Machine Learning and Data Mining Applications in Power and Multi-Energy Systems

Dear Colleagues,

This Special Issue is intended as a forum for advancing research and for applying machine learning and data mining in order to facilitate the development of modern electric power systems, grids and devices, smart grids, and protection devices, as well as for developing tools for more accurate and efficient power system analysis and multi-energy systems.

Conventional signal processing is not more adequate for extracting all of the relevant information from distorted signals through filtering, estimation, and detection in order to facilitate decision making and to control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data mining statistical signal detection, and estimation may help in solving contemporary challenges in modern power systems and multi-energy systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; dynamic optimization of grid operations; demand response; incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information and to transform information into actionable intelligence.

The expected outcomes will be a grid with improved situation awareness, faster and more accurate control actions to detect and isolate faults, improved assurance of power quality, and higher levels of energy efficiency.

Dr. Michał Jasiński
Prof. Dr. Zbigniew Leonowicz
Guest Editors

Manuscript Submission Information

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