Bidirectional irradiance transposition based on the Perez model

Yang, Di; Ye, Zhen; Nobre, A.; Du, Hui; Walsh, Wilfred M.; Lim, Lihong Idris; Reindl, Thomas

doi:10.1016/j.solener.2014.10.006

Cited by 37 publications

(15 citation statements)

References 36 publications

(44 reference statements)

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“…In terms of used method and results, we would like to substantiate the choice for our method by one of the conclusions in [15] (#5: "Elaborate decomposition models do not out-perform simpler models") as it seems to align quite well with our method and results. For our purpose of using the existing PV-fleet as a sensor network, the thus shown uncertainties are acceptable.…”

Section: Comparison To Other Studiesmentioning

confidence: 68%

“…In Yang et al [15], reconstruction of GHI from sensors inclined at various inclination angles is reported using the Perez transposition model. Furthermore, Killinger et al [16] present the power projection model that aims to describe PV performance relative to other (nearby) PV-systems while incorporating the different orientation and tilt through reverse iteration of the Perez DIRINT model, among several other models.…”

Section: Inverse Photovoltaic Yield Model For Global Horizontal Irradmentioning

confidence: 99%

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Inverse photovoltaic yield model for global horizontal irradiance reconstruction

Elsinga

Sark

Ramaekers

2017

Energy Science & Engineering

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This article describes the method of deriving Global Horizontal Irradiance (GHI) from combining power measurements with static meta data (tilt, orientation, brand/type) of rooftop photovoltaic (PV)-systems. This inverse PV model implements a forward yield model that is based on a modified Orgill and Hollands decomposition model and the Perez transposition model for irradiance. The forward as well as the inverse PV model were validated with DC power measurements of four different mono-and polycrystalline modules combined with weather station data (2 minute resolution data over a period ranging from the 11th of June through the 24th of August 2014). The bias-corrected forward PV model shows a best (r)RMSE of 16.0 W (15.1%) with a (r)MBE of −1.67 W (−1.57%) for one of the polycrystalline modules. The bias-corrected inverse PV model shows a best (r)RMSE of 65.6 Wm −2 15.1% with a (r)MBE of 0.994 Wm −2 (0.229%) for one of the polycrystalline modules. Similar results were obtained for the three other modules. 227

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Section: Comparison To Other Studiesmentioning

confidence: 68%

Section: Inverse Photovoltaic Yield Model For Global Horizontal Irradmentioning

confidence: 99%

Inverse photovoltaic yield model for global horizontal irradiance reconstruction

Elsinga

Sark

Ramaekers

2017

Energy Science & Engineering

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“…Note that Eqs. (7) and (8) slightly differ from Yang et al (2014) due to the change in the column vector…”

Section: Multi-pyranometer Approachmentioning

confidence: 99%

“…The aim of the present study is to (1) evaluate the tilt to horizontal irradiance conversion when using for model input G t measurements recorded in angular configurations similar to those encountered in Belgian PV systems installations (e.g., with tilt angle as great as 50.79 • ) and, (2) determine if, as suggested by Yang et al (2014), the use of a multipyranometer system could improve the conversion accuracy. The selection of the decomposition and transposition models used in our calculations is based on previous evaluation of popular decomposition and transposition models performance in Uccle by Demain et al ( , 2016 and Bertrand et al (2015).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of various procedures transposing global tilted irradiance to horizontal surface irradiance

Housmans

Bertrand

2017

Adv. Sci. Res.

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Abstract. Many transposition models have been proposed in the literature to convert solar irradiance on the horizontal plane to that on a tilted plane. The inverse process, i.e. the conversion from tilted to horizontal is investigated here based upon seven months of in-plane global solar irradiance measurements recorded on the roof of the Royal Meteorological Institute of Belgium's radiation tower in Uccle (Longitude 4.35 • E, Latitude 50.79 • N). Up to three pyranometers mounted on inclined planes of different tilts and orientations were involved in the inverse transposition process. Our results indicate that (1) the tilt to horizontal irradiance conversion is improved when measurements from more than one tilted pyranometer are considered (i.e. by using a multipyranometer approach) and (2) the improvement from using an isotropic model to anisotropic models in the inverse transposition problem is not significant.

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“…In addition, reference cells are often installed at plane of 329 array to monitor the PV performance. These tilted data can also be utilized in forecasting by converting 330 them to GHI using inverse transposition models, such as the ones shown in (Yang et al, 2014b(Yang et al, , 2013a. …”

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confidence: 99%

Very short term irradiance forecasting using the lasso

Ye²,

et al. 2015

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We find an application of the lasso (least absolute shrinkage and selection operator) in sub-5-minute solar irradiance forecasting using a monitoring network. Lasso is a variable shrinkage and selection method for linear regression. In addition to the sum of squares error minimization, it considers the sum of 1 -norms of the regression coefficients as penalty. This bias-variance trade-off very often leads to better predictions.One second irradiance time series data are collected using a dense monitoring network in Oahu, Hawaii. As clouds propagate over the network, highly correlated lagged time series can be observed among station pairs. Lasso is used to automatically shrink and select the most appropriate lagged time series for regression. Since only lagged time series are used as predictors, the regression provides true out-of-sample forecasts. It is found that the proposed model outperforms univariate time series models and ordinary least squares regression significantly, especially when training data are few and predictors are many. Very short-term irradiance forecasting is useful in managing the variability within a central PV power plant.

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Bidirectional irradiance transposition based on the Perez model

Cited by 37 publications

References 36 publications

Inverse photovoltaic yield model for global horizontal irradiance reconstruction

Inverse photovoltaic yield model for global horizontal irradiance reconstruction

Evaluation of various procedures transposing global tilted irradiance to horizontal surface irradiance

Very short term irradiance forecasting using the lasso

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