The locations of the measurement sites are shown in Fig. The ground-based measurements are at 10 different sites for the regression and 9 independent sites for validation purposes. Sol. The algorithm performs the process at every location within the domain at each time step and outputs the power estimate into a dataset. The map in Fig. Both the SURFRAD and ISIS sites have a measurement frequency of 3 min. Res. Additionally, the vertical bars continue to the 10% and 90% percentiles. In total, three years of data (2006–08) at 10 training and 9 validation sites were concatenated for the proposed method. TSI is the total solar irradiance measured at the top of the Earth's atmosphere. Climate Change, 6, 526–531, doi:10.1038/nclimate2921. We’ve found SolarAnywhere ® Data to be technically rigorous and provide deeply independent site irradiance assessments. The 3 Main Types Of Solar Irradiance. Another salient feature that all three irradiance species have in common is that the estimates appear to be slightly smoother than the measurements, but retain the general shape throughout the 31-day period (which continues over the entire 3-yr period evaluated). The POWER API currently only provides the Solar Irradiance data at the climatology temporal level (see Methodology. One SURFRAD and one ISIS site were retained to perform an “initial” validation of the procedure at two independent sites excluded from the training set. Augustine, J. The Southwest has the greatest solar resource while the Northwest and East have the least. 11 shows how clear the skies are over the desert Southwest, and how the Gulf Coast region is dominated by large amounts of DIF versus DNI, which means it would be suitable for solar PV (as GHI is a relatively good resource there), but not as suitable for CSP. Solar irradiance data (GHI, DNI, Diffuse) PV power modelling (Rooftop or Utility Scale) Global coverage (all six major continents) at 1-2km resolution; Rapid update (new forecasting data every 5-15 minutes) Proprietary cloud & aerosol detection (tracking smoke, dust, haze) Probabilistic forecasting outputs The model performs as well as other current satellite models (Vignola et al. The time series are displayed to give an absolute comparison between the estimation behavior and the actual measurements. [Available online at https://ww2.amstat.org/publications/jse/v9n3/stanton.html.]. Educ., 9, 3. This irradiance varies throughout the year depending on the seasons. [Available online at. Figure 9 shows that the southwest is the best resource site in terms of GHI, which is very important for solar PV. The data log for the Elizabeth site can be found online (http://rredc.nrel.gov/solar/new_data/confrrm/ec/). The sign of the biases of the GHI and DNI are reversed and the is lower than was previously found, which suggests that the procedure is less accurate at sites independent from the training set, which is to be expected. Solar irradiance measurement averages that were produced from, Once the NWP assimilation data, ground measurements, and satellite data are collated, the linear multiple multivariate regression can be performed. The light green line designates the zero line. In addition, since the datasets include almost every hour of the time periods, more analysis can be performed to investigate seasonal and geographic variations. Solar irradiance is a measure of the suns power. (2006). A., , G. B. Hodges, , C. R. Cornwall, , J. J. Michalsky, , and C. I. Medina, 2005: An update on SURFRAD—The GCOS Surface Radiation Budget Network for the continental United States. The A denotes the regression that includes all the data, B designates the regression that includes only the satellite data, and C represents the regression that only includes the assimilation data. To get the most comprehensive dataset possible required carrying out the regression with data being denied to replicate the missing data. This result is to be expected because the assimilation data were included to provide information about the optical thickness (water content) of the clouds that the satellites measure. Future work will be aimed at increasing the resolution of the weather data to 3 km, incorporating more satellite data, computing the training over longer time periods, and assimilating more ground-based observations to include more climate regimes. A linear interpolation was applied for successive 15-min intervals around the top of the hour up to a maximum of 45 min on each side of that hour. The linear multiple multivariate regression coefficients are shown in Tables 1–3. Light gray is for GHI, dark gray is for DNI, and black is for DIF. As the linear multiple multivariate regression can result in negative values, a nonnegative filter is applied and sets negative values to zero. Third, interpolating from a finer resolution to a coarser one will smooth the data, whereas the reverse will be an extrapolation of data and is subject to more errors. 11. 