An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS

Yang Pu; Yi Chang Li; Shun Fang; Xueying Wang; Zhong Jin; Zhiyang Jia

doi:10.1007/978-981-96-4963-1_40

An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS

Yang Pu
, Yi Chang Li^*
, Shun Fang
, Xueying Wang^*
, Zhong Jin
, Zhiyang Jia

^*Corresponding author for this work

China University of Petroleum-Beijing at Karamay

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In line with the Paris Agreement’s global carbon reduction targets, the rise of Carbon Capture, Utilization, and Storage (CCUS) technology offers significant opportunities to mitigate climate change. With the introduction of the Capacity Bidding Program (CBP), addressing the issues of insufficient power load adjustment flexibility and high CO2 emissions in energy-intensive industrial manufacturing during grid emergencies becomes essential. A low-carbon flexible manufacturing dispatch model that incorporates CCUS infrastructure is proposed. Firstly, distributed carbon capture power plants are introduced in industrial parks to reduce industrial enterprises’ dependence on the main grid. Secondly, the model considers the Capacity Bidding Program. Based on this, a low-carbon scheduling model aimed at maximizing the total manufacturer’s profit is constructed. The model includes raw material costs, power costs, carbon costs, and so on, and it can automatically determine the best load curtailment offers for the Capacity Bidding Program. The effectiveness of the proposed method in improving factory profit, maintaining grid stability, and reducing carbon dioxide emissions is verified through a case study of high-capacity lithium battery manufacturing.

Original language	English
Title of host publication	Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I
Editors	Guangqiang Yin, Xiaodong Liu, Jian Su, Yangzhao Yang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	443-454
Number of pages	12
ISBN (Print)	9789819649624
DOIs	https://doi.org/10.1007/978-981-96-4963-1_40
Publication status	Published - 2025
Externally published	Yes
Event	14th International Conference on Computer Engineering and Networks, CENet 2024 - Kashi, China Duration: 18 Oct 2024 → 21 Oct 2024

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	1384 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	14th International Conference on Computer Engineering and Networks, CENet 2024
Country/Territory	China
City	Kashi
Period	18/10/24 → 21/10/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

CCUS
Capacity Bidding Program
Low-Carbon Electricity Response
Low-Carbon Manufacturing
Resilient Manufacturing

Access to Document

10.1007/978-981-96-4963-1_40

Cite this

Pu, Y., Li, Y. C., Fang, S., Wang, X., Jin, Z., & Jia, Z. (2025). An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS. In G. Yin, X. Liu, J. Su, & Y. Yang (Eds.), Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I (pp. 443-454). (Lecture Notes in Electrical Engineering; Vol. 1384 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-96-4963-1_40

Pu, Yang ; Li, Yi Chang ; Fang, Shun et al. / An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS. Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I. editor / Guangqiang Yin ; Xiaodong Liu ; Jian Su ; Yangzhao Yang. Springer Science and Business Media Deutschland GmbH, 2025. pp. 443-454 (Lecture Notes in Electrical Engineering).

@inproceedings{fbb766e94f9841d58b340b27f9cfb4b9,

title = "An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS",

abstract = "In line with the Paris Agreement{\textquoteright}s global carbon reduction targets, the rise of Carbon Capture, Utilization, and Storage (CCUS) technology offers significant opportunities to mitigate climate change. With the introduction of the Capacity Bidding Program (CBP), addressing the issues of insufficient power load adjustment flexibility and high CO2 emissions in energy-intensive industrial manufacturing during grid emergencies becomes essential. A low-carbon flexible manufacturing dispatch model that incorporates CCUS infrastructure is proposed. Firstly, distributed carbon capture power plants are introduced in industrial parks to reduce industrial enterprises{\textquoteright} dependence on the main grid. Secondly, the model considers the Capacity Bidding Program. Based on this, a low-carbon scheduling model aimed at maximizing the total manufacturer{\textquoteright}s profit is constructed. The model includes raw material costs, power costs, carbon costs, and so on, and it can automatically determine the best load curtailment offers for the Capacity Bidding Program. The effectiveness of the proposed method in improving factory profit, maintaining grid stability, and reducing carbon dioxide emissions is verified through a case study of high-capacity lithium battery manufacturing.",

keywords = "CCUS, Capacity Bidding Program, Low-Carbon Electricity Response, Low-Carbon Manufacturing, Resilient Manufacturing",

author = "Yang Pu and Li, \{Yi Chang\} and Shun Fang and Xueying Wang and Zhong Jin and Zhiyang Jia",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 14th International Conference on Computer Engineering and Networks, CENet 2024 ; Conference date: 18-10-2024 Through 21-10-2024",

year = "2025",

doi = "10.1007/978-981-96-4963-1\_40",

language = "English",

isbn = "9789819649624",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "443--454",

editor = "Guangqiang Yin and Xiaodong Liu and Jian Su and Yangzhao Yang",

booktitle = "Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I",

address = "Germany",

}

Pu, Y, Li, YC, Fang, S, Wang, X, Jin, Z & Jia, Z 2025, An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS. in G Yin, X Liu, J Su & Y Yang (eds), Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I. Lecture Notes in Electrical Engineering, vol. 1384 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 443-454, 14th International Conference on Computer Engineering and Networks, CENet 2024, Kashi, China, 18/10/24. https://doi.org/10.1007/978-981-96-4963-1_40

