Research on Day-Ahead Optimal Scheduling Considering Carbon Emission Allowance and Carbon Trading

Jiangnan Li (), Tian Mao, Guanglei Huang, Wenmeng Zhao and Tao Wang
Additional contact information
Jiangnan Li: Shenzhen Power Supply Company, China Southern Power Grid, Shenzhen 518067, China
Tian Mao: Electric Power Research Institute, China Southern Power Grid, Guangzhou 510530, China
Guanglei Huang: Shenzhen Power Supply Company, China Southern Power Grid, Shenzhen 518067, China
Wenmeng Zhao: Electric Power Research Institute, China Southern Power Grid, Guangzhou 510530, China
Tao Wang: Electric Power Research Institute, China Southern Power Grid, Guangzhou 510530, China

Sustainability, 2023, vol. 15, issue 7, 1-23

Abstract: In the context of the marketization of carbon trading in the power system, it is of great theoretical and practical significance to study a scientific and effective carbon emission quota allocation strategy. To solve this problem, under the current situation of large-scale access to new energy, considering the limitations of the carbon emissions from different emission subjects plus the construction of a carbon trading model among the emission subjects, a day-ahead optimal scheduling method that takes carbon emission quotas and carbon trading into account is proposed. Firstly, carbon transaction cost models of thermal power and wind power are constructed, respectively, and a carbon emission quota allocation strategy based on the entropy method is proposed to redistribute the weights of baseline emission factors for the regional power grid. Then, considering the additional carbon emissions of conventional thermal power units caused by wind power access, the carbon trading costs of different types of generation units are calculated on the basis of carbon trading price prediction. Thereafter, a day-ahead optimal scheduling model considering carbon emissions trading is constructed with the objective of minimizing the total cost of the system in the scheduling period. The model is solved as an MINLP problem based on MATLAB 2016a software utilizing CPLEX 12.4. Simulation results verify the correctness and effectiveness of the proposed method.

Keywords: carbon trading; day-ahead optimal scheduling; allocation of carbon emission credits; entropy method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/7/6108/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/7/6108/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:7:p:6108-:d:1113547

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().