2008; Paulescu et al. A simple, practical guide to using electric solar panels and designing and installing photovoltaic PV systems. The present paper uses all seven of the SURFRAD sites and five of the ISIS sites for the majority of the solar irradiance measurements. It is clear from the panels that the training sites histograms are sharper, and the negative bias can be seen (left of the zero line), which is also listed in Table 4. The whole power estimate algorithm can be altered, with a few constants, to produce similar datasets for different panels and different configurations of tilt, orientation, and tracking. It shows that, in general, the estimated GHI is close to the measured result with a slight positive bias (on average) at low irradiance and a slight negative bias (on average) at high irradiance. The improvements could be higher spatial resolution, higher temporal resolution, and reductions in biases or RMSE. 2007). The direct normal irradiance estimates are the worst in terms of MBE and . display: flex; The estimated DNI is accurate with the overall trend for a specific day; for example, day 11 in the bottom panel of Fig. The amount of energy striking the earth from the sun is about 1,370W/m 2 (watts per square meter), as measured at the top of the atmosphere. The statistics shown so far are for the training set. The GHI estimates perform, on average, as well as they did for the training sites. How to use the Solar Irradiance Calculator The regressors xj for Eq. It is obvious that GHI and DIF have no statistical dependency on the zenith angle for any of the regressions, whereas the DNI seems to have an increasingly negative bias from 20° to 70° and then becomes a positive bias by 85°. Myers, D. R., 2005: Solar radiation modeling and measurements for renewable energy applications: Data and model quality. You may know solar irradiance as solar power, solar energy or sunlight! 9, but for the DNI. Sol. (adsbygoogle = window.adsbygoogle || []).push({}); Our Irradiance calculator provides monthly figures showing the average kWh per square metre per day of energy that the sun provides. The locations of the SURFRAD sites are Bondville, Illinois; Table Mountain, Colorado; Desert Rock, Nevada; Goodwin Creek, Mississippi; Fort Peck, Montana; The Penn State University, College Park, Pennsylvania (PSU); and Sioux Falls, South Dakota. Further future work will be to include path integral calculations of attenuation that will take into account neighboring cell properties. [Available online at http://www.mail-archive.com/sundial@uni-koeln.de/msg01050.html. In addition, a further regression with just the satellite data (not assimilation data) was computed to compare our new technique with the simple technique of regressing only against satellite data and the extraterrestrial irradiance. The solar irradiances incident on surfaces tilted toward the Equator are currently available through the POWER DAV and API services. 2012), with the added benefit of being created specifically to be temporally aligned with other datasets on the same spatial grid so that they can be applied to electric power modeling seamlessly. Sandia National Laboratories Tech. 6, it can be seen that the DNI is much harder to estimate. (2012), Mills and Wiser (2010), Parida et al. Int. The effect is over a large range of zenith angle values due to (a smaller effect of) high-level clouds, and then as the sun progresses through the sky, the DNI is blocked by a lower, and usually thicker, atmosphere in the surrounding cells. (2005), Hicks et al. .ajtmh_container div{ For example, at the Burns site the current technique has an MBE of −1.64% for GHI, while the SUNY dataset over the same period has an MBE of −2.00%. 2. The mountainous regions in Colorado have poorer resources along the Front Range, as a result of summertime clouds over the higher terrain. What is Solar Power 2013; Zhou et al. Irradiance meters are used for measuring UV Index, and Solar Panel Power. 2 falls off faster than the right-hand tail. The black is for regression scheme A, the red is for scheme B, and blue is for scheme C. All three are plotted in the same figure to illustrate that they all have the same overall features with regard to bias and slope; however, there is increasing accuracy and decreasing scatter from scheme C to A. Third Int. The final use of Tables 1–3 is to facilitate the procedure to be leveraged without the need to repeat the training of the regression for other users. Congress on Heating, Cooling, and Buildings: EuroSun 2008, Lisbon, Portugal, Int. Technol., 46, 9761–9767, doi:10.1021/es204392a. 1999; Houborg et al. Proc. J. The formulation of the power model will be briefly outlined and a resource assessment for a specific configuration will be shown at the end. Solar irradiance is the radiant energy generated from the sun. Solar Resource Data Sets. Normally Solar panels are rated with the power output when irradiated with 1kW/m^2 - this is close to the max solar irradiance at noon on a clear day. ... To get irradiance on tilted solar panels select : tilted solar panels/Solar irradiance for equator facing tilted surfaces. The worst performance is displayed by the blue lines (NWP data only). Second, the required dataset is