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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 online resource (118 p.)
Soggetto topico: History of engineering and technology
Soggetto non controllato: business model
cluster analysis
CNN-LSTM
connection harmonization
convolutional neural networks
data mining
different working conditions
distributed energy resources
distributed generation
economic efficiency
electrical power network
energy storage systems
failures
forecasting
global power quality index
grid codes
information recognition
mining industry
multi-headed CNN
obtaining information
power quality
power supply outages
power supply restoration
power systems
prosumer
renewable energy
sensitivity analysis
sliding window
smart grids
solar output
time intervals
virtual power plant
ward algorithm
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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