Enhancing Grid Reliability and Renewable Integration Through AI-Based Predictive Maintenance

Author:

Pohakar Puja Yogesh1,Gandhi Ravi2,Champaty Biswajeet2

Affiliation:

1. Pimpri Chinchwad College of Engineering, India

2. Ajeenkya D.Y. Patil University, India

Abstract

A case study of AI approaches to smart and sustainable power systems can provide insights into how artificial intelligence technologies are being applied in real-world scenarios to enhance the efficiency, reliability, and sustainability of power generation, distribution, and consumption. Green power utility faces the challenge of maintaining a reliable power grid while integrating a significant amount of intermittent renewable energy. To address this challenge, this study implemented AI-driven predictive maintenance strategies. The diagnosis and maintenance of induction motors play a crucial role in ensuring grid reliability and successful integration of renewable energy sources. In general, the detection and diagnosis of incipient faults in induction motors is necessary for improved operational efficiency and product quality assurance.

Publisher

IGI Global

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