Design of system model and program for estimation of annual PV energy production: a comparative study

Yıl 2024, Cilt: 26 Sayı: 1, 53 - 72, 19.01.2024

Mehmet Fatih Beyoğlu Metin Demirtaş

https://doi.org/10.25092/baunfbed.1211834

Öz

Suitability evaluation of a location for power generation plant installation requires long-term measurements and calculations. Since the energy production values foreseen in the project process of the solar power plant directly affect the return period of the project cost, it is of great importance to make the calculations correctly. In this study, a model and program were designed to find the closest estimation values. Energy production values are estimated for 54 kWh solar power plant (SPP) in Balikesir using designed model. It is important that the SPP consists of two groups with different angles, directions and capacities in terms of comparing the accuracy of the calculation. The developed model used the hourly meteorological data and catalog values to Energy production calculations. The model allows making calculations for all the angles of the sun and the characteristic data of the system. The developed program was compared with energy production results of PVGIS (Photovoltaic Geographical Information System) programs. As a result of analysis, it has been observed that more realistic and closer results were produced by means of the designed program. The advantage of this program is that more parameters of the photovoltaic (PV) system can be monitored compared to the other programs.

Anahtar Kelimeler

Solar energy, Matlab/Simulink, PVGIS, Sarah 2, prediction of SPP energy generation.

Yıllık PV enerji üretiminin tahmini için sistem modeli ve programın tasarımı: karşılaştırmalı bir çalışma

Öz

Bir yerin elektrik üretim tesisi kurulumuna uygunluğunun değerlendirilmesi, uzun vadeli ölçümler ve hesaplamalar gerektirir. Güneş enerjisi santralinin proje sürecinde öngörülen enerji üretim değerleri, proje maliyetinin geri dönüş süresini doğrudan etkilediği için hesaplamaların doğru yapılması büyük önem arz etmektedir. Bu çalışmada en yakın tahmin değerlerini bulmak için bir model ve program tasarlanmıştır. Tasarlanan model kullanılarak Balıkesir ilindeki 54 kWh güneş enerjisi santrali (GES) için enerji üretim değerleri tahmin edilmiştir. GES'in farklı açılara, yönlere ve kapasitelere sahip iki gruptan oluşması hesaplamanın doğruluğunun karşılaştırılması açısından önemlidir. Geliştirilen model, saatlik meteorolojik verileri ve katalog değerlerini Enerji üretimi hesaplamalarında kullanmıştır. Model, güneşin tüm açılarının ve sistemin karakteristik verilerinin hesaplanmasına olanak sağlar. Geliştirilen program PVGIS (Photovoltaic Geographical Information System) programlarının enerji üretim sonuçları ile karşılaştırılmıştır. Yapılan analizler sonucunda tasarlanan program sayesinde daha gerçekçi ve yakın sonuçlar üretildiği görülmüştür. Bu programın avantajı diğer programlara göre fotovoltaik (FV) sistemin daha fazla parametresinin izlenebilmesidir.

