Procena učinka solarnog fotonaponskog sistema upotrebom softvera EnergyPlus i veb aplikacije PVGIS
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Apstrakt
Precizna procena učinka solarnog fotonaponskog (FN) sistema zavisi od preciznosti softverskih alata koji se koriste za simulaciju. U ovom radu izvršeno je poređenje softvera EnergyPlus i veb-aplikacije PVGIS. EnergyPlus predstavlja inženjerski softver koji omogućava detaljno simuliranje rada FN sistema, uzimajući u obzir veliki broj ulaznih parametara koji utiču na njihov učinak. S druge strane, veb-aplikacija PVGIS nudi pojednostavljen pristup, ali njena tačnost u poređenju sa inženjerskim simulacija nije uvek jasno definisana. Cilj ovog rada je da ispita u kojoj meri PVGIS može da pruži rezultate uporedive sa onima dobijenim pomoću EnergyPlus simulacija. U tu svrhu sprovedene su uporedne simulacije za devet različitih lokacija na teritoriji Republike Srbije. U okviru veb-aplikacije PVGIS realizovane su simulacije primenom dve datoteke meteoroloških podataka (SARAH3 i ERA5), koje su potom upoređene sa rezultatima dobijenim korišćenjem EPW datoteke meteoroloških podataka u softveru EnergyPlus. Rezultati ukazuju na razlike u rasponu od 3,23% do 9,11% između SARAH3 i EPW datoteka, kao i od -2,89% do 1,82% za ERA5 i EPW datoteke. Dodatno, sprovedena je analiza za poznatu lokaciju u centru Kragujevca, na kojoj bi se solarni prijemnik tokom većeg dela godine nalazio u senci. Rezultati EnergyPlus simulacije pokazali su 63,4% manju proizvodnju u odnosu na PVGIS simulaciju sa SARAH3 datotekom, odnosno 65,6% manju u poređenju sa ERA5 datotekom. Dobijeni rezultati jasno ukazuju da PVGIS veb-aplikacija može pružiti dovoljno precizne procene rada solarnih FN sistema kada se koristi ERA5 datoteka, samo ako su analizirane lokacije neosenčene.
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Reference
[2] Jager, W., Simulating the diffusion of photovoltaic systems: A behavioral perspective, Energy Policy, 34 (2006), 14, pp. 1935-1943.
[3] *** Kazem, A. H., et al., A systematic review of solar photovoltaic energy systems design mod-elling, algorithms, and software, Energy Sources, Part A: Recovery, Utilization, and Environ-mental Effects, 44 (2022), 3, pp. 6709-6736.
[4] *** Islam, A. Md., et al., A comprehensive evaluation of photovoltaic simulation software: A decision-making approach using Analytic Hierarchy Process and performance analysis, Energy Strategy Reviews, 58 (2025), 101633.
[5] Wu, C., Comparison Study of PVWatts and EnergyPlus in Simulating Electricity Production of Fixed PV Array, (2025), Available at SSRN 5429506.
[6] Gurupira, S., Rix, J. A., PV simulation software comparisons: PVSYST, NREL SAM AND PVLIB, Conf.: Saupec. 2017.
[7] Mohammadi, S. A. D., C. Gezegin, Design and simulation of grid-connected solar PV system using PVSYST, PVGIS and HOMER software. International Journal of Pioneering Technology and Engineering, 1(2022), pp. 36-41.
[8] Psomopoulos, C. S., et al., A Comparative Evaluation of Photovoltaic Electricity Production Assessment Software (PVGIS, PVWatts and RETScreen), Environmental Processes, 2 (2015), pp. 175-189.
[9] Larasati, P. D. L. P. D., R. A. N. R. A., Nugraha, Evaluasi Perencanaan Photovoltaic On Grid Menggunakan Software Berbasis Web: Studi Kasus Bandara Udara Internasional Jendral Ahmad Yani Kota Semarang. Knowledge on Sustainable Engineering, Vulnerability, Automation, and Software Intelligence, 1 (2025), 1, pp. 13-25.
[10] *** https://pvgis.com/en/guide-complete-pvgis
[11] *** https://joint-research-centre.ec.europa.eu/photovoltaic-geographical-information-system-pvgis_en
[12] Meral, M. E., F. Dincer, A review of the factors affecting operation and efficiency of photovol-taic based electricity generation systems. Renewable and Sustainable Energy Reviews, 15(2011), 5, pp. 2176-2184.
[13] Das, U. K., et al. Forecasting of photovoltaic power generation and model optimization: A re-view, Renewable and Sustainable Energy Reviews, 81 (2018), 1, pp. 912-928.
[14] Jimenez-Torres, M., et al., The Importance of Accurate Solar Data for Designing Solar Photo-voltaic Systems—Case Studies in Spain, Sustainability, 9 (2017), 2, 247.
[15] *** https://www.totemtim.com/wp-content/uploads/LUXEN-TOPCon-SERIES-N5-MONOFACIAL-144cells-570-590w-MONO-SERBIA.pdf
[16] *** https://pvgis.com/en/pvgis-5-3
[17] *** https://joint-research-centre.ec.europa.eu/photovoltaic-geographical-information-system-pvgis/getting-started-pvgis/pvgis-user-manual_en
[18] *** https://energyplus.net/
[19] *** https://energyplus.net/assets/nrel_custom/pdfs/pdfs_v24.1.0/EnergyPlusEssentials.pdf
[20] Nikolić, N., D. Nikolić, Grejanje i Klimatizacija – osnove proračuna, modeliranja i simulacije, Faculty of Engineering University of Kragujevac, Kragujevac 2025.
[21] Guyot, D., et al. Building energy model calibration: A detailed case study using sub-hourly measured data, Energy and Buildings 223 (2020): 110189.
[22] Jradi, M., et al. ObepME: An online building energy performance monitoring and evaluation tool to reduce energy performance gaps, Energy and Buildings 166 (2018): 196-209.
[23] Jradi, M., C. Veje, B. N. Jørgensen, Deep energy renovation of the Mærsk office building in Denmark using a holistic design approach, Energy and Buildings 151 (2017): 306-319.
[24] Yin, R., S. Kiliccote, M. A. Piette, Linking measurements and models in commercial buildings: A case study for model calibration and demand response strategy evaluation, Energy and Build-ings 124 (2016): 222-235.
[25] Lam, K. P., et al., An EnergyPlus whole building energy model calibration method for office buildings using occupant behavior data mining and empirical data, ASHRAE Journal (2014): 160-167.
[26] *** https://energyplus.net/assets/nrel_custom/pdfs/pdfs_v24.2.0/EngineeringReference.pdf
[27] *** https://energyplus.net/assets/nrel_custom/pdfs/pdfs_v24.1.0/InputOutputReference.pdf
[28] *** https://climate.onebuilding.org/#gsc.tab=0
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