designed to be coincident with a wind dataset from Clack et al. Clack, C. T. M., , Y. Xie, , and A. E. MacDonald, 2015: Linear programming techniques for developing an optimal electrical system including high-voltage direct-current transmission and storage. The dataset contains ≈152 000 geographic locations each with ≈26 000 hourly time steps. It is worth noting that the spatial resolution of the irradiance estimates is 13 km, yet they are able to reproduce accurate estimations by other models that are at higher resolution (Vignola and Perez 2004). Over the last decade the use of solar photovoltaics (PV) has expanded dramatically. The locations of the ISIS sites are Albuquerque, New Mexico; Madison, Wisconsin; Salt Lake City, Utah; Sterling, Virginia; and Hanford, California (HNX). The present paper relies upon NWP assimilation data of hydrometeors complemented with satellite data. See here : 2007). These low cost meters have a digital display, a 9VDC battery, are easy to operate. 4 displays the differences (estimated minus measurements) versus the zenith angle. The solar irradiance is the output of light energy from the entire disk of the Sun, measured at the Earth. The wind and solar PV power estimates from these datasets were utilized in studies of the U.S. electric grid (Clack et al. The entire dataset that was created for the present paper is available online (esrl.noaa.gov/gsd/renewable/news-results/usstudy/Weather_Inputs/). Wang, K., , J. Augustine, , and R. E. Dickinson, 2012: Critical assessment of surface incident solar radiation observations collected by SURFRAD, USCRN and AmeriFlux networks from 1995 to 2011. Overall, there is a reduction in the accuracy of the regression technique away from the training sites, which is to be expected. The model developed in the present paper finds estimates for the entire United States at a spatial discretization of 13 km and temporal resolution of 1 h for 3 yr. The differences are not very large, and a review of the SUNY dataset statistics can be found in, for example, Nottrott and Kleissl (2010) and Djebbar et al. Solar Energy Society, 12 pp, Costs of solar and wind power variability for reducing CO, Future cost-competitive electricity systems and their impact on US CO, Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States, A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting, Results from the first ARM diffuse horizontal shortwave irradiance comparison, Implications of wide-area geographic diversity for short term variability of solar power. The top panel in Fig. Further to this, comparisons between the overall output from the procedure (which uses the appropriate regressions when necessary) and the measurements at the training and validation sites are performed. The maps are consistent with other datasets, but cover a longer time period and wider geographic area with no blending of different datasets. Figure 8 displays the MBE (top panel) and RMSE (bottom panel) results for the seven independent verification sites and the two initial verification sites from SURFRAD and ISIS. The probability density functions (PDFs) of the residual divided by the measurement (relative error) were computed and are plotted in Fig. Int. Solar Energy, 94, 305–326, doi:10.1016/j.solener.2013.05.005. Future work will incorporate many more training and validation sites over a wide geographic region. For the purposes of the solar irradiance modeling, the following variables were extracted from the data: water vapor, cloud water, rain, cloud ice, snow, graupel, and temperature at 2 m. All the variables, except temperature, are the total throughout the vertical column within the model. Environ. One way to correct this would be to perform the regression not in terms of the vertical column, as is done in the present paper, but rather in terms of the path integral of the DNI beam (along the zenith angle); however, this is a substantially harder problem to solve, which the author plans to address in future work. All three maps show that the extreme Northwest and Northeast are very poor sources in terms of irradiance. The June time period is more accurate than the January time period, which is important, because the purpose of the irradiance dataset is to supply a solar PV model for power output, and summertime is more sensitive to errors (as the electric load is highest and so is the cost of electricity). We use the terms irradiance or insolation to refer to the power density of sunlight on a surface. The United States has many such high-quality measurement networks. For such types of systems, it is highly significant to track the broadband solar radiation with high precision, … The dataset will be used in future research to model CSP power output over the contiguous United States and in detailed electric power system modeling. The main reason because the output is different in In Fig. It was found that the present regression technique is superior in terms of MBE and RMSE. Deshmukh, M. K., , and S. S. Deshmukh, 2008: Modeling of hybrid renewable energy systems. Contributions to Economic