Anahtar Kelimeler

Güneş enerjisi, Matlab/Simulink, PVGIS, Sarah 2, GES enerji üretim tahmini

Kaynakça

• Gu, W., Ma, T., Li, M., Shen, L., & Zhang, Y. (2020). A coupled optical-electrical-thermal model of the bifacial photovoltaic module. Applied Energy, 258(October 2019), 114075, 1-14.
• Karafil, A., Ozbay, H., Kesler, M., & Parmaksiz, H., (2016), Calculation of optimum fixed tilt angle of PV panels depending on solar angles and comparison of the results with experimental study conducted in summer in Bilecik, Turkey. ELECO 2015, 971–976
• Copper, J. K., & Sproul, A. B. (2012). Comparative study of mathematical models in estimating solar irradiance for Australia. Renewable Energy, 43, 130–139.
• Shen, C., He, Y. L., Liu, Y. W., & Tao, W. Q. (2008). Modelling and simulation of solar radiation data processing with Simulink. Simulation Modelling Practice and Theory, 16(7), 721–735.
• Tina, G. M., Ventura, C., Sera, D., & Spataru, S. (2017). Comparative assessment of PV plant performance models considering climate effects. Electric Power Components and Systems, 45(13), 1381–1392.
• Al-Ghussain, L., Taylan, O., Abujubbeh, M., & Hassan, M. A. (2023). Optimizing the orientation of solar photovoltaic systems considering the effects of irradiation and cell temperature models with dust accumulation. Solar Energy, 249(October 2022), 67–80.
• Rustemli, S. & Dincadam, F. & Demirtas, M. (2010). Performance comparison of the sun tracking system and fixed system in the application of heating and lighting. Arabian Journal for Science and Engineering. 35. 171-183.
• Beyoğlu, M. F. (2011). Comparison of efficiencies of dual axis solar tracking system and fixed axis PV system in Balikesir City. Balıkesir University Institude of Science, Master thesis.
• Abood, A., A. (2015). A comprehensive solar angles simulation and calculation using Matlab. International Journal of Energy and Enviroment, 6(4), 367–376.
• Jazayeri, K., Uysal, S., & Jazayeri, M. (2013). Matlab/Simulink based simulation of solar incidence angle and the sun’s position in the sky with respect to observation points on the Earth. Proceedings of 2013 International Conference on Renewable Energy Research and Applications, ICRERA 2013, 173–177.
• Humada, A. M., Darweesh, S. Y., Mohammed, K. G., Kamil, M., Mohammed, S. F., Kasim, N. K., Mekhilef, S. (2020). Modeling of PV system and parameter extraction based on experimental data: Review and investigation. Solar Energy, 199, 742–760.
• Lo Brano, V., Ciulla, G., & Di Falco, M., (2014), Artificial neural networks to predict the power output of a PV panel. International Journal of Photoenergy, 1-12.
• Yildiran, N., & Tacer, E., (2016), Identification of photovoltaic cell single diode discrete model parameters based on datasheet values. Solar Energy, 127, 175–183
• Anand, A., & Akella, A. K. (2016). Modelling and analysis of single diode photovoltaic module using Matlab / Simulink, 6(3), 29–34.
• Vinod, Kumar, R., & Singh, S. K. (2018). Solar photovoltaic modeling and simulation: As a renewable energy solution. Energy Reports, 4, 701–712.
• Bouraiou, A., Hamouda, M., Chaker, A., Sadok, M., Mostefaoui, M., & Lachtar, S. (2015). Modeling and simulation of photovoltaic module and array based on one and two diode model using Matlab/Simulink. Energy Procedia, 74, 864–877.
• Lidaighbi, S., Elyaqouti, M., Ben Hmamou, D., Saadaoui, D., Assalaou, K., & Arjdal, E. (2022). A new hybrid method to estimate the single-diode model parameters of solar photovoltaic panel. Energy Conversion and Management: X, 15, 100234.
• Vinod, Kumar, R., & Singh, S. K. (2018). Solar photovoltaic modeling and simulation: As a renewable energy solution. Energy Reports, 4, 701–712.
• Huld, T., Müller, R., & Gambardella, A. (2012). A new solar radiation database for estimating PV performance in Europe and Africa. Solar Energy, 86(6), 1803–1815.
• Beyoğlu, M.F., Demirtaş, M. (2019). A comparative evalution of photovoltaic power plant energy production established in Balikesir province and production forecasting programs. International Marmara Sciences Congress (Autumn) 2019 Proceedings Book (Natural and Applied Sciences), (November), 401–406.
• Tian, H., Mancilla-david, F., Ellis, K., Jenkins, P., & Muljadi, E. (2012). A detailed performance model for photovoltaic systems preprint. Solar Energy Journal, (July), 1-54.
• Neamt, L., & Chiver, O., (2013), A simple method for photovoltaic energy estimation. Environment and Electrical Engineering (EEEIC), 2013 12th International Conference On, (4), 513–516
• AbdelHady, R. (2017). Modeling and simulation of a micro grid-connected solar PV system. Water Science, 31(1), 1–10.
• Mohanty, P., Bhuvaneswari, G., Balasubramanian, R., & Dhaliwal, N. K. (2014). Matlab based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions. Renewable and Sustainable Energy Reviews, 38, 581–593.
• de la Parra, I., Muñoz, M., Lorenzo, E., García, M., Marcos, J., & Martínez-Moreno, F. (2017). PV performance modelling: A review in the light of quality assurance for large PV plants. Renewable and Sustainable Energy Reviews, 78(March), 780–797.
• Tian, Z., Deng, J., Zhang, S., Yao, R., & Shao, L. (2020). A quick measurement method for determining the incidence angle modifier of flat plate solar collectors using spectroradiometer. Solar Energy, 201(March), 746–750.
• Huang, C., Huang, M., & Chen, C. (2012). A novel power output model for photovoltaic systems, 2, 139-147.
• Correa-Betanzo, C., Calleja, H., & De León-Aldaco, S. (2018). Module temperature models assessment of photovoltaic seasonal energy yield. Sustainable Energy Technologies and Assessments, 27(March), 9–16.
• Dobos, A. P. (2014). PVWatts Version 5 Manual.