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Signal Analysis in Power Systems



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Autore: Leonowicz Zbigniew Visualizza persona
Titolo: Signal Analysis in Power Systems Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica: 1 electronic resource (118 p.)
Soggetto topico: History of engineering & technology
Soggetto non controllato: 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
ward algorithm
different working conditions
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
Persona (resp. second.): LeonowiczZbigniew
Sommario/riassunto: 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.
Titolo autorizzato: Signal Analysis in Power Systems  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557105203321
Lo trovi qui: Univ. Federico II
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