Calculation Of Solar Radiation Research Articles

Calculation of urban solar radiation based on simulation and fitting of ASHRAE model constants

Calculation of urban solar radiation based on simulation and fitting of ASHRAE model constants

Pilot projects of industrial photovoltaic solar stations

The scientific article examines the possibilities of using industrial photovoltaic solar stations in power supply systems in the regions of Turkmenistan. Based on the calculations of solar radiation in the regions of Turkmenistan, data on the technical potential of renewable energy sources were obtained. The criteria for evaluating the rational mode of operation of photovoltaic solar stations and the expected amount of electricity generation by solar panels are determined. Pilot projects of energy supply to the population through solar power plants are considered. Keywords: solar radiation, optimal orientation, photovoltaic solar power plant, power generation, decentralized power supply, criteria for evaluating the rational mode of operation.

Calculation of Solar Radiation on Slopes During Snowmelt

Calculation of Solar Radiation on Slopes During Snowmelt

Calculation of the Global Solar Radiation in a Subtropical Region (Qena, Egypt)

Air temperature (T, °C), relative humidity (RH, %), and global solar radiation (G, MJ.m-2 ) have been measured in the meteorological station at South Valley University (SVU) at Qena, Egypt, from 2000 to 2013, while the total column ozone (TCO, DU) is downloaded from Giovanni's website. T, RH, and TCO are important meteorological parameters, and they are useful to estimate the missing data of the global solar radiation (G), as global solar radiation is desirable for electricity generation applications and for agriculture. Qena is a subtropical region in Upper Egypt, as it's characterized by clear weather most days of the year, and it's very hot in the summer and cold in the winter. The meteorological station at South Valley University (SVU) stopped measuring the G. The linear regression equation and the most important statistical indices are used in this paper such as, the determination coefficient (R2 ), the mean absolute error (MAE), the mean absolute bias error (MABE), the mean square error (MSE), the root mean square error (RMSE), the mean percentage error (MPE), the mean bias error (MBE), the model efficiency (ME), and the agreement index (d). For verification of the empirical models' efficiency, the data of a new period has used, 2013, and the results of the models were excellent and valid for estimating the missing data, as R2 was more than 0.92 in all models but it was near one in models 1 and 4. MAE was close to zero for all models. MBE, MPE, and MABE were close to zero for all models except model 3. Model 1 was the best one, as, R2 , MAE, MABE, MSE, RMSE, MAPE, d, ME, and MPE were 0.9883, 0.0193, 0.383, 0.2303, 0.4799, 1.927, 0.9979, 0.992, and 0.2932, respectively

Модуль локального уровня ГИС поддержки точного адаптивно-ландшафтного земледелия

The developed GIS is an information—mathematical model of the agricultural land space, designed for computational analysis of the natural ecological conditions of the hierarchy of landscape areas (ALR) of the region and adaptation of agricultural technologies to them. At the local level of each farm or agricultural company, information on actual land productivity is differentiated relative to the information-mathematical 3D geometric and structural model of the field relief surface. The relief is represented by a system of homomorphic elementary surfaces, each of which is quasi-uniform in the vertical and lateral structure of natural ecological conditions and is distinctive in exposure and morphometric parameters. Homomorphic surfaces correspond to elementary agro-landscape ranges. Original algorithms have been developed for calculating morphometric parameters and exposure within elementary surfaces, the location of current lines, depending on the type of surface, the presence of special points in them and the type of structural lines limiting them. A computational classification of homomorphic surfaces by natural ecological properties affecting the processes of soil formation is provided—position in relation to heat/moisture-bearing flows, gradation of slopes, location within the slope. Algorithms and program modules of information—mathematical automated visualization of homomorphic elementary surfaces, representative points of agrochemical sampling and current lines are designed for interpolation of agrochemical analysis data on each surface; modules for calculating morphometric parameters of elementary surfaces and exposure provide calculation of solar radiation coming within their limits. Within the database, a diagram of relationships between elementary surface objects in a field system was developed. Systemic monitoring and analysis of the law of matter and energy redistribution within elementary surfaces with their corresponding soils, microclimate and agricultural crop, create the possibility of programming spatially differentiated application of biologically active substances within the boundaries of the field, predicting their rates in accordance with climatic trends.

