Papathanasopoulou ◽  
T. Jackson
Keyword(s):  
Carbon Reduction ◽  
The Uk

Hybrid modelling of long-term carbon reduction scenarios for the UK

2008 ◽  
Vol 30 (6) ◽  
pp. 2947-2963 ◽  
Author(s):  
Neil Strachan ◽  
Ramachandran Kannan
Keyword(s):  
Hybrid Modelling ◽  
Carbon Reduction ◽  
The Uk

Carbon-reduction potential of electrification on China's railway transport: An analysis of three possible future scenarios

2020 ◽  
pp. 095440972092198
Author(s):  
Xueyi Xu ◽  
Stephen Kent ◽  
Felix Schmid
Keyword(s):  
Carbon Emissions ◽  
Electricity Generation ◽  
Reduction Potential ◽  
Energy Structure ◽  
Future Scenarios ◽  
Railway Transport ◽  
Carbon Reduction ◽  
Maximum Reduction ◽  
The Uk ◽  
Current Energy

China's national strategy identifies railway electrification as one of the principal means of reducing carbon emissions and optimising the energy structure of transportation in the country. Here, the authors investigate the carbon-reduction potential of rail electrification in China and present a model to estimate the CO2 emissions under three possible future scenarios. These scenarios differ in their contribution to railway transport in China's transportation market. The authors also consider the effect of potential improvements in the country's electricity generation mix. The results demonstrate that railway electrification using the current energy generation mix can reduce carbon emissions by 8.9%. However, using a generation mix similar to that of the UK can help achieve a maximum reduction of carbon emissions of 65.4%.

scholarly journals Modelling Socio-Environmental Sensitivities: How Public Responses to Low Carbon Energy Technologies Could Shape the UK Energy System

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Brighid Moran Jay ◽  
David Howard ◽  
Nick Hughes ◽  
Jeanette Whitaker ◽  
Gabrial Anandarajah
Keyword(s):  
Risk Aversion ◽  
Natural Resources ◽  
Large Scale ◽  
Energy System ◽  
Low Carbon ◽  
Energy Technologies ◽  
The Uk ◽  
The Cost ◽  
Low Carbon Energy

Low carbon energy technologies are not deployed in a social vacuum; there are a variety of complex ways in which people understand and engage with these technologies and the changing energy system overall. However, the role of the public’s socio-environmental sensitivities to low carbon energy technologies and their responses to energy deployments does not receive much serious attention in planning decarbonisation pathways to 2050. Resistance to certain resources and technologies based on particular socio-environmental sensitivities would alter the portfolio of options available which could shape how the energy system achieves decarbonisation (the decarbonisation pathway) as well as affecting the cost and achievability of decarbonisation. Thus, this paper presents a series of three modelled scenarios which illustrate the way that a variety of socio-environmental sensitivities could impact the development of the energy system and the decarbonisation pathway. The scenarios represent risk aversion (DREAD) which avoids deployment of potentially unsafe large-scale technology, local protectionism (NIMBY) that constrains systems to their existing spatial footprint, and environmental awareness (ECO) where protection of natural resources is paramount. Very different solutions for all three sets of constraints are identified; some seem slightly implausible (DREAD) and all show increased cost (especially in ECO).

scholarly journals Could energy-intensive industries be powered by carbon-free electricity?

2013 ◽  
Vol 371 (1986) ◽  
pp. 20110560 ◽  
Author(s):  
David J. C. MacKay
Keyword(s):  
Energy Demand ◽  
Nuclear Power ◽  
Energy System ◽  
Electricity Supply ◽  
Low Carbon ◽  
Main Thrust ◽  
Material Efficiency ◽  
Industrial Energy ◽  
The Uk ◽  
Energy Intensive Industries

While the main thrust of the Discussion Meeting Issue on ‘Material efficiency: providing material services with less material production’ was to explore ways in which society's net demand for materials could be reduced, this review examines the possibility of converting industrial energy demand to electricity, and switching to clean electricity sources. This review quantifies the scale of infrastructure required in the UK, focusing on wind and nuclear power as the clean electricity sources, and sets these requirements in the context of the decarbonization of the whole energy system using wind, biomass, solar power in deserts and nuclear options. The transition of industry to a clean low-carbon electricity supply, although technically possible with several different technologies, would have very significant infrastructure requirements.

scholarly journals An Analysis of the Impact of Bioenergy and Geosequestration in the UK Future Energy System

2014 ◽  
Vol 62 ◽  
pp. 733-742 ◽  
Author(s):  
Catalina Spataru ◽  
Eleni Zafeiratou ◽  
Mark Barrett
Keyword(s):  
Energy System ◽  
The Uk ◽  
The Impact ◽  
Future Energy System

scholarly journals Budget-cut: introduction to a budget based cutting-plane algorithm for capacity expansion models

2021 ◽  
Author(s):  
Bismark Singh ◽  
Oliver Rehberg ◽  
Theresa Groß ◽  
Maximilian Hoffmann ◽  
Leander Kotzur ◽  
...  
Keyword(s):  
Investment Decisions ◽  
General Setting ◽  
Combinatorial Problem ◽  
System Optimization ◽  
Energy System ◽  
Maximum Amount ◽  
Cutting Plane Algorithm ◽  
Linear Programs ◽  
Carbon Reduction ◽  
Computationally Expensive

AbstractWe present an algorithm to solve capacity extension problems that frequently occur in energy system optimization models. Such models describe a system where certain components can be installed to reduce future costs and achieve carbon reduction goals; however, the choice of these components requires the solution of a computationally expensive combinatorial problem. In our proposed algorithm, we solve a sequence of linear programs that serve to tighten a budget—the maximum amount we are willing to spend towards reducing overall costs. Our proposal finds application in the general setting where optional investment decisions provide an enhanced portfolio over the original setting that maintains feasibility. We present computational results on two model classes, and demonstrate computational savings up to 96% on certain instances.

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