dc.contributor.author |
Li, Chengyu |
|
dc.contributor.author |
Zhang, Yanbing |
|
dc.contributor.author |
Pratap, Saurabh |
|
dc.contributor.author |
Zhou, Li |
|
dc.contributor.author |
Liu, Baoquan |
|
dc.contributor.author |
Zhou, Guangliang |
|
dc.date.accessioned |
2023-04-24T10:59:55Z |
|
dc.date.available |
2023-04-24T10:59:55Z |
|
dc.date.issued |
2022-01-12 |
|
dc.identifier.issn |
2296598X |
|
dc.identifier.uri |
http://localhost:8080/xmlui/handle/123456789/2232 |
|
dc.description |
This paper is submitted by the author of IIT (BHU), Varanasi |
en_US |
dc.description.abstract |
The 2060 carbon neutral target reflects the long-term equilibrium and stability of production activities and the natural environment. As an important part of Chinese energy structure, the operation and transformation of power enterprises will face higher requirements. Although the rapid development of smart grids provides necessary technical support for power enterprises to build a modern energy system with green power as the core, whether power enterprises can use smart grids to improve their operating performance and environmental performance has yet to be discussed. The differences caused by the heterogeneity of property rights will also have an impact on the green transformation and development of enterprises. This paper selects 25 Chinese power enterprises as the research objects and uses the 2011–2019 enterprise panel data and the data envelopment analysis model to evaluate the operating performance and environmental performance of power enterprises. The results show that the overall fluctuation trend of the total factor productivity index and green total factor productivity index of power enterprises are W-shaped, and technological progress is the main driving force for the improvement of power operating performance and environmental performance; Compared with enterprises with a single power generation method, enterprises with diversified power generation methods performed better in their overall total factor productivity index. After that, text mining and machine learning methods are used to classify the text of the enterprise’s annual report to determine whether the enterprise applies smart grid technology for production and operation activities. Finally, using feasible generalized least squares method (FLGS) and dynamic panel system generalized moment estimation (SYS-GMM) to analyze the impact of smart grid on the operating performance and environmental performance of power enterprises, and the nature of corporate property rights in this process. It is found that smart grids can improve the operating performance and environmental performance of power enterprises; compared with state-owned enterprises, non-state-owned enterprises can achieve better performance in the application of smart grids to improve operating performance and environmental performance. Finally, this study provides corresponding policy recommendations for power enterprises to achieve performance improvement and green transformation development. |
en_US |
dc.description.sponsorship |
This work was supported by the National Natural Science Foundation of China (71803181, 71663040); National Office for Philosophy and Social Sciences of China (19FGLB062); Science and Technology Innovative Talents (Humanities and Social Sciences) Program of Henan (2021-CX-019); Philosophy and Social Science Program of Henan (2020BJJ067, 2020JC17); Research project of the Chinese Society of Academic Degrees and Graduate Education (2020MSA396); Key R & D and Promotion Project of Henan (Soft Science Research) (222400410123); Key Project of Philosophy and Social Science Research in Colleges and Universities of Henan (2019-YYZD-18, 2021-JCZD-25); Open Research Fund of Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, China (2021KFKT007). |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Frontiers Media S.A. |
en_US |
dc.relation.ispartofseries |
Frontiers in Energy Research;Article number 783786 |
|
dc.subject |
environmental performance |
en_US |
dc.subject |
FLGS |
en_US |
dc.subject |
malmquist-DEA |
en_US |
dc.subject |
operating performance |
en_US |
dc.subject |
system GMM |
en_US |
dc.subject |
Data envelopment analysis |
en_US |
dc.subject |
Electric power transmission networks |
en_US |
dc.subject |
Environmental management |
en_US |
dc.subject |
Learning systems |
en_US |
dc.subject |
Productivity |
en_US |
dc.subject |
Smart power grids |
en_US |
dc.subject |
Environmental performance; Feasible generalized least square method; Generalized least square; Least-squares- methods; Malmquist; Malmquist-DEA; Operating performance; Power enterprise; System GMM; Total factor productivity |
en_US |
dc.subject |
Least squares approximations |
en_US |
dc.title |
Regulation Effect of Smart Grid on Green Transformation of Electric Power Enterprises: Based on the Investigation of “Leader” Trap |
en_US |
dc.type |
Article |
en_US |