Modelling Building Shadows on Rooftop Generating 3D City Model

Abstract: 3D city models enable us to gain a better grasp of how various city components interact with one another. Advances in geosciences now allow for the automatic creation of high-quality, realistic 3D city models. It is not limited to visualization and navigation, however, also for shadow and solar potential analysis. Solar radiation is an example of a 3D GIS tool that is in high demand. The calculation of solar radiation that reaches 3D objects can be simple, but the shadow effect of nearby buildings is a considerably more challenging issue because some facades or roofs are only partially shadowed. The present study is analyzed into two approaches. The first approach is considered as Visualization (client-side) approach to visualize the 3D city models on the website using NodeJS and CesiumJS. The second approach is considered as Analyzation (Server-side) approach to analyze the solar potential using python for faster processing and deeming the future development aspects.

Evaluation of Riparian Tree Cover and Shading in the Chauga River Watershed Using LiDAR and Deep Learning Land Cover Classification

River systems face negative impacts from development and removal of riparian vegetation that provide critical shading in the face of climate change. This study used supervised deep learning to accurately classify the land cover, including shading, of the Chauga River watershed, located in Oconee County, South Carolina, for 2011 and 2019. The study examined the land cover differences along the Chauga River and its tributaries, inside and outside the Sumter National Forest. LiDAR data were incorporated in solar radiation calculations for the Chauga River inside and outside the National Forest. The deep learning classifications produced land cover maps with high overall accuracy (97.09% for 2011; 97.58% for 2019). The most significant difference in land cover was in tree cover in the 50 m buffer of the tributaries inside the National Forest compared to the tributaries outside the National Forest (2011: 95.39% vs. 81.84%, 2019: 92.86% vs. 82.06%). The solar radiation calculations also confirmed a difference between the area inside and outside the National Forest, with the mean temperature being greater outside the protected area (outside: 455.845 WH/m2; inside: 416,770 WH/m2). This study suggests that anthropogenic influence in the Chauga River watershed is greater in the areas outside the Sumter National Forest, which could cause damage to the river ecosystem if left unchecked in the future as development pressures increase. This study demonstrates the accurate application of deep learning for high-resolution classification of river shading combined with the use of LiDAR data to estimate solar radiation reaching the Chauga River. Techniques to monitor riparian zones and shading at high spatial resolutions are critical for the mitigation of the negative impacts of warming climates on aquatic ecosystems.

The Effects of Roadside Woody Vegetation on the Surface Temperature of Cycle Paths

The article is on the effects of woody vegetation growing on the roadside on the temperature of the surface of cycle paths. The main hypothesis of the study is that vegetation has the effect of lowering the temperature of the surroundings in its shadow and thus improves the comfort of users of cycle paths in the summer months. The second hypothesis is to find out which type of road surface is most suitable for the thermal well-being of users. This goal was achieved by measuring the temperature of selected locations on cycle paths with different types of construction surfaces with nearby woody vegetation using a contactless thermometer over several days at regular intervals. The positions of the selected locations were measured using GNSS and the whole locality of interest was photographed using an unmanned aerial vehicle (UAV), or drone, and subsequently a digital surface model (DSM) of the area was created using a Structure from Motion (SfM) algorithm. This model served for the calculation of incident solar radiation during the selected days using the Solar Area Graphics tool with ArcGIS software. Subsequently, the effect of the shade of the surrounding vegetation on the temperature during the day was analysed and statistically evaluated. The results are presented in many graphs and their interpretation used to evaluate the effects of nearby woody vegetation and the type of road surface on the surrounding air temperature and the comfort of users of these routes. The results demonstrate the benefits of using UAVs for the purpose of modelling the course of solar radiation during the day, showing the effect of roadside vegetation on reducing the surface temperature of the earth’s surface and thus confirming the need for planting and maintaining such vegetation.