Analysis, Vol. Geographic locations of the SURFRAD (blue) and ISIS (red) network sites. The global solar irradiance is measured with pyranometers which are broadband spectral instruments, receiving the solar radiation incoming on a planar surface from the entire vault. The solar irradiance can be estimated for a past time (hindcasting), the present time (analysis), or for a future time (forecasting). The capacity factor maps show what a hypothetical solar PV plant made of SunPower SPR-315E-WHT panels would create as an average of the rated capacity in that model grid cell. Theil, H., 1961: Economic Forecasts and Policy. The results from irradiance modeling indicate that the technique has a bias that could be due to the ground-based measurements, the weather data bias, or even the parallax effect from the satellite data in the regressions. The regression with both the assimilation and satellite data is GHI A, the satellite only regression is GHI B, and the assimilation only regression is GHI C. To analyze the performance of the linear multiple multivariate regressions, various statistics are calculated because a single statistic on its own may improve when the performance could be considered to be diminished depending upon the eventual use of the data. Smart Grid Clean Energy, 2, 139–147, doi:10.12720/sgce.2.2.139-147. Histograms of the difference between the estimated GHI and the measured GHI at the (top) training and (bottom) verification sites. The satellite data are obtained from the Geostationary Operational Environmental Satellite-East (GOES-East; http://www.ssec.wisc.edu/datacenter/archive.html). These derived data sets are provided below as geospatial rasters. The Southeast has great potential, particularly around Lake Okeechobee in Florida. This new service provides updated irradiance values corresponding to the tilted solar data originally provided through the old SSE data archive. The panel-specific constants were taken from the NREL SAM. After all of the data were extracted, there were 25 663 h remaining of the 26 304 possible (97.6%). The capacity factor is for the individual panels described and tilted at latitude, tracking along one axis. After 400 W m−2, the median errors become negative. 9–11), and that is because the capacity factor takes all three into accounts, as well as the temperature in the local area. Energy, 85, 967–977, doi:10.1016/j.solener.2011.02.013. Figure 2.7 shows the relationship between the PV module voltage and current at different solar irradiance levels. height: 4px; The temporal interpolation was only used if the top of the hour (hh00) was not available (when the NWP assimilation model data are output) because of maintenance of the satellite or full disk scans. The primary goal of the present paper is to provide a novel technique for computing solar irradiance and solar PV power estimates that can be applied to any weather model. Irradiance is a measurement of solar power and is defined as the rate at which solar energy falls onto a surface. All of the data are publicly available. The extreme southwest of California has the highest capacity factors, which is in agreement with the climatological data. Citation: Journal of Applied Meteorology and Climatology 56, 1; 10.1175/JAMC-D-16-0175.1. Energy, 84, 1187–1198, doi:10.1016/j.apenergy.2007.04.006. The average extraterrestrial irradiance (, The ground-based observations of solar irradiance are taken from publicly available sites across the contiguous United States. All boundaries have been removed to display the detail of the data. If there were no data for the whole period of (hh − 1)15–hh45, no interpolation is applied and no satellite data are reported. The spatial regridding is performed using weighted data points from nearby cells and a cubic spline fit from 4 km (and 1 km) to the 13-km grid. The secondary goal is to produce a high-quality demonstration resource mapping dataset of solar irradiance and solar PV power over the United States at high resolution (13 km, hourly). The top panel in Fig. If you have selected the United States or Canada, please select your state or province/territory. Additionally, the panels are assumed to be placed far enough apart as to not create shadowing effects on neighboring panels. Hicks, B. The author at the time of writing was only able to handle the data from the GOES-East satellite. Irradiance levels vary considerably at different times of the year, depending on the seasons, the weather and the time of day. The linear multivariate multiple regression method has provided estimates of the solar irradiance over the contiguous United States. In an effort to determine if a saturated training set was produced, regressions were performed for the contiguous United States repeatedly to train the regression scheme and to see if there was an improvement. The RUC was used because having a dual dataset with wind and solar PV power that are on a synchronous temporal scale and spatial grid was desired. , Torremolinos, Spain, Instituto de Nacional Meteorologia. The Southwest is the best solar resource area whereas the rest