Smart Energy Systems-Integrated Machine Learning, IoT, and AI Tools-Reference-Cited by-同舟云学术

Smart Energy Systems-Integrated Machine Learning, IoT, and AI Tools

Published:2024-06-07 Issue: Volume: Page:201-229
ISSN:2326-9162
Container-title:Advances in Environmental Engineering and Green Technologies
language:
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Author:

Komala C. R.¹,Basha Mehfooza Munavar²^ORCID,Farook S.³,Niranchana R.⁴^ORCID,Rajendiran M.⁵^ORCID,Subhi B.⁶

Affiliation:

1. Department of Information Science and Engineering, HKBK College of Engineering, India

2. Department of Computer Science and Engineering, AI&DS, Jeppiaar University, India

3. Department of Electrical and Electronics Engineering, School of Engineering, Mohan Babu University, India

4. Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, India

5. Department of Computer Science and Engineering, Panimalar Engineering College, India

6. PCR Engineering College, India

Abstract

The integration of renewable energy sources and AI-driven solutions is revolutionizing the energy landscape, offering efficiency, sustainability, and innovation. This chapter explores the interplay between renewable energy sources and AI-driven solutions, highlighting its role in forecasting, real-time monitoring, predictive maintenance, and demand response. Comparative studies between traditional and novel energy technologies highlight the potential for cleaner, more efficient alternatives. Challenges of integration complexity, data privacy, and scalability are discussed, while a vision of future directions includes holistic energy systems, autonomous energy networks, and collaborative innovation. By harnessing AI's capabilities and embracing innovative power generation methods, the energy sector can create a resilient, sustainable, and intelligent energy future.

Publisher

IGI Global

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