Integration of Remotely Sensed Digital Elevation Model Data and Geographic Information System Facilities to Estimate Net Solar Radiation Variances in Iraq (1987-2017)

The calculation of potential earth's surface solar radiation is imperative for analyzing the atmosphere-vegetation-soil interaction process. Therefore, many schemes were introduced with direct (using net radiometer) or indirect (using air temperature or air plus soil temperatures) formulas. Three combinations of factors are known to control the Rn value; the astronomical based factors which determine the general spatial distribution of Rn values, the climatological factors which determine the assigned spatial variation of those values, and the topographical factors that influence climatological factors rates ( i.e. have indirect effects on Rn values).
 For Iraq, the ecosystem influences of global warming were obvious in the 1980s and the Rn rates approached peak values .. Thereafter, the general behavior of Rn rates was geographically-based , i.e. increasing rates in the middle and southern regions and descending rates in the northern parts, since it was spatially correlated in a reverse manner with RH values. In the present study, this issue was clarified by utilizing the standard annual mean Rn rate known for Iraq’s weather, which was 9.8MJ.m-2.year-1. The results showed that, in 1987, the area with annual mean Rn equal or higher than this annual standard rate was 305088.098 km2. The area was reduced to 241984.77 km2 in 1997, followed by an expansion to 294491.136 km2 in 2007, and another reduction to 277272.542 km2 in 2017.

Reliable Evapotranspiration Predictions with a Probabilistic Machine Learning Framework

Evapotranspiration is often expressed in terms of reference crop evapotranspiration (ETo), actual evapotranspiration (ETa), or surface water evaporation (Esw), and their reliable predictions are critical for groundwater, irrigation, and aquatic ecosystem management in semi-arid regions. We demonstrated that a newly developed probabilistic machine learning (ML) model, using a hybridized “boosting” framework, can simultaneously predict the daily ETo, Esw, & ETa from local hydroclimate data with high accuracy. The probabilistic approach exhibited great potential to overcome data uncertainties, in which 100% of the ETo, 89.9% of the Esw, and 93% of the ETa test data at three watersheds were within the models’ 95% prediction intervals. The modeling results revealed that the hybrid boosting framework can be used as a reliable computational tool to predict ETo while bypassing net solar radiation calculations, estimate Esw while overcoming uncertainties associated with pan evaporation & pan coefficients, and predict ETa while offsetting high capital & operational costs of EC towers. In addition, using the Shapley analysis built on a coalition game theory, we identified the order of importance and interactions between the hydroclimatic variables to enhance the models’ transparency and trustworthiness.

Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.

Energy payback time analysis and return on investment of off-grid photovoltaic systems in rural areas of Tanzania

Owing to a vast land area, abundant solar radiation, and overseas support, the use of photovoltaics (PV) as a source of electricity is rapidly spreading in Sub-Saharan Africa. To understand the actual application situations, two cases of PV electricity generation systems in the rural areas of Tanzania were investigated via life cycle assessment. The energy payback time (EPBT) calculated from the utilisation of the PV systems, taking into consideration the inventory data of the International Energy Agency, revealed an unsatisfactory performance. Specifically, the EPBTs based on actual power generation at the sites greatly exceeded the expected value-based solar radiation calculations. At one site, the EPBT even exceeded the lifespan of the PV panel, indicating that energy recovery was impossible. With respect to the energy return on investment (EROI), it was evident that the income generated from the investments was insufficient to cover current operational costs, suggesting negative returns on investment. Conversely, diesel power generation appeared to be more suitable in these areas owing to the low and discontinuous demand for power. Furthermore, the operation of a more efficient PV system would require improved maintenance and management, as well as an increase in the demand for electricity.

Optimal design of the solar tracking system of parabolic trough concentrating collectors

Abstract The present work aimed to select the optimum solar tracking mode for parabolic trough concentrating collectors using numerical simulation. The current work involved: (1) the calculation of daily solar radiation on the Earth’s surface, (2) the comparison of annual direct solar radiation received under different tracking modes and (3) the determination of optimum tilt angle for the north-south tilt tracking mode. It was found that the order of solar radiation received in Shanghai under the available tracking modes was: dual-axis tracking > north-south Earth’s axis tracking > north-south tilt tracking (β = 15°) > north-south tilt tracking (β = 45) > north-south horizontal tracking > east-west horizontal tracking. Single-axis solar tracking modes feature simple structures and low cost. This study also found that the solar radiation received under the north-south tilt tracking mode was higher than that of the north-south Earth’s axis tracking mode in 7 out of 12 months. Therefore, the north-south tilt tracking mode was studied separately to determine the corresponding optimum tilt angles in Haikou, Lhasa, Shanghai, Beijing and Hohhot, respectively, which were shown as follows: 18.81°, 27.29°, 28.67°, 36.21° and 37.97°.

