Residential College | false |
Status | 已發表Published |
Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities | |
Ahmad,Tanveer1,2; Zhang,Dongdong3; Huang,Chao1,5; Zhang,Hongcai1; Dai,Ningyi1; Song,Yonghua1,6; Chen,Huanxin4 | |
2021-03-20 | |
Source Publication | Journal of Cleaner Production |
ABS Journal Level | 2 |
ISSN | 0959-6526 |
Volume | 289Pages:125834 |
Abstract | The energy industry is at a crossroads. Digital technological developments have the potential to change our energy supply, trade, and consumption dramatically. The new digitalization model is powered by the artificial intelligence (AI) technology. The integration of energy supply, demand, and renewable sources into the power grid will be controlled autonomously by smart software that optimizes decision-making and operations. AI will play an integral role in achieving this goal. This study focuses on the use of AI techniques in the energy sector. This study aims to present a realistic baseline that allows researchers and readers to compare their AI efforts, ambitions, new state-of-the-art applications, challenges, and global roles in policymaking. We covered three major aspects, including: i) the use of AI in solar and hydrogen power generation; (ii) the use of AI in supply and demand management control; and (iii) recent advances in AI technology. This study explored how AI techniques outperform traditional models in controllability, big data handling, cyberattack prevention, smart grid, IoT, robotics, energy efficiency optimization, predictive maintenance control, and computational efficiency. Big data, the development of a machine learning model, and AI will play an important role in the future energy market. Our study's findings show that AI is becoming a key enabler of a complex, new and data-related energy industry, providing a key magic tool to increase operational performance and efficiency in an increasingly cut-throat environment. As a result, the energy industry, utilities, power system operators, and independent power producers may need to focus more on AI technologies if they want meaningful results to remain competitive. New competitors, new business strategies, and a more active approach to customers would require informed and flexible regulatory engagement with the associated complexities of customer safety, privacy, and information security. Given the pace of development in information technology, AI and data analysis, regulatory approvals for new services and products in the new Era of digital energy markets can be enforced as quickly and efficiently as possible. |
Keyword | Artificial Intelligence Big Data Decision Making Energy Demand Energy Digitization Renewable Energy |
DOI | 10.1016/j.jclepro.2021.125834 |
URL | View the original |
Indexed By | SCIE ; SSCI |
Language | 英語English |
WOS Research Area | Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology |
WOS Subject | Green & Sustainable Science & Technology ; Engineering, Environmental ; Environmental Sciences |
WOS ID | WOS:000620273900018 |
Scopus ID | 2-s2.0-85099182935 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU) Faculty of Science and Technology DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING |
Corresponding Author | Ahmad,Tanveer |
Affiliation | 1.State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering,University of Macau, Macao,999078,China 2.Energy and Electricity Research Center,International Energy College,Jinan University,Zhuhai,519070,China 3.School of Electrical Engineering,Guangxi University,Nanning,China 4.School of Energy and Power Engineering,Huazhong University of Science and Technology,Wuhan,China 5.Shunde Graduate School,University of Science and Technology Beijing,Foshan,China 6.Department of Electrical Engineering,Tsinghua University,Beijing,100087,China |
First Author Affilication | University of Macau |
Corresponding Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Ahmad,Tanveer,Zhang,Dongdong,Huang,Chao,et al. Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities[J]. Journal of Cleaner Production, 2021, 289, 125834. |
APA | Ahmad,Tanveer., Zhang,Dongdong., Huang,Chao., Zhang,Hongcai., Dai,Ningyi., Song,Yonghua., & Chen,Huanxin (2021). Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities. Journal of Cleaner Production, 289, 125834. |
MLA | Ahmad,Tanveer,et al."Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities".Journal of Cleaner Production 289(2021):125834. |
Files in This Item: | There are no files associated with this item. |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment