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Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications
| Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications |
| Autore | Vitelli Massimo |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (280 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
adaptive neuro-fuzzy inference systems
ANFIS artificial neural network artificial neural networks clear sky irradiance clustering-based PV fault detection COA complex network analysis data fusion deterioration deterministic optimization algorithm diffractive grating diffractive optical element double flames generation (DFG) strategy duty cycle environmental parameters fault prognosis feed-forward neural networks finite difference time domain genetic algorithm global horizontal irradiance global optimization gradient descent hot spot image processing implicit model solution integrated energy systems linear approximation long short-term memory LSTM cell machine learning mathematical modeling maximum power point tracking metaheuristic optimization algorithm moth-flame optimization MPPT algorithm multiple regression model national power system optical modelling parameter extraction partial shading particle swarm optimization-artificial neural networks performances evaluation persistent predictor photovoltaic array photovoltaic model photovoltaic module photovoltaic plants photovoltaic power prediction photovoltaic system photovoltaic systems photovoltaics publicly available weather reports PV fleet PV power prediction PVs power output forecasting recurrent neural networks renewable energy self-imputation sensor network series-parallel single stage grid connected systems single-diode model smart energy management solar cell optimization Solar cell parameters solar concentrator solar irradiation spectral beam splitting statistical method sustainable development thermal image two-diode model unsupervised learning |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557297703321 |
Vitelli Massimo
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computational Intelligence in Photovoltaic Systems / Emanuele Ogliari, Sonia Leva
| Computational Intelligence in Photovoltaic Systems / Emanuele Ogliari, Sonia Leva |
| Autore | Ogliari Emanuele |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (180 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
artificial neural network
online diagnosis genetic algorithm renewable energy unit commitment photovoltaic panel power forecasting metaheuristic monitoring system embedded systems firefly algorithm tracking system MPPT algorithm integrated storage day-ahead forecast solar radiation prototype model artificial neural networks parameter extraction thermal image thermal model solar cell PV cell temperature evolutionary algorithms uncertainty battery harmony search meta-heuristic algorithm single-diode photovoltaic model symbiotic organisms search photovoltaics tilt angle smart photovoltaic system blind orientation photovoltaic particle swarm optimization analytical methods computational intelligence statistical errors ensemble methods solar photovoltaic electrical parameters demand response metaheuristic algorithm |
| ISBN |
9783039210992
3039210998 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910674025103321 |
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Ogliari Emanuele
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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