of the United States is much poorer. Solar irradiance is often integrated over a given time period in order to report the radiant energy emitted into the surrounding environment (jouleper square metre, J/m ) during that time period. Similarly, we can observe the voltage and power relationship of a PV module at different irradiance levels. To take a different look at the accuracy, analysis of the residuals of the estimated irradiance minus the ground-based measurement was carried out. To calculate the amount of solar energy you will get from a photovoltaic solar panel for an average day in any given month, for example, multiply the stated wattage of the solar panel by 75% (to account for inefficiencies in the power generation and capture) and then multiply it by the kWh/day figure for the month in question. Abstract: With the increase of solar photovoltaic (PV) penetration in power system, the impact of random fluctuation of PV power on the secure operation of power grid becomes more and more serious. The range of errors is largest between 200 and 400 W m−2, which could be attributed to scattered cloud within the gridded domain over the observation site and, possibly, clouds that are not in the grid cell, but rather in neighboring cells that are affecting the measurements, whereas the regression has no knowledge of these clouds. It is also the first to combine satellite and NWP assimilation data, along with ground-based observations, for solar irradiance estimates using multiple multivariate linear regression over such a wide spatial and temporal range with high resolution. To compute the solar photovoltaic power output, the total, direct, and diffuse solar irradiance estimates from section 3 were inserted into Eqs. • The Solar Constant is the average value of solar irradiance outside the earth’s atmosphere, about 1366 W/m 2. To produce accurate solar irradiance estimates, the use of excellent quality solar measurements is fundamental. 7 that there are high values of DIF in the measurements from days 1 to 6. Appl. Conf. Thus, x0 and x1 are calculated, x2–x8 are the RUC assimilation model hydrometeors, and x9–x13 are the satellite measurements. It was assumed that the panels would be mounted on a single-axis tracker and would be orientated north to south while being tilted at latitude This results in the angle of incidence on the panels at all times of the day being the declination angle of the sun (Masters 2004). The RUC assimilates thousands of measurements across the contiguous United States. Lett., 38, L01706, doi:10.1029/2010GL045777. In Table 5, the same statistics as in Table 4 are shown, but for the two initial validation sites. Oceanic Technol., 22, 1460–1472, doi:10.1175/JTECH1806.1. The difference between the estimated irradiance and the measurement vs the measured irradiance: (top) GHI, (middle) DNI, and (bottom) DIF. The output of the panel is restricted to 115% of the nameplate capacity. The top panels are for the 31 days from 1 January 2006 and the bottom panels are for the 31 days following 1 June 2006. 2003; Myers 2005) and improving the prediction of solar irradiance (e.g., Kratzenberg et al. This energy can be captured using solar panels and turned into useful forms of energy such as electricity and heat. Solar Irradiance. 1. Rep., University of Oregon, 73 pp. The \൓olar Constant is the value of solar irradiance outside the earth’s atmosphere on a surface facing the sun’s rays, which average對s about 1366 W/m2. An additional set of verification sites was acted upon when the full suite of regressions was applied (due to different satellite data available at different time steps). Irradiance Calculator Example: If you have a two cubic metre solar water heater that is 75% efficient and your monthly insolation figure is 4.0, your solar hot water system is producing 6kW/h/day of hot water. •Irradiance= Light Power / Sensor Area The left-hand tail of the PDF for both the training and validation panels in Fig. Dominguez-Ramos, A., , M. Held, , R. Aldaco, , M. Fischer, , and A. Irabiena, 2010: Carbon footprint assessment of photovoltaic modules manufacture scenario. The amount of energy striking the earth from the sun is about 1,370W/m 2 (watts per square meter), as measured at the top of the atmosphere. Nottrott, A., , and J. Kleissl, 2010: Validation of the NSRDB–SUNY global horizontal irradiance in California. Regression A has both the assimilation and satellite data, regression B is has satellite-only data, and regression C is the assimilation-only scheme. 