Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
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 renewa...
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| Published in | Journal of cleaner production Vol. 289; p. 125834 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
20.03.2021
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| Subjects | |
| Online Access | Get full text |
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| 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.
Big data and AI applications. [Display omitted]
•The use of AI in the smart energy industry, including power generation, supply and demand is reviewed.•The role of AI in control and design of renewable energy and how it can revolutionize the energy industry is addressed.•Big data explosion, cyberattack prevention, smart grid, IoT, DL and ML improvement are key AI success stories.•History, challenges, strengths, and global trends of existing AI-based techniques are summarized.•AI is entering emerging markets in energy industry; has an impact on sustainable growth as cheap and clean energy. |
|---|---|
| AbstractList | 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. 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. Big data and AI applications. [Display omitted] •The use of AI in the smart energy industry, including power generation, supply and demand is reviewed.•The role of AI in control and design of renewable energy and how it can revolutionize the energy industry is addressed.•Big data explosion, cyberattack prevention, smart grid, IoT, DL and ML improvement are key AI success stories.•History, challenges, strengths, and global trends of existing AI-based techniques are summarized.•AI is entering emerging markets in energy industry; has an impact on sustainable growth as cheap and clean energy. |
| ArticleNumber | 125834 |
| Author | Dai, Ningyi Song, Yonghua Zhang, Dongdong Ahmad, Tanveer Huang, Chao Chen, Huanxin Zhang, Hongcai |
| Author_xml | – sequence: 1 givenname: Tanveer surname: Ahmad fullname: Ahmad, Tanveer email: tanveer.ahmad.pk11@gmail.com, tahmad@um.edu.mo organization: State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering, University of Macao, Macao, 999078, China – sequence: 2 givenname: Dongdong surname: Zhang fullname: Zhang, Dongdong organization: School of Electrical Engineering, Guangxi University, Nanning, China – sequence: 3 givenname: Chao surname: Huang fullname: Huang, Chao organization: State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering, University of Macao, Macao, 999078, China – sequence: 4 givenname: Hongcai surname: Zhang fullname: Zhang, Hongcai organization: State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering, University of Macao, Macao, 999078, China – sequence: 5 givenname: Ningyi surname: Dai fullname: Dai, Ningyi organization: State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering, University of Macao, Macao, 999078, China – sequence: 6 givenname: Yonghua surname: Song fullname: Song, Yonghua organization: State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering, University of Macao, Macao, 999078, China – sequence: 7 givenname: Huanxin surname: Chen fullname: Chen, Huanxin organization: School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, China |
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| SubjectTerms | Artificial intelligence Big data business planning computer software consumers (people) data analysis Decision making electrical equipment Energy demand Energy digitization energy efficiency energy industry environment hydrogen information information technology markets methodology power generation Renewable energy renewable energy sources researchers robots supply utilities |
| Title | Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities |
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