A novel time-effective model for daily distributed solar radiation estimates across variable terrain

Abstract

Accurate and precisess estimation of spatio-temporal variability of solar radiation is critical. Some commonly used models evaluate this variability using methods in which the data required for estimating atmospheric attenuation may not be easily accessible for some study areas. Here, a daily solar radiation estimation method which uses ambient air temperature, a Digital Elevation Model, time of year, and monthly radiation estimates from Solar Analyst model has been proposed. The objective was to use air temperature-based empirical models for atmospheric transmissivity and diffuse fractions to vary total monthly radiation estimation from Solar Analyst, and then calculate total daily radiation as a fraction of total monthly radiation by applying a daily transmissivity-based ratio, as air temperature data are readily available at most locations on the planet. Results revealed that daily solar radiation can be estimated very well, with Mean Absolute Bias Error of around 40-53 W m −2 or Mean Bias Error of ± 10%, under all sky conditions at seven sites in diverse climate regions, using significantly less input data. The presented method is an improvement over previously used methods with Mean Bias Error of under 10% but more input parameters. Furthermore, the hourly solar radiation values can be calculated using the presented method using the ratio between daily and hourly radiation, for example from literature values and estimated daily insolation. The result also showed that the method is more useful for those stations with substantially higher numbers of sunny days than cloudy or partly cloudy days because the uncertainty of the model decreased from cloudy to sunny sky conditions. The implemented Digital Elevation Models environment of this method makes it applicable in many studies that need spatial estimation of solar radiation, especially for solar energy generation projects. Keywords Solar radiation · Digital elevation model · Solar analyst · Atmospheric transmissivity · Air temperature Abbreviations

Evaluating solar energy technical and economic potential on rooftops in an urban setting: the city of Lethbridge, Canada

“…Cloud cover has the largest influence on radiation attenuation in the atmosphere [27]. Solar analyst uses defined default values for the diffuse proportion of global radiation (k D ) and the ratio of the insolation received at the Earth's surface as direct radiation along the shortest atmospheric path at sea level to the insolation at the upper border of the atmosphere ( sl , transmittivity), which should be adjusted for local atmospheric conditions [11,20,45]. Accordingly, utilizing meteorological measured [8] data over 5 years from a station (Lethbridge CDA, located at 49°42′0″N, 112°46′60″W) inside the study region and calculating the actual values of required inputs (k D = 0.429, sl = 0.589 ), the effects of cloud cover and local atmospheric conditions have been included.…”

“…All meteorological data were obtained from Alberta Agriculture and Forestry, Alberta Climate Information Service (ACIS) (https ://agric ultur e.alber ta.ca/acis, retrieved 2016). Instead of sl in global annual solar radiation calculation, we used k T sl (the ratio of measured global solar radiation on a horizontal surface against the extraterrestrial radiation at sea level) [11]. Between 11:30 and 12:30 h for each day of the years 2010-2014, the hourly k T was evaluated for the station [46].…”

“…Utilizing light detection and ranging (LiDAR) data, geographic information system (GIS) methods, and PV-performance modeling, the proposed method is an efficient and scalable technique which can be automated and replicated effectively. A new detailed method for calculating solar resource availability using ArcGIS was employed [11]. Solar analyst required inputs which were calculated for the region and the accuracy of the simulated radiation was examined by comparing the results with measured data.…”

Short Term Active Power Load Prediction on A 33/11 kV Substation Using Regression Models

“…ARIMA time series forecast model was developed in [12] to predict the temperature in Pakistan and it also develops a linear trend model to estimate electric power consumption. Digital Elevation Models were developed in [13] to predict the solar irradiation.…”

Comparison of the advanced machine learning methods for better prediction accuracy of solar radiation using only temperature data: A case study

“…Two temperature-based empirical models 15,16 are commonly used for solar radiation prediction. [17][18][19] The diurnal temperature range is considered in Hargreaves and Samani model as an indicator of the R a ratio that arrives at the surface of the earth. An exponential function between the diurnal temperature range and solar radiation was provided in Bristow and Campbell model.…”