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Prospect of Artificial Intelligence Towards Demand Response, Control, and Predictions in Integrated Microgrid Renewable Energy Systems

Prospect of Artificial Intelligence Towards Demand Response, Control, and Predictions in Integrated Microgrid Renewable Energy Systems
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Author(s): Sindhu Sivankutty Nair (South Batina, Oman)
Copyright: 2025
Pages: 26
Source title: Leveraging AI for Innovative Sustainable Energy: Solar, Wind and Green Hydrogen
Source Author(s)/Editor(s): Hind Hammouch (University Sidi Mohamed Ben Abdellah, Morocco)and Laeeq Razzak Janjua (WSB University, Poland)
DOI: 10.4018/979-8-3373-0045-0.ch021

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Abstract

Microgrids play a vital role in sustainable energy systems, and this is accomplished by integrating renewable energy sources like solar, wind, biogas, and tide energy. Optimization resources are done through real-time monitoring with advanced data analytics which would adjust stably to changing environmental contexts. Renewable energy sources are more successful when it comes to competing with traditional sources of energy by maximizing the potential energy yield. Regarding demand response, this paper explores the application of AI methods, looking at both price- and incentive-based programs. Regarding their use and effectiveness, this article considers a variety of control targets, input sources, and applications. To sum up, the purpose of this review analysis is to provide valuable insights into the selection of AI approaches, with an emphasis on demand-side applications for future energy systems, along with control and prediction techniques using AI. This article offers direction and assistance for the creation of sustainable integrated energy systems.

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