A novel framework for the carbon reduction performance of power grids: A case study of provincial power grids within the China Central Power Grid

Abstract

Power grids play a crucial role in connecting electricity suppliers and consumers. They facilitate efficient power transmission and energy management, significantly contributing to the transition toward low-carbon practices across both upstream and downstream sectors. Effectively managing carbon reduction in the power industry is essential for enhancing carbon reduction efficiency and achieving dual-carbon goals. Recent studies have focused on the outcomes of carbon reduction efforts rather than the management process. However, when power grids prioritize the process of carbon reduction in their management, they are more likely to achieve better results. To address this gap, we propose an evaluation model for managing carbon reduction activities in power grids, comprising the carbon management efficiency (CME) module based on the maturity model and the carbon reduction efficiency (CRE) module based on the entropy method. The CME module provides a scorecard corresponding to a detailed and continuous evaluation model for carbon management processes to calculate its performance. Simultaneously, the CRE module relates carbon reduction results to the development direction of the government and power grid, allowing for effective adjustments and updates based on actual situations. The evaluation model was applied to provincial power grids within the China Central Power Grid. The results reveal that despite some fluctuations in carbon reduction performance, provincial power grids within the China Central Power Grid have made continuous progress in carbon reduction efforts. According to the synergy model, there is evidence suggesting that power grids are steadily improving their carbon reduction performance, and a more organized approach would lead to a greater degree of synergy. The evaluation model applies to power grids, and its framework can be extended to other industries, providing a theoretical reference for evaluating their carbon reduction efforts.

Graphical abstract

Keywords

power grid / carbon reduction / evaluation model / maturity model / synergy model

References

[1] Aghdam F H, Kalantari N T, Ravadanegh S N, (2020). Reconfiguration-based hierarchical energy management in multimicrogrid systems considering power losses, reliability index, and voltage enhancement. Turkish Journal of Electrical Engineering and Computer Sciences, 28( 5): 2433–2447

[2] Alizadeh R, Beiragh R G, Soltanisehat L, Soltanzadeh E, Lund P D, (2020). Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach. Energy Economics, 91: 104894

[3] Antunes P, Carreira P, da Silva M M, (2014). Towards an energy management maturity model. Energy Policy, 73: 803–814

[4] FanC (2018). The research on low-carbon performance evaluation of listed thermal power generation companies based on the DPSIR model. Dissertation for the Doctoral Degree. Nanchang: East China Jiao Tong University (in Chinese)

[5] Hoffmann V H, Busch T, (2008). Corporate carbon performance indicators. Journal of Industrial Ecology, 12( 4): 505–520

[6] JinY H (2022). The systematic evaluation methods for energy management performance in enterprises. Dissertation for the Doctoral Degree. Wuhan: Huazhong University of Science and Technology (in Chinese)

[7] Kuo R J, Hsu C W, Chen Y L, (2015). Integration of fuzzy ANP and fuzzy TOPSIS for evaluating carbon performance of suppliers. International Journal of Environmental Science and Technology, 12( 12): 3863–3876

[8] Liu H, Liu Y, Wang H, Yang J, Zhou X, (2019). Research on the coordinated development of greenization and urbanization based on system dynamics and data envelopment analysis——A case study of Tianjin. Journal of Cleaner Production, 214: 195–208

[9] LiuJLiuW JinLTuT DingY (2020). A performance evaluation framework of electricity markets in China. In: 5th Asia Conference on Power and Electrical Engineering (ACPEE): IEEE 2020: 1043–8

[10] Luo X Y, (2018). The construction of a carbon performance evaluation index system for enterprises based on the “3E” triangle model. Communication of Finance and Accounting, 29: 61–64 (in Chinese)

[11] Modak M, Pathak K, Ghosh K K, (2017). Performance evaluation of outsourcing decision using a BSC and fuzzy AHP approach: A case of the Indian coal mining organization. Resources Policy, 52: 181–191

[12] Myung J K, An H, Lee S, (2019). Corporate competitiveness index of climate change: A balanced scorecard approach. Sustainability, 11( 5): 1445

[13] Nakthong V, Kubaha K, (2019). Development of a sustainability index for an energy management system in Thailand. Sustainability, 11( 17): 4587

[14] Qi S, Ju M, Duan M, Xing M, (2012). Research on low carbon management using a scientific classification method. Frontiers of Environmental Science & Engineering, 6( 4): 524–530

[15] Rietbergen M G, Opstelten I J, Blok K, (2017). Improving energy and carbon management in construction and civil engineering companies—Evaluating the impacts of the CO₂ performance ladder. Energy Efficiency, 10( 1): 55–79

[16] StatisticsB P (2020). Statistical review of world energy 2020. Avalible at the website of BP

[17] Tan W, Shen W, Zhao J, (2007). A methodology for dynamic enterprise process performance evaluation. Computers in Industry, 58( 5): 474–485

[18] Yun S, Hamburger R O, Cornell C A, Foutch D A, (2002). Seismic performance evaluation for steel moment frames. Journal of Structural Engineering, 128( 4): 534–545

[19] Zhang C, Randhir T O, Zhang Y, (2018). Theory and practice of enterprise carbon asset management from the perspective of low-carbon transformation. Carbon Management, 9( 1): 87–94

[20] Zhang Q, Gu B, Zhang H, Ji Q, (2023). Emission reduction mode of China’s provincial transportation sector: Based on “Energy+” carbon efficiency evaluation. Energy Policy, 177: 113556

[21] Zhou Z, Liu J, Zeng H, Xu M, Li S, (2022). Carbon performance evaluation model from the perspective of circular economy—The case of Chinese thermal power enterprise. Frontiers of Engineering Management, 1: 1–15

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s42524-024-4016-8 is accessible for authorized users.

Competing Interests

The authors declare that they have no competing interests.

List of abbreviations
carbon management efficiency	CME
carbon reduction efficiency	CRE
carbon management system	CMS
administration	A
strategies	S
implementation	I
compliance	C
optimization	O
input	IP
flow	F
output	OP
economy	E
operation degree	OD
orderliness degree	ORD
synergy degree	SYD

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