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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 online resource (244 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
artificial neural networks
Baltic area climate cloud cloud coverage cloud detection coastal wind measurements coastline computational design method convection CSP plants data processing digitized image processing electrical resistivity tomography extreme value analysis feature engineering feature importance forecasting geophysical prospecting geothermal energy GES-CAL software global radiation graphical user interface software Hazaki Oceanographical Research Station hydropower reservoir image processing lake breeze influence light gradient boosting machine machine learning machine learning techniques metaheuristic multistep-ahead prediction parameter extraction passive design strategy photovoltaic power plant plan position indicator point cloud data potential well field location remote sensing remote sensing data acquisition renewable energy resource assessment and forecasting satellite scanning LiDAR scatterometer shading envelopes sky camera smart island solar energy solar energy resource solar irradiance enhancement solar irradiance estimation solar irradiance forecasting solar photovoltaic solar radiation forecasting statistical analysis surface solar radiation time domain electromagnetic method total sky imagery velocity volume processing voxel-design approach whale optimization algorithm wind speed |
| 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 / Charlotte Hasager, Mikael Sjöholm
| Remote Sensing of Atmospheric Conditions for Wind Energy Applications / Charlotte Hasager, Mikael Sjöholm |
| 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 |
9783038979432
3038979430 |
| 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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