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m2), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. The algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

Research into various modeling methods including the artificial neural networks in studying solar radiation for different regions in the Russian Federation

The comparison of results obtained using the artificial neural networks (ANN) has been carried out in researching solar radiation for various regions of the Russian Federation with data modeling applying a spline interpolation preserving an interpolant shape or a polynomial (up to tenth degree) in the MATLAB environment obtained when using the MATLAB Basic Fitting-a graphical user interface (GUI). The neural network has been trained by the feed-forward backprop algorithm. The following functions were used: the Bayesian Regularization, the function of gradient descent with regard for moments, the hyperbolic tangent functions. The Mean Square Error (MSE) was chosen as a loss function which was minimized. The 15 input parameters were taken. As a result, the obtained model had high values of correlation coefficients and low values of the Mean Square Error among the target and the output values. The polynomial (up to tenth degree inclusive) coefficients and the norm of the residuals were obtained which were decreasing with the increasing of the polynomial degree. It was shown that the better results are received using the artificial neural networks (ANN), somewhat worse ones employing a spline interpolant and shape-preserving interpolant. At the same time, the proposed models and methods can be used in calculation of solar radiation for various regions in the Russian Federation and other countries.

Performance analysis of solar still integrated with internal reflectors and fins

Effect of utilizing both internal reflectors and fins on the productivity of solar still for several months has been experimentally and numerically studied. Accurate theoretical describing single sloped solar still integrated with fins and internal reflectors is developed. The effect of fins shadow is considered. Accurate calculations of solar radiation absorbed by the basin water and basin liner are performed considering solar path diagram and hourly variation of beam radiation falling on tilted surfaces. The performance of solar still is estimated under the Jordan weather conditions. The developed model is validated experimentally and found in great agreement with experimental work. The simulation results of this study show that adding internal reflectors at three sides of solar still (south, east and west reflector) increases the efficiency about 13%, 20%, 28%, 33%, 37% and 46% in June, April, September, October, January, and December respectively. While the average monthly efficiency increase and the average monthly productivity increase are 29.1% and 3.014 L/day⋅m2 respectively. Furthermore, the results show that there is no significant effect on daily water output and basin water temperature when adding fins alone. Finally, adding internal reflectors with fins together, tremendous increase in both productivity and efficiency is achieved.

Object-Based Image Procedures for Assessing the Solar Energy Photovoltaic Potential of Heterogeneous Rooftops Using Airborne LiDAR and Orthophoto

Available renewable energy resources play a vital role in fulfilling the energy demands of the increasing global population. To create a sustainable urban environment with the use of renewable energy in human habitats, a precise estimation of solar energy on building roofs is essential. The primary goal of this paper is to develop a procedure for measuring the rooftop solar energy photovoltaic potential over a heterogeneous urban environment that allows the estimation of solar energy yields on flat and pitched roof surfaces at different slopes and in different directions, along with multi-segment roofs on a single building. Because of the complex geometry of roofs, very high-resolution data, such as ortho-rectified aerial photography (orthophotos), and LiDAR data have been used to generate a new object-based algorithm to classify buildings. An overall accuracy index and a Kappa index of agreement (KIA) of 97.39% and 0.95, respectively, were achieved. The paper also develops a new model to create an aspect-slope map, which combines slope orientation with the gradient of the slope and uses it to demonstrate the collective results. This study allows the assessment of solar energy yields through defining solar irradiances in units of pixels over a specific time period. It might be beneficial in terms of more efficient measurements for solar panel installations and more accurate calculations of solar radiation for residents and commercial energy investors.

