A New Algorithm for the Satellite-Based Retrieval of Solar Surface Irradiance in Spectral Bands

The impacts of incentive policies on improving private investment for rural electrification in Nigeria - A geospatial study

In Nigeria, 86 million people lack electricity access, the highest number worldwide, predominantly in rural areas. Despite government efforts, constrained budgets necessitate private investors, who, without adequate incentives, are hesitant to commit capital due to perceived high risks. This study identifies three existing incentive policies-concessionary loans, capital subsidy, and financing productive use equipment-aimed at promoting rural electrification in Nigeria. Employing geospatial and regulatory analyses, we evaluate their impact on electrification planning across 22,696 population clusters. While all incentives encourage mini-grids and stand-alone systems, results show varied impacts, predominantly favouring mini-grids. Under the baseline, grid extension is optimal for 66% of clusters, followed by mini-grids (27%) and stand-alone systems (7%). Concessionary loans boost mini-grid and Stand-Alone Systems shares by 10% and 5%, respectively. Capital subsidies increase the mini-grid share to 41%, surpassing concessional loans (37%). Financing productive equipment enhances Stand-Alone Systems and mini-grid shares to 15% and 43%. Incentives impact LCOE, CAPEX, and OPEX, with average LCOE reducing to 0.31 EUR/kWh (concessionary loans), 0.30 EUR/kWh (capital subsidy), and 0.27 EUR/kWh (financing productive use). Financing productive uses proves decisively more effective in lowering costs for mini-grids and stand-alone systems than loans or capital subsidies. The important policy implications of this study reinforce the need for tailored incentives for distinct electrification options.

Solar Potential in Saudi Arabia for Flat-Plate Surfaces of Varying Tilt Tracking the Sun

The objective of the present work is to investigate the performance of flat-plate solar panels in Saudi Arabia that continuously follow the daily motion of the sun. To that end, the annual energy sums are estimated for such surfaces at 82 locations covering all Saudi Arabia. All calculations use a surface albedo of 0.2 and another one with a near-real value. The variation of the solar energy sums on annual, seasonal, and monthly basis is given for near-real ground albedos; the analysis provides regression equations for the energy sums as function of time. A map of the annual inclined solar energy for Saudi Arabia is derived and presented. The annual energy sums are found to vary between 2159 and 4078 kWhm−2year−1. Finally, a correction factor, introduced in a recent publication, is used; it is confirmed that the linear relationship between the correction factor and the ground-albedo ratio is general enough to be graphically representable as a nomogram. A discussion regarding the differences among solar systems on horizontal, fixed-tilt, 1-axis, and 2-axis systems is presented.

Solar Potential in Saudi Arabia for Inclined Flat-Plate Surfaces of Constant Tilt Tracking the Sun

The objective of the present work is to investigate the optimally performing tilt angles in Saudi Arabia of solar panels that follow the daily motion of the Sun. To that end, the annual energy sums are estimated for surfaces with tilt angles in the range 5°–55° at 82 locations covering all Saudi Arabia. All calculations use a surface albedo of 0.2 and a near-real value, too. It is found that tilt angles of 40°, 45°, and 50°, respectively, are optimal for the three recently defined solar energy zones in Saudi Arabia. The variation of the energy sums in each energy zone on annual, seasonal and monthly basis is given for near-real ground albedos; the analysis provides regression equations for the energy sums as functions of time. A map of the annual global inclined solar energy for Saudi Arabia is derived and presented. The annual energy sums are found to vary between 2159 kWhm−2year−1 and 4078 kWhm−2year−1. Finally, a correction factor, introduced in a recent publication, is used; it is confirmed that the relationship between the correction factor and either the tilt angle or the ground-albedo ratio has a general application and it may constitute a nomogram.

Solar Potential in Saudi Arabia for Southward-Inclined Flat-Plate Surfaces

The major objective of the present work is to investigate into the appropriate tilt angles of south-oriented solar panels in Saudi Arabia for maximum performance. This is done with the estimation of the annual energy sums received on surfaces with tilt angles in the range 15°–55° inclined to south at 82 locations covering all Saudi Arabia. The analysis shows that tilt angles of 20°, 25° and 30° towards south are the optimum ones depending on site. These optimum tilt angles define three distinct solar energy zones in Saudi Arabia. The variation of the energy sums in each energy zone on annual, seasonal and monthly basis is given; the analysis provides regression equations for the energy sums as function of time in each case. Furthermore, the spatial distribution of the annual global inclined solar energy in Saudi Arabia is shown in a solar map specially derived. The annual energy sums are found to vary between 1612 kWhm−2year−1 and 2977 kWhm−2year−1 across the country. Finally, the notion of a correction factor is introduced, defined, and employed. This factor can be used to correct energy values estimated by a reference ground albedo to those based on near-real ground albedo.

