Comparison of Numerical Weather Prediction Solar Irradiance Forecasts in the US, Canada and Europe
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Available online at www.sciencedirect.com Solar Energy 94 (2013) 305–326 www.elsevier.com/locate/solener Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe Richard Perez a,⇑, Elke Lorenz b, Sophie Pelland c, Mark Beauharnois a, Glenn Van Knowe d, Karl Hemker Jr. a, Detlev Heinemann b, Jan Remund e, Stefan C. Mu¨ller e, Wolfgang Traunmu¨ller f, Gerald Steinmauer g, David Pozo h, Jose A. Ruiz-Arias h, Vicente Lara-Fanego h, Lourdes Ramirez-Santigosa i, Martin Gaston-Romero j, Luis M. Pomares k a Atmospheric Sciences Research Center, The University at Albany, 251 Fuller Rd., Albany, NY 12203, USA b University of Oldenburg, Oldenburg, Germany c Natural Resource Canada, Montreal, Canada d MESO, Inc., Albany, New York, USA e Meteotest, Zurich, Switzerland f Bluesky Wetteranalysen, Attnang-Puchheim, Austria g Austria Solar Innovation Center, Wels, Austria h University of Jaen, Jaen, Spain i CIEMAT, Madrid, Spain j CENER, Sarriguren, Spain k IrSOLaV, Madrid, Spain Received 5 November 2012; received in revised form 8 May 2013; accepted 9 May 2013 Available online 17 June 2013 Communicated by: Associate Editor Frank Vignola Abstract This article combines and discusses three independent validations of global horizontal irradiance (GHI) multi-day forecast models that were conducted in the US, Canada and Europe. All forecast models are based directly or indirectly on numerical weather prediction (NWP). Two models are common to the three validation efforts – the ECMWF global model and the GFS-driven WRF mesoscale model – and allow general observations: (1) the GFS-based WRF- model forecasts do not perform as well as global forecast-based approaches such as ECMWF and (2) the simple averaging of models’ output tends to perform better than individual models. Ó 2013 Elsevier Ltd. All rights reserved. Keywords: Irradiance; Forecast; Validation; Solar resource; Numerical weather prediction 1. Introduction requires reliable forecasts of the expected power produc- tion as a basis for management and operation strategies. Solar power generation is highly variable due its During the last years the contribution of solar power to dependence on meteorological conditions. The integration the electricity supply has been increasing fast leading to of this fluctuating resource into the energy supply system a strong need for accurate solar power predictions (in Germany, for instance, the PV production already exceeds 40% of electrical demand on sunny summer ⇑ Corresponding author. Tel.: +1 5184378751. E-mail address: [email protected] (R. Perez). days). 0038-092X/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.solener.2013.05.005 306 R. Perez et al. / Solar Energy 94 (2013) 305–326 Nomenclature AEMet Spanish Weather Service KSI Kolmogorov–Smirnov test integral ARPS Advanced Multiscale Regional Prediction MASS Mesoscale Atmospheric Simulation System System [model] CDFmeas cumulative measured frequency distribu- MAE mean absolute error tion MBE mean bias error CDFpred cumulative predicted frequency distribu- MOS Model Output Statistics tion MSE mean square error CENER Centro National de Energias Renovables NCEP National Centers for Environmental Pre- (National Renewable Energy Center) diction CIEMAT Centro de Investigaciones Energeticas, NDFD National Digital Forecast Database [mod- Medioambientales y Tecnologicas(Center el] for Research on Energy, Environment and NOAA National Oceanic and Atmospheric Admin- Technology) istration DSWRF downward shortwave radiation flux at the N number of evaluated prediction-measure- surface ment pairs ECMWF European Center for Medium Range Weath- NWP numerical weather prediction er Forecasts [model] RMSE root mean square error GEM Global Environmental Multiscale [model] SURFRAD Surface Radiation Network NOAA GHI global irradiance WRF Weather Research and Forecasting [model] GFS Global Forecast System [model] WRF-ASRC WRF-Model from Atmospheric Sciences HIRLAM High Resolution Limited Area Model Research Center Imas maximum possible irradiance value WRF-AWS WRF Model from AWSTruepower Imeas measured Irradiance WRF-Meteotest WRF Model from Meteotest Ipred predicted irriadiance WRF-UJAEN WRF Model from University of Jaen IEA SHC International Energy Agency Solar Heating and Cooling Programme Following this new and rapidly evolving situation on the horizons. Day-ahead predictions are of particular impor- energy market, substantial research effort is currently being tance for application in the energy market, where day- spent on the development of irradiance and solar power ahead power trading plays a major role in many countries. prediction models, and several models have been proposed This article