Knowledge Graph of Low-Carbon Technologies in the Energy Sector and Cost Evolution Based on LDA2Vec: A Case Study in China

Climate change has attracted global attention, highlighting the critical role of low-carbon technologies in addressing environmental challenges. Due to the multidisciplinary nature, complexity, and diversity of research content on low-carbon technologies, a comprehensive overview is still limited. This paper uses bibliometrics analysis to discuss the research status and hotspots of low-carbon technology from a macro-perspective. The LDA2Vec topic recognition model is adopted to identify key technical terms, and CiteSpace software 6.3.1 Advanced Edition is used to conduct in-depth analysis of the development trajectory of low-carbon technology. After checking the frequency of the relevant keywords, four key techniques were identified. In order to further analyze the research results, the learning curve theory is used to predict the cost development trend of key low-carbon technologies. The results show that: (i) low-carbon technologies play a key role in the energy sector and have a potential impact on policy making, and the cost of related technologies will be significantly reduced in the next few years. (ii) Global low-carbon technologies have entered an important period of development, but remaining challenges need to be addressed by optimizing technological performance. (iii) It is very important to strengthen the research on hydrogen production technology and photovoltaic power generation technology; the cost reduction in hydrogen production technology is still significant and there is room for further optimization. (iv) To effectively address the high costs and technical barriers associated with emerging low-carbon technologies, increased funding for research and development is critical.

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Publication Details

Journal
Sustainability
Published
2024-08-26
DOI
https://doi.org/10.3390/su16177337
Primary Topic
Advanced Graph Neural Networks
Type
article
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article

Knowledge Graph of Low-Carbon Technologies in the Energy Sector and Cost Evolution Based on LDA2Vec: A Case Study in China

Sibao Fu, Peng Zhi-wen, Xingjiu Zhao
Sustainability
Advanced Graph Neural Networks
article

Knowledge Graph of Low-Carbon Technologies in the Energy Sector and Cost Evolution Based on LDA2Vec: A Case Study in China

Sibao Fu, Peng Zhi-wen, Xingjiu Zhao
article en

Abstract

Climate change has attracted global attention, highlighting the critical role of low-carbon technologies in addressing environmental challenges. Due to the multidisciplinary nature, complexity, and diversity of research content on low-carbon technologies, a comprehensive overview is still limited. This paper uses bibliometrics analysis to discuss the research status and hotspots of low-carbon technology from a macro-perspective. The LDA2Vec topic recognition model is adopted to identify key technical terms, and CiteSpace software 6.3.1 Advanced Edition is used to conduct in-depth analysis of the development trajectory of low-carbon technology. After checking the frequency of the relevant keywords, four key techniques were identified. In order to further analyze the research results, the learning curve theory is used to predict the cost development trend of key low-carbon technologies. The results show that: (i) low-carbon technologies play a key role in the energy sector and have a potential impact on policy making, and the cost of related technologies will be significantly reduced in the next few years. (ii) Global low-carbon technologies have entered an important period of development, but remaining challenges need to be addressed by optimizing technological performance. (iii) It is very important to strengthen the research on hydrogen production technology and photovoltaic power generation technology; the cost reduction in hydrogen production technology is still significant and there is room for further optimization. (iv) To effectively address the high costs and technical barriers associated with emerging low-carbon technologies, increased funding for research and development is critical.

SustainabilityVol. 16(17)
Beijing University of Posts and Telecommunications (CN), Beijing University of Technology (CN)
Openalex Percentile: Top 88%
Advanced Graph Neural Networks
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Knowledge Graph of Low-Carbon Technologies in the Energy Sector and Cost Evolution Based on LDA2Vec: A Case Study in China — Sibao Fu, Peng Zhi-wen, et al. · Sustainability (2024) | TGRS Research Map | TGRS