Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 630, Issue -, Pages 469-486Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2018.02.103
Keywords
Carbon mitigation; Tradable green certificate; Uncertainties; Multi-objective; Electric power system
Categories
Funding
- National Natural Science Foundation of China [41701621, 71673022, 71704010]
- Key Program of National Natural Science Foundation of China [41731286]
- Fundamental Research Funds for the Central Universities [FRF-TP-16-052A1, FRF-BR-17-005B]
- Shaanxi Province Natural Science Basic Research Program Youth Talent Project [2016JQ5008]
Ask authors/readers for more resources
Contradictions of increasing, carbon mitigation pressure and electricity demand have been aggravated significantly. A heavy emphasis is placed on analyzing the carbon mitigation potential of electric energy systems via tradable green certificates (TGC). This study proposes a ffadable green certificate (TGC)-fractional fuzzy stochastic robust optimization (FFSRO) model through integrating fuzzy possibilistic, two-stage stochastic and stochastic robust programming techniques into a linear fractional programming framework. The framework can address uncertainties expressed as stochastic and fuzzy sets, and effectively deal with issues of multi-objective tradeoffs between the economy and environment. The proposed model is applied to the major economic center of China, the Beijing-Tianjin-Hebei region. The generated results of proposed model indicate that a TGC mechanism is a cost-effective pathway to cope with carbon reduction and support the sustainable development pathway of electric energy systems. In detail, it can: (i) effectively promote renewable power development and reduce fossil fuel use; (ii) lead to higher CO2 mitigation potential than non-TGC mechanism; and (iii) greatly alleviate financial pressure on the government to provide renewable energy subsidies. The TGC-FESRO model can provide a scientific basis for making related management decisions of electric energy systems. (C) 2017 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available