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http://hdl.handle.net/10397/106163
Title: | Artificial intelligence powered large-scale renewable integrations in multi-energy systems for carbon neutrality transition : challenges and future perspectives | Authors: | Liu, ZX Sun, Y Xing, CJ Liu, J He, YD Zhou, YK Zhang, GQ |
Issue Date: | Nov-2022 | Source: | Energy and AI, Nov. 2022, v. 10, 100195 | Abstract: | The vigorous expansion of renewable energy as a substitute for fossil energy is the predominant route of action to achieve worldwide carbon neutrality. However, clean energy supplies in multi-energy building districts are still at the preliminary stages for energy paradigm transitions. In particular, technologies and methodologies for large-scale renewable energy integrations are still not sufficiently sophisticated, in terms of intelligent control management. Artificial intelligent (AI) techniques powered renewable energy systems can learn from bio-inspired lessons and provide power systems with intelligence. However, there are few in-depth dissections and deliberations on the roles of AI techniques for large-scale integrations of renewable energy and decarbon-isation in multi-energy systems. This study summarizes the commonly used AI-related approaches and discusses their functional advantages when being applied in various renewable energy sectors, as well as their functional contribution to optimizing the operational control modalities of renewable energy and improving the overall operational effectiveness. This study also presents practical applications of various AI techniques in large-scale renewable energy integration systems, and analyzes their effectiveness through theoretical explanations and diverse case studies. In addition, this study introduces limitations and challenges associated with the large-scale renewable energy integrations for carbon neutrality transition using relevant AI techniques, and proposes further promising research perspectives and recommendations. This comprehensive review ignites advanced AI tech-niques for large-scale renewable integrations and provides valuable informational instructions and guidelines to different stakeholders (e.g., engineers, designers and scientists) for carbon neutrality transition. | Keywords: | Artificial intelligent techniques Renewable energy Large-scale integration Energy transition Carbon neutrality |
Publisher: | Elsevier BV | Journal: | Energy and AI | EISSN: | 2666-5468 | DOI: | 10.1016/j.egyai.2022.100195 | Rights: | © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). The following publication Liu, Z., Sun, Y., Xing, C., Liu, J., He, Y., Zhou, Y., & Zhang, G. (2022). Artificial intelligence powered large-scale renewable integrations in multi-energy systems for carbon neutrality transition: Challenges and future perspectives. Energy and AI, 10, 100195 is available at https://dx.doi.org/10.1016/j.egyai.2022.100195. |
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1-s2.0-S2666546822000428-main.pdf | 4.85 MB | Adobe PDF | View/Open |
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