A study of determining a model for prediction of solar radiation
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1 A study of determining a model for prediction of solar radiation Osman KARA, Bülent Yaniktepe, Coşkun Ozalp Osmaniye Korkut Ata University, Energy Systems Engineering Department, Osmaniye, Turkey
2 Contents Introduction System description Model description Results and discussion Conclusions 2
3 Introduction Solar radiation is defined as the amount of energy radiated from the sun in the form of electromagnetic waves that reaches the Earth surface. Solar radiation plays a key role in many various natural processes and hydrological cycle. Since, Solar radiation provides the energy for many natural processes such as photosynthesis, evaporation, evapotranspiration, cloud formation, snow melt, etc. [1]. 3
4 Introduction Various types of models have been developed by researchers for estimation of Solar radiation based on other meteorological data, which are more commonly available worldwide [2]. From these models it can be referred to artificial intelligence based models [3], remote sensing retrievals [4], single-layer and multi-layer radiative transfer models [5], and empirical models. 4
5 Introduction Based on the accuracy required for a research and available meteorological data, different types of empirical models have been proposed: sunshine-based models [6], temperaturebased models [7], cloud-based models [1]. 5
6 Introduction Solar energy is one of the most common renewable energy sources. Using of this energy is profited by solar radiation arriving in earth. Photovoltaic (PV) technologies using solar energy ensure a clean, renewable and sustainable energy source. PV technologies are quickly developing. Recently, PV has been used a great many large utility like photovoltaic power plants, residential systems, and irrigations. Accordingly, solar radiation model in summer season (June, July and August) is conducted by using Angstrom Prescott linear regression. Data is gathered from meteorological measuring device. 6
7 Introduction This device was established in 20 m high from the ground level. Measured data on solar radiation and sunshine duration has been recorded by a Vantage pro 2 station. In order to verify the predicted results, statistical methods as mean bias error (MBE), root mean square (RMSE), and relative percentage error are used. The new linear equation is obtained for monthly-average daily global solar radiance. 7
8 System Description Fig. 1. Measurement of Solar Radiation [8] Solar radiance measurements consist of global and/or direct radiation measurements taken periodically throughout the day. The measurements are taken using either a pyranometer (measuring global radiation) and/or a pyrheliometer (measuring direct radiation). The azimuth angle is the compass direction from which the sunlight is coming. The declination angle can be calculated by the equation Fig. 2. Azimuth Angle [8] 8
9 Model Description Angstrom Prescott formula is as follows: H/H 0 =a+b (S/S 0 ) (1) where H (monthly mean daily) and H 0 (daily) are global and extraterrestrial radiation on a horizontal surface respectively. Moreover, S (monthly average daily) and S 0 (monthly average maximum possible daily) are both sunshine duration 9
10 Model Description Basic statistical error analyses which are coefficient of determination (R 2 ), mean absolute percentage error (MAPE), mean absolute bias error (MABE), root mean square error (RMSE), were tested to measure accuracy and performance of the derived models. Where Hi,c and Hi,m are the ith calculated and measured values, respectively and x is the total number of observations. 10
11 Conclusions In this study, the ratios of H/H 0 and S/S 0 can be used to estimate the global radiation Osmaniye province in Turkey. It was seen that the equation which include the summer periods (June-July-August) gave better results. 11
12 Conclusions Several sunshine based models have been employed for estimating global solar radiation for Osmaniye [8-9]. The differences between the results of the different models are negligible. The linear degree equation is calculated, according to R-squared, MAPE, MABE and RMSE. The linear seasonal partitioning equation can be used to estimate the global solar radiation in Osmaniye. Table 1. The summary of all the statistical parameters for Linear MABE 1,1372 RMSE 0,9204 MAPE 38,306 R 2 0,
13 REFERENCES 1. Yang K, Koike T, Ye B. Improving estimation of hourly, daily, and monthly solar radiation by importing global data sets. Agric For Meteorol 2006;137: Almorox J, Hontoria C, Benito M. Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain). Appl Energy 2011;88: Kumar R, Aggarwal RK, Sharma JD. Comparison of regression and artificial neural network models for estimation of global solar radiations. Renew Sustain Energy Rev 2015;52: Alonso-Montesinos J, Batlles FJ, Bosch JL. Beam, diffuse and global solar irradiance estimation with satellite imagery. Energy Convers Manag 2015;105: Pawlak DT, Clothiaux EE, Modest MF, Cole JNS. Full spectrum correlated-k distribution for shortwave atmospheric radiative transfer. J Atmos Sci2004;61: Angstrom A. Solar and terrestrial radiation. Quart J Roy Meteorol Soc1924;50: Meza F, Varas E. Estimation of mean monthly solar global radiation as a function of temperature. Agric For Meteor 2000;100: Yanıktepe, B., and Y.A. Genc Establishing New Model for Predicting the Global Solar Radiation on Horizontal Surface in Osmaniye, TURKEY. 4. International Conference on Nuclear and Renewable Energy Resources, Antalya, Turkey. 9. Yaniktepe B., Kara O. and Ozalp C., Technoeconomic Evaluation for an Installed Small-Scale Photovoltaic Power Plant, International Journal of Photoenergy, Volume 2017 (2017), Article ID , 7 pages 13
14 THANKS FOR YOUR PARTICIPATION 14
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