2008
DOI: 10.1016/j.solener.2008.04.008
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Spatial insolation models for photovoltaic energy in Canada

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Cited by 37 publications
(33 citation statements)
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“…Accurate estimation of spatially continuous long-term solar radiation data is necessary information for solar electricity projects, building design processes, irrigation scheduling strategies, hydrologic models, crop simulation models, and different land management techniques such as reforestation. Collecting radiation data in most countries is costly, difficult, and involves uncertainties, so solar radiation data are usually only recorded by a few meteorological stations [3]. For this reason, over the last few decades, many models have been developed for representing the spatio-temporal variability of global solar radiation that are applied in design and planning of solar energy systems, including recent satellitebased models, or predictive models based on correlations of solar radiation with sunshine duration, air temperature, cloud observations, and other weather data (Table 1).…”
Section: Introductionmentioning
confidence: 99%
“…Accurate estimation of spatially continuous long-term solar radiation data is necessary information for solar electricity projects, building design processes, irrigation scheduling strategies, hydrologic models, crop simulation models, and different land management techniques such as reforestation. Collecting radiation data in most countries is costly, difficult, and involves uncertainties, so solar radiation data are usually only recorded by a few meteorological stations [3]. For this reason, over the last few decades, many models have been developed for representing the spatio-temporal variability of global solar radiation that are applied in design and planning of solar energy systems, including recent satellitebased models, or predictive models based on correlations of solar radiation with sunshine duration, air temperature, cloud observations, and other weather data (Table 1).…”
Section: Introductionmentioning
confidence: 99%
“…Several spatial interpolation methods can be found in the literature, such as natural neighbour interpolation (Dinis et al 2009), inverse functions of distance (Pons and Ninyerola 2008), multiple linear regression (Daly et al 1994), splines (McKenney et al 2008) or kriging (Ruiz-Arias et al 2011). The results of different studies, which compare deterministic and stochastic methods for the interpolation of environmental variables, show that the kriging method presents considerable advantages over the deterministic interpolation procedures (Luo et al 2008).…”
Section: Introductionmentioning
confidence: 99%
“…In most cases, insolation is the result of the interactions between all these factors (Duffie & Beckman, 1991;Hofierka & Suri, 2002). To make modeling of solar radiation even more challenging, insolation data sets are expensive to collect and in Canada, as well as in other countries (with the exception of the United States and the European Union), few meteorological stations record such data (Hofierka & Suri, 2002;McKenney et al, 2008). Approaches used to determine solar radiation over a large geographic regions often derive spatial databases of solar radiation using different interpolation techniques e.g.…”
Section: Introductionmentioning
confidence: 99%
“…Those for Africa and selected developing countries were accomplished upon funding from the European Commission 4 and the United Nations Environment Program (UNEP) 5 respectively and they mostly appear on the web as simple images, which are of limited value for further regional research and analysis. For Canada, insolation maps exist in the Natural Resources Canada's Photovoltaic System Design Manual, NASA SSE worldwide maps and at the Great Lakes Forestry Centre (McKenney et al, 2008). Again these resources suffer from low resolution with the finest being 300 arc seconds (~ 10 km), which is much larger than any existing solar farm.…”
Section: Introductionmentioning
confidence: 99%
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