Francisco J. Santos-Alamillos

Analysis of WRF Model Wind Estimate Sensitivity to Physics Parameterization Choice and Terrain Representation in Andalusia (Southern Spain)

AbstractThis paper reports on an evaluation of the relative roles of choice of parameterization scheme and terrain representation in the Weather Research and Forecasting (WRF) mesoscale model, in the context of a regional wind resource assessment. As a first step, 32 configurations using two different schemes for microphysics, cumulus, planetary boundary layer (PBL), or shortwave and longwave radiation were evaluated. In a second step, wind estimates that were obtained from various experiments with different spatial resolution (1, 3, and 9 km) were assessed. Estimates were tested against data from four stations, located in southern Spain, that provided hourly wind speed and direction data at 40 m above ground level. Results from the first analysis showed that wind speed standard deviation (STD) and bias values were mainly sensitive to the PBL parameterization selection, with STD differences up to 10% and bias differences between −15% and 10%. The second analysis showed a weak influence of spatial resoluti...

Analysis of Spatiotemporal Balancing between Wind and Solar Energy Resources in the Southern Iberian Peninsula

AbstractElectricity from wind and, to a lesser extent, solar energy is intermittent and not controllable. Unlike conventional power generation, therefore, this electricity is not suitable to supply base-load electric power. In the future, with greater penetration of these renewable sources, intermittency and control problems will become critical. Here, the authors explore the use of canonical correlation analysis (CCA) for analyzing spatiotemporal balancing between regional solar and wind energy resources. The CCA allows optimal distribution of wind farms and solar energy plants across a territory to minimize the variability of total energy input into the power supply system. The method was tested in the southern half of the Iberian Peninsula, a region covering about 350 000 km2. The authors used daily-integrated wind and solar energy estimates in 2007 from the Weather Research and Forecasting (WRF) mesoscale model, at a spatial resolution of 9 km. Results showed valuable balancing patterns in the study r...

Optimal management of wind and solar energy resources

This paper presents a portfolio-based approach to the harvesting of renewable energy (RE) resources. Our examined problem setting considers the possibility of distributing the total available capacity across an array of heterogeneous RE generation technologies (wind and solar power production units) being dispersed over a large geographical area. We formulate the capacity allocation process as a bi-objective optimization problem, in which the decision maker seeks to increase the mean productivity of the entire array while having control on the variability of the aggregate energy supply. Using large-scale optimization techniques, we are able to calculate - to an arbitrary degree of accuracy - the complete set of Pareto-optimal configurations of power plants, which attain the maximum possible energy delivery for a given level of power supply risk. Experimental results from a reference geographical region show that wind and solar resources are largely complementary. We demonstrate how this feature could help energy policy makers to improve the overall reliability of future RE generation in a properly designed risk management framework.

A High-Resolution Topographic Correction Method for Clear-Sky Solar Irradiance Derived with a Numerical Weather Prediction Model

AbstractRugged terrain is a source of variability in the incoming solar radiation field, but the influence of terrain is still not properly included by most current numerical weather prediction (NWP) models. In this work, a downscaling postprocessing method for NWP-model solar irradiance through terrain effects is presented. It allows one to decrease the estimation bias caused by terrain shading and sky-view reduction, and to account for elevation variability, surface orientation, and surface albedo. The method has been applied to a case study in southern Spain using the Weather Research and Forecasting (WRF) mesoscale model with a spatial resolution of 30 arc s, resulting in disaggregated maps of 3 arc s. The validation was based on a radiometric network made of eight stations located in the Natural Park of Sierra Magina over an area of roughly 30 × 35 km2 and 12 carefully selected cloudless days during a year. Three of the stations were equipped with tilted pyranometers. Their inclination and aspect wer...

Assessing the Surface Solar Radiation Budget in the WRF Model: A Spatiotemporal Analysis of the Bias and Its Causes

AbstractSolar radiation plays a key role in the atmospheric system but its distribution throughout the atmosphere and at the surface is still very uncertain in atmospheric models, and further assessment is required. In this study, the shortwave downward total solar radiation flux (SWD) predicted by the Weather Research and Forecasting (WRF) Model at the surface is validated over Spain for a 10-yr period based on observations of a network of 52 radiometric stations. In addition to the traditional pointwise validation of modeled data, an original spatially continuous evaluation of the SWD bias is also conducted using a principal component analysis. Overall, WRF overestimates the mean observed SWD by 28.9 W m−2, while the bias of ERA-Interim, which provides initial and boundary conditions to WRF, is only 15.0 W m−2. An important part of the WRF SWD bias seems to be related to a very low cumulus cloud amount in the model and, possibly, a misrepresentation of the radiative impact of this type of cloud.

Do spaceborne aerosol observations limit the accuracy of modeled surface solar irradiance

Aerosols play a primary role in the global climate system and the solar radiation budget at the Earth surface. Here we analyze the role of spaceborne aerosol observations and their uncertainties in the expected accuracy of the modeled cloudless surface shortwave downward radiation using a state-of-the-art numerical weather prediction model over the continental U.S. We compare five different modeling approaches for the aerosol optical effects with differing sophistication. Overall, we show that, counterintuitively, the direct and diffuse irradiances predicted by solar radiation models that use empirically adjusted fixed aerosol extinction may be more accurate than more sophisticated radiative transfer models that require inputs of aerosols. We conclude that, compared to ground observations, the mean absolute error in satellite-retrieved aerosol optical depth over the U.S., and possibly elsewhere, should be reduced to less than 0.025 aerosol optical depth unit to assure improvement over the predictions of a simpler, aerosol-insensitive radiation model.

The Impact of the NAO on the Solar and Wind Energy Resources in the Mediterranean Area

The influence of the NAO on the solar and wind energy resources in the Mediterranean area, in particular, and over the whole North Atlantic area, in general, has been explored based on the analysis of 20 years of reanalysis and satellite data. The analysis was carried out for the winter and annual periods and proved the existence of a marked influence of the NAO pattern on the spatial and temporal variability of the solar and wind energy resources in the study area. Particularly, the NAO signature on the solar/wind energy resources was found to be a north-south dipolar pattern, with the positive/negative centre over the Mediterranean area. Although the spatial patterns obtained are similar, the nature of the relationship obtained for wind energy was found to be less linear and more complex than that attained for solar energy. A composite analysis revealed that interannual variability of the solar and wind energy resources in the Mediterranean area can reach values above 20% in winter and 10% in the annual case associated with changes in the NAO phase. Finally, the analysis of the spatial patterns of the NAO influence on the solar and wind energy resources revealed the existence of spatial and local balancing between these two energy resources in the study area. Results are of interest regarding the estimation of the expected interannual variability of the wind farms and solar plants production in the study region.

Worldwide impact of aerosol’s time scale on the predicted long-term concentrating solar power potential

Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis.