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Assessment of Renewable Energy Resources with Remote Sensing
| Assessment of Renewable Energy Resources with Remote Sensing |
| Autore | Martins Fernando Ramos |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (244 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
metaheuristic
parameter extraction solar photovoltaic whale optimization algorithm cloud detection digitized image processing artificial neural networks solar irradiance estimation solar irradiance forecasting solar energy sky camera remote sensing CSP plants coastal wind measurements scanning LiDAR plan position indicator velocity volume processing Hazaki Oceanographical Research Station cloud coverage image processing total sky imagery geothermal energy geophysical prospecting time domain electromagnetic method electrical resistivity tomography potential well field location GES-CAL software smart island solar radiation forecasting light gradient boosting machine multistep-ahead prediction feature importance voxel-design approach shading envelopes point cloud data computational design method passive design strategy lake breeze influence hydropower reservoir solar irradiance enhancement solar energy resource wind speed extreme value analysis scatterometer feature engineering forecasting graphical user interface software machine learning photovoltaic power plant surface solar radiation global radiation satellite Baltic area coastline cloud convection climate renewable energy resource assessment and forecasting remote sensing data acquisition data processing statistical analysis machine learning techniques |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557427903321 |
Martins Fernando Ramos
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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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Remote Sensing of Atmospheric Conditions for Wind Energy Applications
| Remote Sensing of Atmospheric Conditions for Wind Energy Applications |
| Autore | Hasager Charlotte |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (290 p.) |
| Soggetto non controllato |
complex flow
Floating Lidar System (FLS) mesoscale wind energy resources variational analysis wind turbine wind sensing wind energy wind gusts wake wind structure complex terrain global ocean remote sensing forecasting detached eddy simulation five-minute ahead wind power forecasting tropical cyclones fetch effect aerosol vertical Light Detection and Ranging range gate length resource assessment field experiments remote sensing optical flow turbulence atmospheric boundary layer Doppler Wind Lidar offshore empirical equation Lidar WindSAT coastal wind measurement offshore wind speed forecasting Doppler wind lidar Doppler wind wind lidar cross-correlation QuikSCAT wind resource assessment detecting and tracking single-particle gust prediction NWP model velocity-azimuth-display algorithm lidar-assisted control (LAC) Doppler lidar motion estimation power performance testing lidar large-eddy simulations wind farm coherent Doppler lidar wake modeling probabilistic forecasting control NeoWins wind turbine controls impact prediction wind turbine wake Hazaki Oceanographical Research Station VAD virtual lidar Doppler radar IEA Wind Task 32 ASCAT wind atlas turbulence intensity |
| ISBN | 3-03897-943-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346674903321 |
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Hasager Charlotte
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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