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Structural Prognostics and Health Management in Power & Energy Systems
| Structural Prognostics and Health Management in Power & Energy Systems |
| Autore | Wang Dong |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (218 p.) |
| Soggetto non controllato |
empirical mode decomposition
underground powerhouse sensitivity analysis DNN fault detection neural networks structural health monitoring analysis mode decomposition dynamic analysis of the structure residual useful life renewable energy remaining useful life retrofitting activities wind turbine blade optimized deep belief networks strain prediction offshore wind turbines low frequency tail fluctuation oil and gas platforms supporting vector machine (SVM) wave–structure interaction (WSI) sifting stop criterion probabilistic analyses of stochastic processes and frequency mode mixing non-probabilistic reliability index data-driven prognostics turbine blisk wind turbines supervisory control and data acquisition system fuzzy safety criterion analysis-empirical mode decomposition rotation of hydraulic generator life cycle cost health monitoring reliability wavelet decomposition weighted regression similarity-based approach vibration transmission mechanism wind and wave analysis full-scale static test deep learning multioperation condition extremum surface response method lithium-ion battery vibration test lateral-river vibration operational modal analysis dynamic analysis regeneration phenomenon machine learning prognostic and Health Management offshore structures NAR neural network techno-economic assessments stochastic subspace identification vertical axis wind turbine dynamic fuzzy reliability analysis |
| ISBN | 3-03921-767-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910372782603321 |
Wang Dong
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| MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Wind Power Integration into Power Systems: Stability and Control Aspects
| Wind Power Integration into Power Systems: Stability and Control Aspects |
| Autore | Meegahapola Lasantha |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (264 p.) |
| Soggetto topico |
Technology: general issues
Energy industries & utilities |
| Soggetto non controllato |
DFIG
ES virtual inertia control capacity allocation fuzzy logic controller wind power generation multi-model predictive control fuzzy clustering virtual synchronous generator doubly fed induction generator sub-synchronous resonance impedance modeling renewable energy sources (RESs) regional RoCoF model-based operational planning linear sensitivity-based method (LSM) cumulant-based method (CBM) collaborative capacity planning distributed wind power (DWP) energy storage system (ESS) optimization variable-structure copula Reynolds-averaged Navier-Stokes method wind turbine wake model 3D aerodynamic model turbulence model correction modules hybrid prediction model wavelet decomposition long short-term memory scenario analysis weak grids full-converter wind active power output control parameters subsynchronous oscillation eigenvalue analysis doubly fed induction generator (DFIG) wind generation frequency control artificial neural network (ANN) error following forget gate-based long short-term memory ultra-short-term prediction wind power load frequency control (LFC) wind farm particle swarm optimization kinetic energy inertial response low inertia the center of inertia frequency response metrics wind integration PSS/E FORTRAN electromechanical dynamics FCWG dynamics strong interaction electromechanical loop correlation ratio (ELCR) FCWG dynamic correlation ratio (FDCR) quasi- electromechanical loop correlation ratio (QELCR) permanent magnet synchronous generator (PMSG) supercapacitor energy storage (SCES) rotor overspeed control low voltage ride through (LVRT) capacity configuration of SCES |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Wind Power Integration into Power Systems |
| Record Nr. | UNINA-9910557761903321 |
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Meegahapola Lasantha
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||