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Large Grid-Connected Wind Turbines
| Large Grid-Connected Wind Turbines |
| Autore | Muyeen S M |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (212 p.) |
| Soggetto non controllato |
doubly-fed induction generator
fault current limiters power system power smoothing fault characteristics prediction intervals wind forecast PI controller transmission line wake effect real fault cases reliability of electricity supplies load frequency control optimization reserve power battery energy storage system wind turbine allocation primary frequency control low voltage ride through (LVRT) de-loading fault ride-through fault diagnosis and isolation fractional order proportional-integral-differential controller multi-objective artificial bee colony algorithm Fault Ride Through (FRT) distance protection droop curve Distribution Static VAr Compensator(D-SVC) Distributed-Flexible AC Transmission system (D-FACTS) rotor inertia power wind turbine LPV observer doubly fed induction generator (DFIG) squirrel cage induction generator (SCIG) wind farm optimal control fuzzy logic controller (FLC) wind power forecasting wavelet neural network DFIG-based wind farm permanent magnet synchronous generator automatic generation control series dynamic braking resistor hardware-in-the-loop superconductor Distribution Static Synchronous Compensator (D-STATCOM) control wind turbine kinetic energy storage multiple sensor faults large-scale wind farm |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346691203321 |
Muyeen S M
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management
| Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management |
| Autore | Kisi Ozgur |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (238 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
groundwater
artificial intelligence hydrologic model groundwater level prediction machine learning principal component analysis spatiotemporal variation uncertainty analysis hydroinformatics support vector machine big data artificial neural network nitrogen compound nitrogen prediction prediction models neural network non-linear modeling PACF WANN SVM-LF SVM-RF Govindpur streamflow forecasting Bayesian model averaging multivariate adaptive regression spline M5 model tree Kernel extreme learning machines South Korea uncertainty sustainability prediction intervals ungauged basin streamflow simulation satellite precipitation atmospheric reanalysis ensemble modeling additive regression bagging dagging random subspace rotation forest flood routing Muskingum method extension principle calibration fuzzy sets and systems particle swarm optimization EEFlux irrigation performance CWP water conservation NDVI water resources Daymet V3 Google Earth Engine improved extreme learning machine (IELM) sensitivity analysis shortwave radiation flux density sustainable development |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557448103321 |
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Kisi Ozgur
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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