ForewordThe first version of this handbook was developed in response to a growing need by the solar energy industry for a single document addressing the key aspects of solar resource characterization. The solar energy industry has developed rapidly throughout the last few years, and there have been significant enhancements in the body of knowledge in the areas of solar resource assessment and forecasting. Thus, this second version of the handbook was developed from the need to update and enhance the initial version and present the state of the art in a condensed form for all of its users.Although the first version of this handbook was developed by only researchers from the National Renewable Energy Laboratory, this version has additional contributions from an international group of experts primarily from the knowledge that has been gained through participation in the International Energy Agency's Solar Heating and Cooling Programme Task 36 and Task 46.As in the first version, this material was assembled by scientists and engineers who have many decades of combined experience in atmospheric science, radiometry, meteorological data processing, and renewable energy technology development.Readers are encouraged to provide feedback to the authors for future revisions and an expansion of the handbook's scope and content. iv This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. PrefaceAs the world looks for low-carbon sources of energy, solar power stands out as the single most abundant energy resource on Earth. Harnessing this energy is the challenge for this century. Photovoltaics, solar heating and cooling, and concentrating solar power (CSP) are primary forms of energy applications using sunlight. These solar energy systems use different technologies, collect different fractions of the solar resource, and have different siting requirements and production capabilities. Reliable information about the solar resource is required for every solar energy application. This holds true for small installations on a rooftop as well as for large solar power plants. However, solar resource information is of particular interest for large installations, because they require a substantial investment, sometimes exceeding $1 billion in construction costs. Before such a project is undertaken, the best possible information about the quality and reliability of the fuel source must be made available. That is, project developers need to have reliable data about the solar resource available at specific locations, including historic trends with seasonal, daily, hourly, and (preferably) subhourly variability to predict the daily and annual performance of a proposed power plant. Without this data, an accurate financial analysis is not possible.In September 2008, the U.S. Department of Energy (DOE) hosted a meeting of prominent CSP developers and stakeholders. One purpose was to identify areas in which the DOE's CSP program should focus its efforts to help the industry develop an...

International audienceThe direct irradiance received on a plane normal to the sun, called direct normal irradiance (DNI), is of particular relevance to concentrated solar technologies, including concentrating solar thermal plants and concentrated photovoltaic systems. Following various standards from the International Organization for Standardization (ISO), the DNI definition is related to the irradiance from a small solid angle of the sky, centered on the position of the sun. Half-angle apertures of pyrheliometers measuring DNI have varied over time, up to %10°. The current recommendation of the World Meteorological Organization (WMO) for this half-angle is 2.5°. Solar concentrating collectors have an angular acceptance function that can be significantly narrower, especially for technologies with high concentration ratios. The disagreement between the various interpretations of DNI, from the theoretical definition used in atmospheric physics and radiative transfer modeling to practical definitions corresponding to specific measurements or conversion technologies is sig-nificant, especially in the presence of cirrus clouds or large concentration of aerosols. Under such sky conditions, the circumsolar radi-ation—i.e. the diffuse radiation coming from the vicinity of the sun—contributes significantly to the DNI ground measurement, although some concentrating collectors cannot utilize the bulk of it. These issues have been identified in the EU-funded projects MACC-II (Monitoring Atmospheric Composition and Climate-Interim Implementation) and SFERA (Solar Facilities for the European Research Area), and have been discussed within a panel of international experts in the framework of the Solar Heating and Cooling (SHC) program of the International Energy Agency's (IEA's) Task 46 "Solar Resource Assessment and Forecasting". In accordance with these discussions, the terms of reference related to DNI are specified here. The important role of circumsolar radiation is evidenced, and its potential contribution is evaluated for typical atmospheric conditions. For thorough analysis of performance of concentrating solar sys-tems, it is recommended that, in addition to the conventional DNI related to 2.5° half-angle of today's pyrheliometers, solar resource ScienceDirect Solar Energy 110 (2014) 561–577 data sets also report the sunshape, the circumsolar contribution or the circumsolar ratio (CSR)

At any site, the bankability of a projected solar power plant largely depends on the accuracy and general quality of the solar radiation data generated during the solar resource assessment phase. The term “site adaptation” has recently started to be used in the framework of solar energy projects to refer to the improvement that can be achieved in satellite-derived solar irradiance and model data when short-term local ground measurements are used to correct systematic errors and bias in the original dataset. This contribution presents a preliminary survey of different possible techniques that can improve long-term satellite-derived and model-derived solar radiation data through the use of short-term on-site ground measurements. The possible approaches that are reported here may be applied in different ways, depending on the origin and characteristics of the uncertainties in the modeled data. This work, which is the first step of a forthcoming in-depth assessment of methodologies for site adaptation, has been done within the framework of the International Energy Agency Solar Heating and Cooling Programme Task 46 “Solar Resource Assessment and Forecasting”

Solar irradiance nowcasts can be derived with sky images from all sky imagers (ASI) by detecting and analyzing transient clouds, which are the main contributor of intra-hour solar irradiance variability. The accuracy of ASI based solar irradiance nowcasting systems depends on various processing steps. Two vital steps are the cloud height detection and cloud tracking. This task is challenging, due to the atmospheric conditions that are often complex, including various cloud layers moving in different directions simultaneously. This challenge is addressed by detecting and tracking individual clouds. For this, we developed two distinct ASI nowcasting approaches with four or two cameras and a third hybridized approach. These three systems create individual 3-D cloud models with unique attributes 2 including height, position, size, optical properties and motion. This enables us to describe complex multi-layer conditions. In this paper, derived cloud height and motion vectors are compared with a reference ceilometer (height) and shadow camera system (motion) over a 30 day validation period. The validation data set includes a wide range of cloud heights, cloud motion patterns and atmospheric conditions. Furthermore, limitations of ASI based nowcasting systems due to image resolution and image perspective constrains are discussed. The most promising system is found to be the hybridized approach. This approach uses four ASIs and a voxel carving based cloud modeling combined with a cloud segmentation independent stereoscopic cloud height and tracking detection. We observed for this approach an overall mean absolute error of 648 m for the height, 1.3 m/s for the cloud speed and 16.2° for the motion direction.

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