Assessment of Renewable Energy Resources with Remote Sensing
Martins, Fernando Ramos (editor)
The book “Assessment of Renewable Energy Resources with Remote Sensing" focuses on disseminating scientific knowledge and technological developments for the assessment and forecasting of renewable energy resources using remote sensing techniques. The eleven papers inside the book provide an overview of remote sensing applications on hydro, solar, wind and geothermal energy resources and their major goal is to provide state of art knowledge to contribute with the renewable energy resource deployment, especially in regions where energy demand is rapidly expanding. Renewable energy resources have an intrinsic relationship with local environmental features and the regional climate. Even small and fast environment and/or climate changes can cause significant variability in power generation at different time and space scales. Methodologies based on remote sensing are the primary source of information for the development of numerical models that aim to support the planning and operation of an electric system with a substantial contribution of intermittent energy sources. In addition, reliable data and knowledge on renewable energy resource assessment are fundamental to ensure sustainable expansion considering environmental, financial and energetic security.
Keywordsmetaheuristic; 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
Webshop linkhttps://mdpi.com/books/pdfview ...
Publication date and placeBasel, Switzerland, 2021
Research & information: general