Research on an Improved Carbon Emission Flow Model Considering Electric Vehicle Charging Fluctuation and Hybrid Power Transaction

Xianfeng Zhu, Ziwei Liu, Ran Shen, Qingming Wang (), Aihong Tang, Xinyu You, Wenhan Yu, Wenhao Wang and Lujie Mao
Additional contact information
Xianfeng Zhu: Yichang Power Supply Company, State Grid Hubei Electric Power Co., Ltd., Yichang 443200, China
Ziwei Liu: Yichang Power Supply Company, State Grid Hubei Electric Power Co., Ltd., Yichang 443200, China
Ran Shen: Yichang Power Supply Company, State Grid Hubei Electric Power Co., Ltd., Yichang 443200, China
Qingming Wang: School of Automation, Wuhan University of Technology, Wuhan 430070, China
Aihong Tang: School of Automation, Wuhan University of Technology, Wuhan 430070, China
Xinyu You: School of Automation, Wuhan University of Technology, Wuhan 430070, China
Wenhan Yu: School of Automation, Wuhan University of Technology, Wuhan 430070, China
Wenhao Wang: School of Automation, Wuhan University of Technology, Wuhan 430070, China
Lujie Mao: School of Automation, Wuhan University of Technology, Wuhan 430070, China

Energies, 2023, vol. 16, issue 19, 1-15

Abstract: With the update of the power transaction mode and the access of increasing electric vehicles with high randomness to the power grid, the existing carbon emission flow calculation method cannot consider the influence of carbon emission due to the fluctuation in electric vehicle charging and various transaction modes. Given the above shortcomings, this paper proposes an improved carbon emission flow model considering electric vehicle charging fluctuations and hybrid power transactions. The model first considers different transaction modes, allocates the network loss to both sides of power generation, and forms a lossless network, realizing the decoupling of the bilateral transaction mode, pool transaction mode, and network loss and then calculating the day-ahead network’s carbon emission. Then, the changes in different transaction modes caused by the fluctuation in electric vehicle charging under different transaction modes are analyzed and the nodes of ‘spontaneous change’ are found to form a day-ahead intra-day deviation network and calculate its carbon emission flow. Finally, the calculation results are combined to obtain an improved power system carbon emission flow considering electric vehicle charging fluctuations and transaction modes. In this paper, the 33-node system is used for verification.

Keywords: electric vehicle; carbon emission flow; bilateral transaction mode; pool transaction mode; charging fluctuation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/19/6835/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/19/6835/ (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:jeners:v:16:y:2023:i:19:p:6835-:d:1248641

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

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