The Effect of Climate on the Solar Radiation Components on Building Skins and Building Integrated Photovoltaics (BIPV) Materials

The business model of building-integrated photovoltaics (BIPV) is developing expeditiously and BIPV will soon be recognised as a building envelope material for the entire building skins, among other alternatives such as brick, wood, stone, metals, etc. This paper investigates the effect of climate on the solar radiation components on building skins and BIPV materials in the northern hemisphere. The selected cities are Stavanger in Norway, Bern in Switzerland, Rome in Italy, and Dubai in the UAE. The study showed that for all the studied climates, the average incident radiation on the entire building skins is slightly more than the average incident radiation on the east or west facades, regardless of the orientations of the building facades. Furthermore, the correlation between solar radiation components and different BIPV technologies is discussed in this paper. It is also found that when it comes to the efficiency of different BIPV cells, the impact of the climate on some of the BIPV technologies (such as DSC and OSC) is much more significant than others (such as c-Si, mc-Si and CIGS). The evidence from this study suggests that in climates with higher diffuse radiation-or with more overcast days per year-the contribution of IR radiation decreases. Therefore, the efficiency of BIPV materials that their spectral responses are dependent on the IR radiation (like Si and CIGS) in such a climate would drop down meaningfully. On the other hand, the DSC and OSC solar cells could be a good option for cloudy climates since they have more stable performance, even in such a climate. Although, their efficiency compared to other BIPV materials such as Si-based BIPV solar cells is still significantly less thus far.

Development of a Seamless Forecast for Solar Radiation Using ANAKLIM++

A novel approach for a blending between nowcasting and numerical weather prediction (NWP) for the surface incoming shortwave radiation (SIS) for a forecast horizon of 1–5 h is presented in this study. The blending is performed with a software tool called ANAKLIM++ (Adjustment of Assimilation Software for the Reanalysis of Climate Data) which was originally designed for the efficient assimilation of two-dimensional data sets using a variational approach. A nowcasting for SIS was already presented and validated in earlier publications as seamless solar radiation forecast (SESORA). For our blending, two NWP models, namely the ICON (Icosahedral Non-hydrostatic model) from the German weather Service (DWD) and the IFS (Integrated Forecasting System) from the European Centre for Medium-Range Weather Forecasts (ECMWF), were used. The weights for the input data for ANAKLIM++ vary for every single forecast time and pixel, depending on the error growth of the nowcasting. The results look promising, since the root mean square error (RMSE) and mean absolute error (MAE) of the blending are smaller than the error measures of the nowcasting or NWP models, respectively.

Reliability Predictors for Solar Irradiance Satellite-Based Forecast

The worldwide growing development of PV capacity requires an accurate forecast for a safer and cheaper PV grid penetration. Solar energy variability mainly depends on cloud cover evolution. Thus, relationships between weather variables and forecast uncertainties may be quantified to optimize forecast use. An intraday solar energy forecast algorithm using satellite images is fully described and validated over three years in the Paris (France) area. For all tested horizons (up to 6 h), the method shows a positive forecast skill score compared to persistence (up to 15%) and numerical weather predictions (between 20% and 40%). Different variables, such as the clear-sky index (Kc), solar zenith angle (SZA), surrounding cloud pattern observed by satellites and northern Atlantic weather regimes have been tested as predictors for this forecast method. Results highlighted an increasing absolute error with a decreasing SZA and Kc. Root mean square error (RMSE) is significantly affected by the mean and the standard deviation of the observed Kc in a 10 km surrounding area. The highest (respectively, lowest) errors occur at the Atlantic Ridge (respectively, Scandinavian Blocking) regime. The differences of relative RMSE between these two regimes are from 8% to 10% in summer and from 18% to 30% depending on the time horizon. These results can help solar energy users to anticipate—at the forecast start time and up to several days in advance—the uncertainties of the intraday forecast. The results can be used as inputs for other solar energy forecast methods.

