The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
An Overview of Machine Learning Algorithms on Microgrids
|
|
Author(s): G. Kanimozhi (Vellore Institute of Technology, Chennai, India)and Aaditya Jain (Vellore Institute of Technology, Chennai, India)
Copyright: 2024
Pages: 27
Source title:
AI Approaches to Smart and Sustainable Power Systems
Source Author(s)/Editor(s): L. Ashok Kumar (PSG College of Technology, India), S. Angalaeswari (Vellore Institute of Technology, India), K. Mohana Sundaram (KPR Institute of Engineering and Technology, India), Ramesh C. Bansal (University of Sharjah, UAE & University of Pretoria, South Africa)and Arunkumar Patil (Central University of Karnataka, India)
DOI: 10.4018/979-8-3693-1586-6.ch009
Purchase
|
Abstract
The concept of microgrid (MG) is based on the notion of small-scale power systems that can operate independently or in conjunction with the larger power grid. MGs are generally made up of renewable energy resources, such as solar panels, wind turbines, and energy storage devices (batteries). Overuse of non-renewable resources causes depletion of the ozone layer and eventually leads to global warming. The classical techniques are not sufficient to solve the problem and require modern solutions like machine learning (ML) algorithms—a subset of artificial intelligence, and deep learning -a subset of ML algorithms. Though MGs have many advantages, they also have issues like high costs, complex management, and the need for better energy storage. ML can predict energy demand, optimize power flow to save money, improve energy storage management, enhances cybersecurity, and protects MGs from hackers. The chapter presented here provides a review of different ML techniques that can be implemented on MGs, their existing problems, and some improvised solutions to overcome the grid issues.
Related Content
|
Md. Yeamin Masum, Mohammad Omar Faruq, Md. Nasir Mia, Mohammad Badruddoza Talukder.
© 2025.
28 pages.
|
|
Geetha Manoharan, Sanjeev Kumar.
© 2025.
26 pages.
|
|
Md. Mehedi Hasan Sawon, Farhana Yeasmin Lina, Mohammad Badruddoza Talukder, Md. Akram Hossain.
© 2025.
20 pages.
|
|
Mst. Sumyia Akter, Apurba Sarkar, Md Imran Hossain.
© 2025.
24 pages.
|
|
S. Anand Bharathi, S. Vinoth Kumar, S. Rajamohan, D. Unika.
© 2025.
42 pages.
|
|
Sandeep Kumar, Aman Kumar Bhardwaj, Kuldeep Singh, Sandeep Paatlan.
© 2025.
24 pages.
|
|
Dhanashri Sanadkumar Havale, Sachin Tryambak Bhandarkar, Hrishikesh Kokate.
© 2025.
30 pages.
|
|
|