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A new, more accurate and considerably simpler version of the Perez[1] diffuse irradiance model is presented. This model is one of those used currently to estimate short time step (hourly or less) irradiance on tilted planes based on global and direct (or diffuse) irradiance. It has been shown to perform more accurately than other models for a large number of locations worldwide. The key assumptions defining the model remain basically unchanged. These include (1) a description of the sky dome featuring a circumsolar zone and horizon zone superimposed over an isotropic background, and (2) a parameterization of insolation conditions (based on available inputs to the model), determining the value of the radiant power originating from these two zones. Operational modifications performed on the model are presented in a step by step approach. Each change is justified on the basis of increased ease of use and/or overall accuracy. Two years of hourly data on tilted planes from two climatically distinct sites in France are used to verify performance accuracy. The isotropic, Hay and Klucher models are used as reference. Major changes include (1) the simplification of the governing equation by use of reduced brightness coefficients; (2) the allowance for negative coefficients; (3) reduction of the horizon band to an arc-of-great-circle; (4) optimization of the circumsolar region width; and (5) optimization of insolation conditions parameterization

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Abstract-We propose a new formulation for the Linke turbidity coefficient with the objective of removing its dependence upon solar geometry. In the process, we also develop two new simple clear sky models for global and direct normal irradiance. 

Abstract-We present a new simple model capable of exploiting geostationary satellite visible images for the production of site / time-specific global and direct irradiances The new model features new clear sky global and direct irradiance functions, a new cloud-index-to-irradiance index function, and a new global-to-directirradiance conversion model. The model can also exploit operationally available snow cover resource data, while deriving local ground specular reflectance characteristics from the stream of incoming satellite data. Validation against 10 US locations representing a wide range of climatic environments indicates that model performance is systematically improved, compared to current visible-channel-based modeling practice. 

This paper presents an initial validation of a solar radiation service that provides historical, as well as up-to-the-moment solar resource data from satellites, short-term forecasts from cloud motion analysis, and medium term forecasts (up to seven days ahead) from numerical weather prediction models [1].Forecasts are validated for several, climatically distinct regions of the US, investigating single-site performance against ground-truth measurements. We also present an initial analysis of regional performance using satellitederived irradiances as a reference.

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...

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