Analyzing the impact of climate change on energy-economy-carbon nexus system in China

H. Mei, Y.P. Li, C. Suo, Y. Ma and J. Lv

Applied Energy, 2020, vol. 262, issue C, No S0306261920300805

Abstract: Climate change mitigation by reducing carbon dioxide emission becomes one of the major challenges for energy systems. In this study, a multi-GCM ensemble simulation and optimization approach is developed for analyzing the impact of climate change on China’s energy-economy-carbon nexus system under multiple uncertainties through integrating techniques of multiple global climate models, support-vector-regression, Monte Carlo simulation, and interval chance-constrained programming within a general framework. The developed approach can tackle multiple uncertainties existed in global climate models, random carbon dioxide emission and complex optimization process. Results disclose that (i) the national electricity demand would grow around 58.6% in the next 30 years under climate change; (ii) for climate change mitigation and sustainable development, fossil fuel would be gradually replaced by renewable energy (i.e. the share of fossil fuel to the total energy supply decreasing 22.5% and the share of electricity generated from renewable energy increasing 27.0% by 2050); (iii) compared to the peak value in 2030, carbon dioxide emission would reduce 15.1% by 2050, most reduction from coal-fired power generation; (iv) there is a tradeoff between carbon dioxide emission and system cost as p-level decreases from 0.15 to 0.01 (i.e. carbon dioxide emission can reduce 1.9% with 3.7% of raised system cost). It is desired for China to adjust its current energy supply structure for reducing carbon emission and seeking a low-carbon developmental path. The most effective way is to eliminate some small coal-fired units. A number of wind-power and solar-power projects are expected to be implemented due to their abundant potential markets.

Keywords: Climate change; Energy-economy-carbon nexus; Multi-GCM; Multiple uncertainties; Simulation-optimization; Systems analysis (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (56)

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DOI: 10.1016/j.apenergy.2020.114568

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