Reprint
Signal Analysis in Power Systems
Edited by
August 2020
118 pages
- ISBN978-3-03936-820-4 (Hardback)
- ISBN978-3-03936-821-1 (PDF)
This is a Reprint of the Special Issue Signal Analysis in Power Systems that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary
The analysis of power systems under various conditions represents one of the most important and complex tasks in electrical power engineering. Studies in this area are necessary to ensure that the reliability, efficiency, and stability of the power system is not adversely affected. This issue is devoted to reviews and applications of modern methods of signal processing used to analyze the operation of a power system and evaluate the performance of the system in all aspects. Smart grids as an emerging research field of the current decade is the focus of this issue. Monitoring capability with data integration, advanced analysis of support system control, enhanced power security and effective communication to meet the power demand, efficient energy consumption and minimum costs, and intelligent interaction between power-generating and -consuming devices depends on the selection and implementation of advanced signal analysis and processing techniques.
Format
- Hardback
License and Copyright
© 2020 by the authors; CC BY-NC-ND license
Keywords
convolutional neural networks; multi-headed CNN; CNN-LSTM; forecasting; solar output; sliding window; renewable energy; data mining; cluster analysis; power quality; global power quality index; electrical power network; distributed generation; mining industry; data mining; power quality; cluster analysis; ward algorithm; different working conditions; distributed generation; power supply restoration; power supply outages; failures; time intervals; obtaining information; information recognition; connection harmonization; virtual power plant; distributed energy resources; energy storage systems; grid codes; power systems; smart grids; prosumer; business model; economic efficiency; sensitivity analysis