scholarly journals Carbon Reduction Potential of Resource-Dependent Regions Based on Simulated Annealing Programming Algorithm

2017 ◽  
Vol 9 (7) ◽  
pp. 1161 ◽  
Author(s):  
Wei Li ◽  
Guomin Li ◽  
Rongxia Zhang ◽  
Wen Sun ◽  
Wen Wu ◽  
...  
Author(s):  
Xueyi Xu ◽  
Stephen Kent ◽  
Felix Schmid

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%.


2011 ◽  
Vol 39 (1) ◽  
pp. 51-65 ◽  
Author(s):  
Behzad Sodagar ◽  
Deepak Rai ◽  
Barbara Jones ◽  
Jakub Wihan ◽  
Rosi Fieldson

2003 ◽  
Vol 125 (1) ◽  
pp. 141-146 ◽  
Author(s):  
A. J. Knoek van Soest ◽  
L. J. R. Richard Casius

A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical and biomechanical optimization problems is compared to a sequential quadratic programming algorithm, a downhill simplex algorithm and a simulated annealing algorithm. When high-dimensional non-smooth or discontinuous problems with numerous local optima are considered, only the simulated annealing and the genetic algorithm, which are both characterized by a weak search heuristic, are successful in finding the optimal region in parameter space. The key advantage of the genetic algorithm is that it can easily be parallelized at negligible overhead.


2008 ◽  
Vol 41 (2) ◽  
pp. 13952-13957 ◽  
Author(s):  
Ganesh K. Venayagamoorthy ◽  
Gabriele Braband

2018 ◽  
Vol 8 (5) ◽  
pp. 504-514 ◽  
Author(s):  
Michele Florencia Victoria ◽  
Srinath Perera

Purpose The purpose of this paper is to identify the carbon intensive building elements or “carbon hotspots” of office buildings in order to maximise the carbon reduction potential during design stages. Design/methodology/approach Embodied carbon (EC) estimates of 28 office buildings in the UK were obtained and carbon hotspots of the sample (in accordance with the new rules of measurement (NRM) element classification) were identified using the 80:20 Pareto principle. Findings Frame, substructure, external walls, services and upper floors were identified as carbon hotspots of the selected sample. However, findings do not support the 80:20 ratio in this case but propose a ratio of 80:36. Stairs, internal walls and partitions, internal doors, wall finishes, ceiling finishes and fittings and furnishings were identified as carbon insignificant elements that have a lower EC reduction potential compared to the rest. Research limitations/implications The findings are applicable to office buildings in the UK but the methodology is adaptable to different types of buildings in other countries. Originality/value Findings unveil carbon intensive and carbon insignificant building elements of typical office buildings in the UK. This informs designers of the elements that could yield the highest potential EC savings via effective design choices. In addition, a logical design timeline is proposed for building elements based on their element hotspot category and design sequence to assist design decision making.


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