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Advanced Operation and Maintenance in Solar Plants, Wind Farms and Microgrids
| Advanced Operation and Maintenance in Solar Plants, Wind Farms and Microgrids |
| Autore | Hernández-Callejo Luis |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (366 p.) |
| Soggetto topico |
Research & information: general
Physics |
| Soggetto non controllato |
wind turbine
electric generator spectral analysis fault diagnosis photovoltaic power forecasting data-driven deep learning variational autoencoders RNN angle swinging grid frequency oscillations electromechanical system inertial masses microgrids coordination protection distributed generation photovoltaic resources DigSILENT photovoltaic module defect detection power plant efficiency thermal image photovoltaic aging dark I-V curves bidirectional power inverter online distributed measurement of dark I-V curves sustainability compressive strength Bolomey formula sustainable concrete glass powder solar cell solar panel parameter extraction analytical Lambert W-function spacecraft solar panels I-V curve modeling wind power non-conventional renewable energy forecasting energy bands combinatorial optimization deep learning (DL) unmanned aerial vehicle (UAV) photovoltaic (PV) systems image-processing image segmentation semantic segmentation faults diagnostic artificial intelligence unbalanced datasets synthetic data artificial neural network based MPPT hybrid boost converter renewable energies solar power system microgrid control system storage system primary control photovoltaic (PV) plants coverage path planning (CPP) corrosion monitoring FPGA offshore wind turbines ultrasound thickness loss SCADA visualisation software wind-turbine windfarm cross-platform HMI GUI corrosion monitoring photovoltaic systems expected energy models fleet-scale lasso regression performance modeling machine learning fault location in photovoltaic arrays failure modes simulation fault detection criterion adaptive protection distributed power generation power distribution power system protection |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566457603321 |
Hernández-Callejo Luis
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Energy Data Analytics for Smart Meter Data
| Energy Data Analytics for Smart Meter Data |
| Autore | Reinhardt Andreas |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (346 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
smart grid
nontechnical losses electricity theft detection synthetic minority oversampling technique K-means cluster random forest smart grids smart energy system smart meter GDPR data privacy ethics multi-label learning Non-intrusive Load Monitoring appliance recognition fryze power theory V-I trajectory Convolutional Neural Network distance similarity matrix activation current electric vehicle synthetic data exponential distribution Poisson distribution Gaussian mixture models mathematical modeling machine learning simulation Non-Intrusive Load Monitoring (NILM) NILM datasets power signature electric load simulation data-driven approaches smart meters text convolutional neural networks (TextCNN) time-series classification data annotation non-intrusive load monitoring semi-automatic labeling appliance load signatures ambient influences device classification accuracy NILM signature load disaggregation transients pulse generator smart metering smart power grids power consumption data energy data processing user-centric applications of energy data convolutional neural network energy consumption energy data analytics energy disaggregation real-time smart meter data transient load signature attention mechanism deep neural network electrical energy load scheduling satisfaction Shapley Value solar photovoltaics review deep learning deep neural networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557645803321 |
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Reinhardt Andreas
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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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Industrial Applications: New Solutions for the New Era
| Industrial Applications: New Solutions for the New Era |
| Autore | de Sales Guerra Tsuzuki Marcos |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (270 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
induction machines
electrical machines vector control SVPWM modulation frequency inverter artificial intelligence photovoltaics fault detection machine learning operation and maintenance renewable energy water-in-crude oil emulsion water content ultrasound propagation velocity exoskeletons test bench industry benchmarking microgrid model-based systems engineering service systems goal-oriented requirements engineering safety instrumented system ventricular assist device Bayesian network Petri net control strategy UAV fuzzy PID controller ROS Industry 4.0 database data models big data and analytics asset administration shell MLOps digital twin IoT prediction coordinate metrology optical scanning noise reduction digital manufacturing integrated inspection system data analytics uncertainty convolutional neural networks warehouse management image classification ensemble learning synthetic data depth image electrical maintenance COVID-19 thermography fever computer vision intelligent systems |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Industrial Applications |
| Record Nr. | UNINA-9910566468403321 |
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de Sales Guerra Tsuzuki Marcos
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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