GPU-Enabled Shadow Casting for Solar Potential Estimation in Large Urban Areas. Application to the Solar Cadaster of Greater Geneva

In the context of encouraging the development of renewable energy, this paper deals with the description of a software solution for mapping out solar potential in a large scale and in high resolution. We leverage the performance provided by Graphics Processing Units (GPUs) to accelerate shadow casting procedures (used both for direct sunlight exposure and the sky view factor), as well as use off-the-shelf components to compute an average weather pattern for a given area. Application of the approach is presented in the context of the solar cadaster of Greater Geneva (2000 km2). The results show that doing the analysis on a square tile of 3.4 km at a resolution of 0.5 m takes up to two hours, which is better than what we were achieving with the previous work. This shows that GPU-based calculations are highly competitive in the field of solar potential modeling.

The Seamless Solar Radiation (SESORA) Forecast for Solar Surface Irradiance—Method and Validation

Due to the integration of fluctuating weather-dependent energy sources into the grid, the importance of weather and power forecasts grows constantly. This paper describes the implementation of a short-term forecast of solar surface irradiance named SESORA (seamless solar radiation). It is based on the the optical flow of effective cloud albedo and available for Germany and parts of Europe. After the clouds are shifted by applying cloud motion vectors, solar radiation is calculated with SPECMAGIC NOW (Spectrally Resolved Mesoscale Atmospheric Global Irradiance Code), which computes the global irradiation spectrally resolved from satellite imagery. Due to the high spatial and temporal resolution of satellite measurements, solar radiation can be forecasted from 15 min up to 4 h or more with a spatial resolution of 0.05 ∘ . An extensive validation of this short-term forecast is presented in this study containing two different validations based on either area or stations. The results are very promising as the mean RMSE (Root Mean Square Error) of this study equals 59 W/m 2 (absolute bias = 42 W/m 2 ) after 15 min, reaches its maximum of 142 W/m 2 (absolute bias = 97 W/m 2 ) after 165 min, and slowly decreases after that due to the setting of the sun. After a brief description of the method itself and the method of the validation the results will be presented and discussed.

Improvement in Surface Solar Irradiance Estimation Using HRV/MSG Data

The Advanced Model for the Estimation of Surface Solar Irradiance (AMESIS) was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) to derive surface solar irradiance from SEVIRI radiometer on board the MSG geostationary satellite. The operational version of AMESIS has been running continuously at IMAA-CNR over all of Italy since 2017 in support to the monitoring of photovoltaic plants. The AMESIS operative model provides two different estimations of the surface solar irradiance: one is obtained considering only the low-resolution channels (SSI_VIS), while the other also takes into account the high-resolution HRV channel (SSI_HRV). This paper shows the difference between these two products against simultaneous ground-based observations from a network of 63 pyranometers for different sky conditions (clear, overcast and partially cloudy). Comparable statistical scores have been obtained for both AMESIS products in clear and cloud situation. In terms of bias and correlation coefficient over partially cloudy sky, better performances are found for SSI_HRV (0.34 W/m2 and 0.995, respectively) than SSI_VIS (−33.69 W/m2 and 0.862) at the expense of the greater run-time necessary to process HRV data channel.

Extensive validation of CM SAF surface radiation products over Europe

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8-13 W/m², whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements.

A Satellite-Based Sunshine Duration Climate Data Record for Europe and Africa

Besides 2 m - temperature and precipitation, sunshine duration is one of the most important and commonly used parameter in climatology, with measured time series of partly more than 100 years in length. EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF) presents a climate data record for daily and monthly sunshine duration (SDU) for Europe and Africa. Basis for the advanced retrieval is a highly resolved satellite product of the direct solar radiation from measurements by Meteosat satellites 2 to 10. The data record covers the time period 1983 to 2015 with a spatial resolution of 0.05° × 0.05°. The comparison against ground-based data shows high agreement but also some regional differences. Sunshine duration is overestimated by the satellite-based data in many regions, compared to surface data. In West and Central Africa, low clouds seem to be the reason for a stronger overestimation of sunshine duration in this region (up to 20% for monthly sums). For most stations, the overestimation is low, with a bias below 7.5 h for monthly sums and below 0.4 h for daily sums. A high correlation of 0.91 for daily SDU and 0.96 for monthly SDU also proved the high agreement with station data. As SDU is based on a stable and homogeneous climate data record of more than 30 years length, it is highly suitable for climate applications, such as trend estimates.