ORIGINAL RESEARCH
A Low-Carbon Generation Expansion Planning
Model Considering Carbon Trading and Green
Certificate Transaction Mechanisms
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Department of Economics and Management, North China Electric Power University, Baoding, China
Submission date: 2019-01-17
Final revision date: 2019-03-04
Acceptance date: 2019-03-28
Online publication date: 2019-10-04
Publication date: 2020-01-16
Corresponding author
Shijian Liu
Department of Economics and Management, North China Electric Power University, 071003, Baoding, China
Pol. J. Environ. Stud. 2020;29(2):1169-1183
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ABSTRACT
Generation expansion planning for more renewable energy is of great significance to the
implementation of low-carbon economy and energy transition in the power sector. This paper introduces
two widely used renewable energy incentives (such as carbon trading mechanism and green certificate
transaction mechanism) into traditional generation expansion planning, and establishes a low-carbon
generation expansion planning model. Then the brain storm optimization algorithm was employed to
solve the model. Finally, for the comparison between the two mechanisms, this paper sets four scenarios
for case simulation. The results show that both carbon trading mechanisms and green certificate
transaction mechanisms can increase the installed capacity of renewable energy and reduce carbon
emissions, and the optimization effect of green certificate transaction mechanism on planning results is
better than that of the carbon trading mechanism. When both mechanisms are introduced, the installed
proportion of renewable energy will be the highest and carbon emissions will achieve the minimum.
Moreover, with the increase of carbon price or green certificate price, and the strengthening of carbon
emission constraint or renewable energy quota constraint, the proportion of coal-fired units in the power
supply structure is gradually decreasing, and the carbon emissions of the system are gradually reduced.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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