Application of Machine Learning to Power Systems
This special issue belongs to the section "Inventions and Innovation in Electrical Engineering/Energy/Communications".
Special Issue Information
Dear colleagues,
The interconnection between all energy-related ‘things’ within a grid, and even between the grids themselves in the Energy Internet, is both technologically complex and risky. It poses significant challenges for decision makers and regulators. A power grid with smart environment technologies that automates the process of monitoring the health of the grid, or the usage of facilities, for long-term maintenance and facility management, is needed. Tools to collate such information automatically from grid in-use to aid the maintenance or facility manager in making smarter and timelier decisions are needed. In addition, different systems can be interconnected in a way similar to the interconnection between different web servers over the Internet. This Special Issue aims to solicit innovative research and state-of-the-art machine learning algorithms for managing the risks posed by fast-paced technology changes, the volatility of global electricity prices, system over-frequency, and cyber-physical threats, as well as for improving power system planning, operation, and control.
Prof. Dr. Tek-Tjing Lie
Dr. Ramon Zamora
Dr. Miftah Al-Karim
Guest Editors
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Keywords
- machine learning
- cyber security
- risk
- energy internet
- fault detection
- power-system health monitoring
- power-system security assessment
- preventive and corrective control
- demand-side management
- outage management
- asset management
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Published Papers
Inventions - ISSN 2411-5134