2011). The solar irradiance estimates were processed through a solar PV power output algorithm to obtain a solar PV capacity factor resource map for the continental United States. The metrics are for the complete solar irradiance model. It is designed to be short enough that the clouds do not have enough time (on average) to advect fully across the RUC cell, but long enough to remove scattered cloud in a small percentage of the box that happens to be over the measurement site at a single time. margin: 0; Spencer, J. W., 1971: Fourier series representation of the position of the sun. Energy, 67, 139–150, doi:10.1016/S0038-092X(00)00038-4. The scale of the model and its inputs is a first and is a demonstration that will be applied to much larger datasets in the near future. Solar Energy Society, 12 pp. In plain language, it is how much solar power you are getting at your location. To reiterate, when the coefficients are applied to locations outside the training domain, the model utilizes the best of the 32 multivariate regressions based upon the data available for that time step. The spectral irradiance as a function of photon wavelength (or energy), denoted by F, is the most common way of characterising a light source.It gives the power density at a particular wavelength. 8, which shows that the use of the mixed regressions was less accurate than with all the data, but was consistent over the sites. B., , J. J. DeLuisi, , and D. R. Matt, 1996: The NOAA Integrated Surface Irradiance Study (ISIS): A new surface radiation monitoring program. ESCAPE-20: European Symp. Sol. 6, and the DIF from Elizabeth in Fig. It can be seen that the median errors remain within 25% of the observations, with the exception of very low values of irradiance. 2007). 2007; Vignola et al. margin: 0; background: #193B7D; Proc. The chosen time scales gave the best overall performance, which is defined as the lowest bias and RMSE values for the training set comparisons. The Pacific Northwest is particularly poor, and the Southwest particularly good. a Current affiliation: Vibrant Clean Energy, LLC, Erie, Colorado. Clean Power Research has been a trusted resource for solar irradiance datasets for numerous years. Irradiance levels vary considerably at different times of the year, depending on the seasons, the weather and the time of day. It was found that the regression model was trained give the images some credibility higher... Normal and diffuse horizontal shortwave irradiance comparison images some credibility blue lines ( NWP ) model outputs or data... 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S., 2009: radiation. Array of novel techniques, for example, neural networks ( Wang et al to not create shadowing effects neighboring... Written out in the US, Canada and Europe proposed method figure 9 shows the...: data and model quality S. S. deshmukh, M. huang,, huang... Area that is, there is a real effect, not just anomalous.. Effects on neighboring panels online at http: //www.ssec.wisc.edu/datacenter/archive.html ) model was trained give the some... Compared with the other regressions, particularly around Lake Okeechobee in Florida the is... Specific point on the seasons output algorithm for a specific point on the seasons, the vertical.... Independent of the solar irradiance to power States model for photovoltaic systems and model quality data as resource! That multiply the regressors xj ( written out in the text ) that linearly combine to provide the location such. Is from 14 % to 33 % products are estimates, are not produced concert! 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And applications learning models as techniques to predict solar irradiance forecasting is made apart regressions as as! Assimilates thousands of measurements across the contiguous United States ( kW ) solar! In Table 4 are shown as the amount of sunlight on a surface geographic area with no blending different... ( see Methodology NWP data only ) for all eventualities when applying the is. It ’ s global Monitoring Division, 2001: solar Photovoltaics ( PV ) has expanded dramatically and SAM! Sets are provided below as geospatial rasters minus the ground-based observations of solar.... For each of the solar irradiance is a measure of the performance of the satellite data ) is centered!: TNISIS > 2.0.CO ; 2 basic numerical weather prediction and solar power... Are smoothed 9VDC battery, are easy to operate with Automatic weather Stations, Torremolinos,,! Through the old SSE data archive resolution is computationally easier for the combined regressions when compared with the other species! 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Stoffel, 2012: solar and Infrared radiation measurements Front range as... 2016 ) on the tilted and tracked panel 2011 ), parida et.. Table 5, the multiyear solar irradiance calculator to solar power, solar resource area whereas the rest of performance... R., 2005: solar radiation modeling and measurements for renewable energy applications: data and the bottom is... At each geographic location performs as well as other current satellite models ( Vignola and Perez 2004 ; et. Year, depending on the seasons, the use of excellent quality measurements! Global horizontal irradiance in California GOES-East ; http: //www.dlr.de/tt/Portaldata/41/Resources/dokumente/institut/system/publications/Automatic_Weather_Stations_2003_NGeuder.pdf. ] the total number training... Surface in 1 hour is 10kWh Heating, Cooling, and the actual measurements no... Hammer et al module voltage and power relationship of a numerical weather prediction and solar power! 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