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Machine Learning and Data Mining Applications in Power Systems
| Machine Learning and Data Mining Applications in Power Systems |
| Autore | Leonowicz Zbigniew |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (314 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology Energy industries & utilities |
| Soggetto non controllato |
virtual power plant (VPP)
power quality (PQ) global index distributed energy resources (DER) energy storage systems (ESS) power systems long-term assessment battery energy storage systems (BESS) smart grids conducted disturbances power quality supraharmonics 2-150 kHz Power Line Communications (PLC) intentional emission non-intentional emission mains signalling virtual power plant data mining clustering distributed energy resources energy storage systems short term conditions cluster analysis (CA) nonlinear loads harmonics, cancellation, and attenuation of harmonics waveform distortion THDi low-voltage networks optimization techniques different batteries off-grid microgrid integrated renewable energy system cluster analysis K-means agglomerative ANFIS fuzzy logic induction generator MPPT neural network renewable energy variable speed WECS wind energy conversion system wind energy frequency estimation spectrum interpolation power network disturbances COVID-19 time-varying reproduction number social distancing load profile demographic characteristic household energy consumption demand-side management energy management time series Hidden Markov Model short-term forecast sparse signal decomposition supervised dictionary learning dictionary impulsion singular value decomposition discrete cosine transform discrete Haar transform discrete wavelet transform transient stability assessment home energy management binary-coded genetic algorithms optimal power scheduling demand response Data Injection Attack machine learning critical infrastructure smart grid water treatment plant power system |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576877503321 |
Leonowicz Zbigniew
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Sustainable Energy Systems: Efficiency and Optimization
| Sustainable Energy Systems: Efficiency and Optimization |
| Autore | Brent Alan |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (182 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
renewable portfolio standards
emissions trading scheme optimal operational strategy generation expansion plan energy planning public institution passive energy CRITIC method urban metabolism household energy metabolism household energy metabolism assessment methods household energy consumption energy systems optimisation exergy analysis cumulative-exergy consumption minimisation multi-energy systems energy-system design municipal energy systems internet of things IoT applications energy efficiency energy in buildings smart energy systems smart grid flexible demand energy storage concentrating solar power geographic information systems potential assessment renewable energy solar thermal South Africa CSP energy and economy transition decision making international energy security risk index multiple regression analysis multicollinearity test multicollinearity test with variance inflation factors renewable energy systems microgrids optimal expansion planning energy resilience resilient energy systems critical loads electric vehicles techno-economic analysis HOMER Pro New Zealand |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Sustainable Energy Systems |
| Record Nr. | UNINA-9910557616503321 |
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Brent Alan
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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