combines and discusses three independent recently by research organizations as well as by private validations of global horizontal irradiance (GHI) multi- companies. Common operational approaches to short-term day forecast models that were performed in the US, Can- solar radiation forecasting include (1) numerical weather ada and Europe in the framework of the IEA SHC Task prediction (NWP) models that infer local cloud informa- 36 “Solar resource knowledge management” (http://archi- tion – hence, indirectly, transmitted radiation – through ve.iea-shc.org/task36/). Comparing the performance of the dynamic modeling of the atmosphere up to several days different models gives valuable information both to ahead (e.g., see Remund et al., 2008); (2) models using researchers, to rank their approaches and inform further satellite remote sensing or ground based sky measurements model development, and to forecast users, to assist them to infer the motion of clouds and project their impact in the in choosing between different forecasting products. It is future. Earlier contributions by some of the authors have important that a standardized methodology for evalua- shown that satellite-derived cloud motion tends to outper- tion is used for the comparison in order to achieve mean- form NWP models for forecast horizons up to 4–5 h ahead ingful results when comparing different approaches. depending on location (e.g., Perez et al., 2010; Heinemann Therefore, a common benchmarking procedure has been et al., 2006). Short-term forecasting using ground-based set up in the framework of the IEA SHC Task 36. As sky imagery with very high spatial and temporal resolution a basis for the benchmarking we have prepared several is suitable for intra-hour forecasting (Chow et al., 2011); ground measurement data sets covering different climatic (3) statistical time series models based on measured irradi- regions and a common set of accuracy measures has been ance data are applied for very short term forecasting in the identified. range of minutes to hours (e.g., see Pedro and Coimbra, The paper first gives an overview of the different fore- 2012). In this paper we focus our attention on solar radia- casting approaches. Then we present the ground measure- tion forecasts based on NWP models which are most ment datasets used for the validation. Next, the concept of appropriate for day-ahead and multi-day forecast evaluation is introduced, and finally, we provide the results R. Perez et al. / Solar Energy 94 (2013) 305–326 307 of the forecast comparison along with a short discussion 10. Forecasts based on meteorologists’ cloud cover fore- and conclusions. casts by Bluesky (BLUESKY-meteorologists). The first two models are directly based on global (plan- 2. Forecast models etary) NWP systems, respectively GEM, and ECMWF. The native time step of the regional configuration of the The evaluation includes forecasts based on global, mul- GEM model and its ground resolution are 7.5 min and tiscale and mesoscale NWP models. Hourly site-specific 15 km, respectively. GEM forecasts of downward short- forecasts are derived from direct NWP model output with wave radiation flux at the surface (DSWRF) originating different methods ranging from simple averaging and inter- at 00:00Z and 12:00Z were de-archived by the Canadian polation techniques to advanced statistical postprocessing Meteorological Centre at an hourly time step for this anal- tools and meteorologists’ interpretation to combine the ysis. The de-archived forecasts cover North America and output of various NWP models. The models considered adjacent waters. As described by Pelland et al. (2011), the for this evaluation are listed below, along with the acro- GEM solar forecasts were postprocessed by taking an aver- nyms that will be used to present results: age of the irradiance forecasts over a square region cen- tered on the location of each site used in the validation. 1. The Global Environmental Multiscale (GEM) model The size of this square grid was optimized for each station from Environment Canada in its regional determinis- by selecting a size that minimized forecast root mean tic configuration (Mailhot et al., 2006). square error during a 1 year training period prior to the 2. An application of the European Centre for Medium- evaluation period used here. Range Weather Forecasts (ECMWF) model (Lorenz ECMWF irradiance forecasts used here had a temporal et al., 2009a,b). resolution of 3 h and a spatial resolution of 25 km. The 3. Several versions of the Weather Research and Fore- ECMWF site-specific, hourly data prepared for the present casting (WRF) model (Skamarock et al., 2005, analysis according to Lorenz et al. (2009b) are obtained via 2008) initialized with Global Forecast System time interpolation of the 3-hourly global clear sky indices.