Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Role of Artifcial Intelligence in Renewable Energy Subject The topic of the resource Artifcial Intelligence; control system; General Electric; Hydrogen; powerScout; Renewable energy; Robotics Description An account of the resource Technology is evolving at an unbelievable pace, to the extent where many of us cant keep up effectively. With increasing Artifcial Intelligence (AI) complexity, our environment will be transformed in amazing ways over the years and decades that follow. The renewable energy (RE) sector is no different. AI can observe patterns and beneft from large amounts of knowledge. Consequently, AI is able to make improvements to enhance energy production, conversion, and even delivery. These systems allow precise forecasting of, for example, weather and loads, mitigating, among countless other uses, the possibility of electrical surges. AI systems would signifcantly improve the productivity of renewable systems by automation over the next 10 years. For solar and wind energy, this will become particularly prevalent. Independent power producers would have the latitude required to deliver ever-more sustainable business models and services by integrating increased generation coupled with low-cost savings provided by automation. We are all aware of the requirements of RE, including solar power. However, how can AI help to increase the availability of RE? The demand for global energy is growing day by day, but fossil fuels cannot fulfll our future needs for energy. Because of increased energy consumption, fossil fuel carbon emissions have reached very high levels over time. RE, however, is emerging as a good replacement for fossil fuels. It is safer and also very clean in comparison to traditional sources. The RE industry has made tremendous strides during the preceding decade with developments in technology. AI and machine learning technologies can analyze data to predict the future. So, the use of AI can solve the problems and challenges of RE. In this chapter we discuss RE, its sources and challenges, and how AI can address these challenges. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. Creator An entity primarily responsible for making the resource Vijayalakshmi S.; Savita; Genish T.; George J.P. Source A related resource from which the described resource is derived Power Systems, pp. 253-269. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-15044-9_12" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-15044-9_12</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152423305&amp;doi=10.1007%2F978-3-031-15044-9_12&amp;partnerID=40&amp;md5=3ae357f58a88f779ac17e4ba7b3fc418" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152423305&amp;doi=10.1007%2f978-3-031-15044-9_12&amp;partnerID=40&amp;md5=3ae357f58a88f779ac17e4ba7b3fc418</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 16121287 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vijayalakshmi S., Department of Data Science, Christ University, Maharashtra, Lavasa, India; Savita, School of Computing Science and Engineering, Galgotias University, Uttar Pradesh, Greater Noida, India; Genish T., Department of Computer Science, KPR College of Arts Science and Research, Tamil Nadu, Coimbatore, India; George J.P., Department of Data Science, Christ University, Pune, Lavasa, India