Jakoplić et al., 2024 - Google Patents
Location-specific optimization of photovoltaic forecasting models using fine-tuning techniquesJakoplić et al., 2024
View PDF- Document ID
- 703194448387096725
- Author
- Jakoplić A
- Franković D
- Bulat H
- Rojnić M
- Publication year
- Publication venue
- IEEE access
External Links
Snippet
The global energy landscape is increasingly shaped by renewable energy sources, particularly photovoltaic systems, which are influenced by economic, environmental and geopolitical factors. Technological advances and political incentives have reduced the cost …
- 238000000034 method 0 title description 27
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
- G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/08—Adaptations of balloons, missiles, or aircraft for meteorological purposes; Radiosondes
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/02—Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover, wind speed
- G01W1/06—Instruments for indicating weather conditions by measuring two or more variables, e.g. humidity, pressure, temperature, cloud cover, wind speed giving a combined indication of weather conditions
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Barbieri et al. | Very short-term photovoltaic power forecasting with cloud modeling: A review | |
Haupt et al. | Variable generation power forecasting as a big data problem | |
Dev et al. | Solar irradiance forecasting using triple exponential smoothing | |
Tooke et al. | Tree structure influences on rooftop-received solar radiation | |
Nobre et al. | PV power conversion and short-term forecasting in a tropical, densely-built environment in Singapore | |
Kato | Prediction of photovoltaic power generation output and network operation | |
Mathe et al. | PVNet: A LRCN architecture for spatio-temporal photovoltaic PowerForecasting from numerical weather prediction | |
Li | Using GIS and remote sensing techniques for solar panel installation site selection | |
Ayodele et al. | Solar energy harvesting on building’s rooftops: A case of a Nigeria cosmopolitan city | |
Adjiski et al. | Assessment of the solar energy potential of rooftops using LiDAR datasets and GIS based approach | |
Alonso et al. | Sky camera imagery processing based on a sky classification using radiometric data | |
Santos et al. | Solar potential analysis in Lisbon using LiDAR data | |
Manandhar et al. | Short-term solar radiation forecast using total sky imager via transfer learning | |
Yuzer et al. | Deep learning model for regional solar radiation estimation using satellite images | |
Trigo-González et al. | Photovoltaic power electricity generation nowcasting combining sky camera images and learning supervised algorithms in the Southern Spain | |
Vega-Garita et al. | A practical method for considering shading on photovoltaics systems energy yield | |
Lorenz et al. | Forecasting solar radiation and photovoltaic power | |
Abouelaziz et al. | Photogrammetry and deep learning for energy production prediction and building-integrated photovoltaics decarbonization | |
Jakoplić et al. | Location-specific optimization of photovoltaic forecasting models using fine-tuning techniques | |
Kebir et al. | Best-effort algorithm for predicting cloud motion impact on solar PV power systems production | |
Barbieri et al. | A comparative study of clear-sky irradiance models for Western Australia | |
Xu et al. | A stochastic framework for solar irradiance forecasting using condition random field | |
Fomenko et al. | Review of Ultra-Short-Term Solar Radiation Prediction Methods | |
Niccolai et al. | Irradiance Nowcasting by Means of Deep-Learning Analysis of Infrared Images. Forecasting 2022, 4, 338–348 | |
Stoop | Data Driven Understanding of Energy-Meteorological Variability and its Impact on Energy System Operations |