ACTIVE SAMPLING AND MODEL BASED PREDICTION FOR FAST AND ROBUST DETECTION AND RECONSTRUCTION OF COMPLEX ROOFS IN 3D POINT CLOUDS

Abstract. 3D city models in Level-of-Detail 2 (LoD2) are nowadays inevitable for many applications such as solar radiation calculation and energy demand estimation. City-wide models are required which can solely be acquired by fully automatic approaches. In this paper we propose a novel method for the 3D-reconstruction of LoD2 buildings with structured roofs and dormers from LIDAR data. We apply a hybrid strategy which combines the strengths of top-down and bottom-up methods. The main contribution is the introduction of an active sampling strategy which applies a cascade of filters focusing on promising samples in an early stage and avoiding the pitfalls of RANSAC based approaches. Such filters are based on prior knowledge represented by (non-parametric) density distributions. Samples are pairs of surflets, i.e. 3D points together with normal vectors derived from a plane approximation of their neighborhood. Surflet pairs imply immediately important roof parameters such as azimuth, inclination and ridge height, as well as parameters for internal precision and consistency, giving a good base for assessment and ranking. Ranking of samples leads to a small number of promising hypotheses. Model selection is based on predictions for example of ridge positions which can easily be falsified based on the given observations. Our approach does not require building footprints as prerequisite. They are derived in a preprocessing step using machine learning methods, in particular Support Vector Machines (SVM).

Graphic method of calculation of the direct solar radiation received on the facade with available opposing building

Introduction. An approach to the development of a method for taking into account the influence of a single opposing building on direct solar radiation inflows to the building under study, taking into account all the irradiation periods of the facade under study, is presented. When calculating the consumption of thermal energy for heating and ventilation of a building in accordance with the method presented in regulatory documents, it is necessary to perform calculations of heat gain to the building from solar radiation. These calculations are carried out without taking into account the influence of the opposing building, what reduces the accuracy of the results. In foreign and domestic literature sources not found suitable for construction calculations and taking into account all periods of exposure methods. The objectives of this study are: the mathematical substantiation of the method, the possibility of its practical application, the formation of the calculation algorithm. Materials and methods. Calculations of the angular height and azimuth of the Sun by astronomical formulas, trigonometric calculations, construction of graphs of the tangents of changes in solar coordinates from the true solar time are applied. Results. The graphical method is proposed for determining irradiation periods by direct solar radiation of a facade of any orientation. The method is based on consideration of the formulas of the solar coordinates and the location of the opposing building. In this case, the graphic field is used to plot the changes in the tangents of the angular height of the Sun and the tangents of the difference between the azimuths of the Sun and the normal to the surface of the facade from the true solar time. The parameters of the building are applied to the graphic field and, in accordance with the proposed recommendations, the periods of irradiation of the facade are determined. Then the summation of direct solar radiation for the periods of irradiation of the facade is made. The algorithm of calculations on the example of a building in the presence of an opposing building is presented. The decrease of incoming direct solar radiation is shown. Conclusions. The developed graphic method is mathematically justified, has a practical orientation, which makes it relevant to the purpose and easy to use. The calculations for the presented method showed a significant decrease in the received direct solar radiation compared with the calculation without taking into account the influence of the opposing building, which shows the need to apply the method. The implementation of the method will contribute to an increase in the accuracy of calculations of direct solar radiation received on the facade and, therefore, the accuracy of calculations of energy consumption for heating and ventilation of the building.

A complete design data and performance parameter evaluation of a pilot scale solar updraft tower

Renewable energy sources are the best alternative for giving solution to the energy shortage and CO2 emission problems. Solar updraft tower is a relative novel technology for electricity production from solar energy. It consists of three main components; a solar air collector with absorber plate, central chimney, and a turbine. The objective of this work is to present complete design parameters of individual components of a small and less expensive prototype solar updraft tower. The main contents of this study are; solar radiation calculations, chimney design, solar wind turbine design calculations, heat loss and pressure loss estimations for collector. The pilot solar chimney power plant considered in this work consists of an air collector diameter of 3.5-m, the chimney diameter and height are 0.6 and 6 m, respectively. Theoretically the maximum velocity of air is achieved at chimney base is 1.9 m/s. The overall efficiency of the plant is estimated as 0.0019%.