2013
DOI: 10.1016/j.renene.2013.06.008
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Evaluation and improvement of empirical models of global solar irradiation: Case study northern Spain

Abstract: 8This paper presents a new methodology to build parametric models to estimate global solar 9 irradiation adjusted to specific on-site characteristics based on the evaluation of variable im-

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Cited by 46 publications
(38 citation statements)
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“…Another different alternative resulted from the cloud cover measurement [12]. For a more detailed description of parametric models, the authors refer to their previous study [13]. This research concluded that some of the drawbacks of parametric models were the complexity of variable selection for model tuning and high mean absolute errors, ranging between 2.2-3.3 MJ/m 2 day.…”
Section: Introductionmentioning
confidence: 98%
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“…Another different alternative resulted from the cloud cover measurement [12]. For a more detailed description of parametric models, the authors refer to their previous study [13]. This research concluded that some of the drawbacks of parametric models were the complexity of variable selection for model tuning and high mean absolute errors, ranging between 2.2-3.3 MJ/m 2 day.…”
Section: Introductionmentioning
confidence: 98%
“…This methodology was proven useful for developing a general (non-locally dependent) model for solar irradiation estimation, which was implemented in a case of study in Spain, under different climates and on diverse terrain. The results are compared with the classic parametric models [5,13].…”
Section: Introductionmentioning
confidence: 99%
“…The knowledge of seasonal and temporal variations allow its use in studies on evapotranspiration, optimization of water demand in irrigation, crop forecasting, agricultural planning, climate change, development of energy technology systems (thermal and photovoltaic), food preservation, buildings and ambiance, among others (Antonanzas-Torres et al, 2013;Dumas et al, 2015;Huber et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…In this context, the high cost of measuring solar irradiation with a pyranometer and the scarcity of long, reliable datasets for specific locations has encouraged the use of simplified estimators, including models based on air temperature, air humidity, precipitation, sky cover (clouds), sunshine fraction, linear regression, geostationary satellite data, stochastic models, artificial neural networks, among others (Gueymard & Myers, 2009;Antonanzas-Torres et al, 2013;Bojanowski et al, 2013;Veeraboina & Guduri, 2014;Yacef et al, 2014;Dumas et al, 2015;Teke et al, 2015).…”
Section: Introductionmentioning
confidence: 99%
“…Ground measurements are the first choice to describe the irradiance levels at a certain location, providing high quality data, depending on adequate maintenance of the instruments used in the measuring campaign [3]. When no on-site measurements are available, other techniques should be applied, such as empirical models based on meteorological variables like temperature or sunshine duration [3,4] or models based on reanalysis and retrospective weather prediction models [5,6]. Satellite-based models have become a very powerful tool for estimating the solar resource at high and uniform spatial resolution (typically a few kilometres) and temporal resolution (hourly or better) over large geographical areas [3,7].…”
Section: Introductionmentioning
confidence: 99%