An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS. / Pu, Yang; Li, Yi Chang; Fang, Shun et al.
Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I. ed. / Guangqiang Yin; Xiaodong Liu; Jian Su; Yangzhao Yang. Springer Science and Business Media Deutschland GmbH, 2025. p. 443-454 (Lecture Notes in Electrical Engineering; Vol. 1384 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS

AU - Pu, Yang

AU - Li, Yi Chang

AU - Fang, Shun

AU - Wang, Xueying

AU - Jin, Zhong

AU - Jia, Zhiyang

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

PY - 2025

Y1 - 2025

N2 - In line with the Paris Agreement’s global carbon reduction targets, the rise of Carbon Capture, Utilization, and Storage (CCUS) technology offers significant opportunities to mitigate climate change. With the introduction of the Capacity Bidding Program (CBP), addressing the issues of insufficient power load adjustment flexibility and high CO2 emissions in energy-intensive industrial manufacturing during grid emergencies becomes essential. A low-carbon flexible manufacturing dispatch model that incorporates CCUS infrastructure is proposed. Firstly, distributed carbon capture power plants are introduced in industrial parks to reduce industrial enterprises’ dependence on the main grid. Secondly, the model considers the Capacity Bidding Program. Based on this, a low-carbon scheduling model aimed at maximizing the total manufacturer’s profit is constructed. The model includes raw material costs, power costs, carbon costs, and so on, and it can automatically determine the best load curtailment offers for the Capacity Bidding Program. The effectiveness of the proposed method in improving factory profit, maintaining grid stability, and reducing carbon dioxide emissions is verified through a case study of high-capacity lithium battery manufacturing.

AB - In line with the Paris Agreement’s global carbon reduction targets, the rise of Carbon Capture, Utilization, and Storage (CCUS) technology offers significant opportunities to mitigate climate change. With the introduction of the Capacity Bidding Program (CBP), addressing the issues of insufficient power load adjustment flexibility and high CO2 emissions in energy-intensive industrial manufacturing during grid emergencies becomes essential. A low-carbon flexible manufacturing dispatch model that incorporates CCUS infrastructure is proposed. Firstly, distributed carbon capture power plants are introduced in industrial parks to reduce industrial enterprises’ dependence on the main grid. Secondly, the model considers the Capacity Bidding Program. Based on this, a low-carbon scheduling model aimed at maximizing the total manufacturer’s profit is constructed. The model includes raw material costs, power costs, carbon costs, and so on, and it can automatically determine the best load curtailment offers for the Capacity Bidding Program. The effectiveness of the proposed method in improving factory profit, maintaining grid stability, and reducing carbon dioxide emissions is verified through a case study of high-capacity lithium battery manufacturing.

KW - CCUS

KW - Capacity Bidding Program

KW - Low-Carbon Electricity Response

KW - Low-Carbon Manufacturing

KW - Resilient Manufacturing

UR - https://www.scopus.com/pages/publications/105005570795

U2 - 10.1007/978-981-96-4963-1_40

DO - 10.1007/978-981-96-4963-1_40

M3 - Conference contribution

AN - SCOPUS:105005570795

SN - 9789819649624

T3 - Lecture Notes in Electrical Engineering

SP - 443

EP - 454

BT - Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I

A2 - Yin, Guangqiang

A2 - Liu, Xiaodong

A2 - Su, Jian

A2 - Yang, Yangzhao

PB - Springer Science and Business Media Deutschland GmbH

T2 - 14th International Conference on Computer Engineering and Networks, CENet 2024

Y2 - 18 October 2024 through 21 October 2024

ER -

Pu Y, Li YC, Fang S, Wang X, Jin Z, Jia Z. An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS. In Yin G, Liu X, Su J, Yang Y, editors, Proceedings of the 14th International Conference on Computer Engineering and Networks - Volume I. Springer Science and Business Media Deutschland GmbH. 2025. p. 443-454. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-96-4963-1_40

An Economic Low-Carbon Scheduling Model for Manufacturers in Capacity Bidding Program Considering CCUS

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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