THERMAL SCIENCE

International Scientific Journal

ENERGY EFFICIENCY CART MODELING OF SOLAR ENERGY COLLECTORS BY GENETIC PROGRAMMING

ABSTRACT
Uniquely constructed technical solution of solar energy collector is presented in this paper. It presents a great breakthrough in the field of energy efficiency and successful exploitation of renewable energy sources. Principle of this high-temperature energy storage enables the energy accumulated from the sun to be yielded when necessary and continuously, 24 hours a day and 365 days a year. Furthermore this paper is containing a modeling of sun irradiance, generated energy intensity for flat solar panel and for Prof. Petrovic concentrator. Modeling is made with genetic programming and it is found out that genetic programming is suitable method for modeling of energy intensity. It offers results which are within acceptable tolerances while maintaining ease of use and short computational time. Genetic programming yielded results of 12,97%, 14,6% and 9,25% average percent error for irradiance, flat solar panel and Prof. Petrovic solar concentrator respectively. [Projekat Ministarstva nauke Republike Srbije, br. TR 35015]
KEYWORDS
PAPER SUBMITTED: 2015-09-29
PAPER REVISED: 2015-12-13
PAPER ACCEPTED: 2016-01-08
PUBLISHED ONLINE: 2016-02-20
DOI REFERENCE: https://doi.org/10.2298/TSCI150929031K
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2016, VOLUME 20, ISSUE Supplement 2, PAGES [S471 - S479]
REFERENCES
  1. Zheng, H., et al., Combination of a Light Funnel Concentrator with a Deflector for Orientated Sunlight Transmission, Energy Conversion and Management, 88 (2014), Dec., pp. 785-793
  2. Sencan, A., et al., Different Methods for Modeling Absorption Heat Transformer Powered by Solar Pond, Energy Conversion and Management, 48 (2007), 3, pp. 724-735
  3. Wu, W., et al., Hybrid Solar Concentrator with Zero Self-Absorption Loss, Solar Energy, 84 (2010), 12, pp. 2140-2145
  4. Velazquez, N., et al., Numerical simulation of a Linear Fresnel Reflector Concentrator used as direct generator in a Solar-GAX cycle, Energy Conversion and Management, 51 (2010), 3, pp. 434-445
  5. Jorge, F., Armando C. O., Numerical Simulation of a Trapezoidal Cavity Receiver for a Linear Fresnel Solar Collector Concentrator, Renewable Energy, 36 (2011), 1, pp. 90-96
  6. Nazimi, S., et al., Optical Characterization of 3-D Static Solar Concentrator, Energy Conversion and Management, 64 (2012), Dec., pp. 579-586
  7. Maimoon, A., Fahad, A. S., Optimization of Heliostat Field Layout in Solar Central Receiver Systems on Annual Basis Using Differential Evolution Algorithm, Energy Conversion and Management, 95 (2015), May, pp. 1-9
  8. Li, X., et al., Performance Investigation on Solar Thermal Conversion of a Conical Cavity Receiver Employing a Beam-down Solar Tower Concentrator, Solar Energy, 114 (2015), Apr., pp. 134-151
  9. Somchai, K., Ekawit, C., Theory and Experiment of a Two-dimensional Cone Concentrator for Sunlight, Solar Energy, 82 (2008), 2, pp. 111-117
  10. Babić, I., Đurišić, Z., Impact of Daily Variation of Solar Radiation on Photovoltaic Plants Economy at the Open Market, Thermal Science, 19 (2015), 3, pp. 837-844
  11. Gostimirovic, M., et al., Surface Layer Properties of the Workpiece Material in High Performance Grinding, Metalurgija, 51 (2012), 1, pp. 105-108
  12. Zadeh, M., Thermo-economic-environmental Optimization of a Microturbine Using Genetic Algorithm, Thermal Science, 19 (2015), 2, pp. 475-487
  13. Pavlović, T., et al., Renewable Sources of Energy (in Serbian), Akademija nauka i umjetnosti Republike Srpske, Banja Luka, Republic of Srpska, B&H, 2013
  14. Petrović, V., Long-Term Heat Storage Device and Method for Long-Term Heat Storage of Solar Energy and Other Types of Energy with Changing Availability, Patent US20150159959 A1, (2015)
  15. Kovač, P., et al., Influence of Data Quantity on Accuracy of Predictions in Modeling Tool Life by the Use of Genetic Algorithms, International Journal of Industrial Engineering, 21 (2014), 1, pp. 14-21
  16. Kovač, P., et al., Application of Fuzzy Logic and Regression Analysis for Modeling Surface Roughness in Face Milling, Journal of Intelligent Manufacturing, 24 (2012), 4, pp. 755-762
  17. Nagy, Lj., et al., Matlab Algorithms for the Lighting Control on the Constant Value, Journal of Production Engineering, 14 (2011), 1, pp. 47-50
  18. Hrnjica, B., GPdotNET V4.0 – artificial intelligence tool [Computer program], http://gpdotnet.codeplex.com

© 2019 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence