Науковий вісник НГУ

Optimizing solar panel tilt angles across diverse Algerian terrain

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

Hits: 669

Authors:

A.Namoune*, orcid.org/0009-0008-0022-8466, Laboratory of Energetic Physics, Faculty of Exact Science, Department of Physics, University Frères Mentouri Constantine 1, Constantine, Algeria, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

A.Chaker, orcid.org/0000-0002-5111-1478, Laboratory of Energetic Physics, Faculty of Exact Science, Department of Physics, University Frères Mentouri Constantine 1, Constantine, Algeria

I.Saouane, orcid.org/0009-0000-9599-6039, Laboratory of Energetic Physics, Faculty of Exact Science, Department of Physics, University Frères Mentouri Constantine 1, Constantine, Algeria; Department of Matter Sciences, Chahid Laarbi Tebessi University, Tebessa, Algeria

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 079 - 084

https://doi.org/10.33271/nvngu/2024-5/079

Abstract:

Purpose. To optimize the efficiency and performance of a solar system by maximizing the capture of solar radiation through determining the most optimal solar panel tilt angle.

Methodology. Stochastic techniques are presently utilized for estimating, optimizing, and predicting various solar energy systems. The authors have developed an algorithm that simulates the echolocation behavior of bats.

Findings. To attain this objective, we evaluated different angles of inclination for the incident energy surface that will maximize the sunlight. Next, we compared the intensity of incident solar energy from a horizontal surface and the same surface tilted at the optimum angle. As a result, we determined the optimal tilt angles for other Algerian cities not covered by this study, based on two factors: geometry and climate, using multiple linear regression analysis. The results obtained reflect average monthly and annual values for solar panel tilt angles. These results depend on the latitude and sunshine levels of the locations studied.

Originality. The present study introduces a computational algorithm that utilizes the echolocation behavior of bats to determine the most advantageous tilt angle for a photovoltaic (PV) panel.

Practical value. Optimizing solar panel angles across various terrains in Algeria is crucial for maximizing the energy efficiency of photovoltaic installations. The optimization algorithm based on the echolocation behavior of bats allows for the determination of optimal angles by taking into account regional, climatic, and seasonal variations, thereby increasing energy production. This innovative approach offers an effective solution for improving the profitability of solar systems while contributing to sustainable development.

Keywords: optimal angle, solar panels, solar irradiation, Stochastic techniques, optimization algorithm, echolocation of bats

References.

1. Hwang, T., Kang, S., & Kim, J. T. (2012). Optimization of the building integrated photovoltaic system in office buildings – Focus on the orientation, inclined angle and installed area. Energy and Buildings, 46. https://doi.org/10.1016/j.enbuild.2011.10.041.

2. Kang, H., Hong, T., Jung, S., & Lee, M. (2019). Techno-economic performance analysis of the smart solar photovoltaic blinds considering the photovoltaic panel type and the solar tracking method. Energy and Buildings, 193. https://doi.org/10.1016/j.enbuild.2019.03.042.

3. Frid, S. E., Lisitskaya, N. V., & Muminov, Sh. A. (2023). The Optimal Angle of Inclination of Photovoltaic Modules to the Horizon, Energy Sources. Solar installations and their application, 59. https://doi.org/10.3103/S0003701X23600662.

4. Chang, Y. P. (2010). Optimal the tilt angles for photovoltaic modules in Taiwan. International Journal of Electrical Power & Energy Systems, 32, 956-964. https://doi.org/10.1016/j.ijepes.2010.02.010.

5. Talebizadeha, P., & Mehrabian, M. A. (2011). Prediction of the optimum slope and surface azimuth angles using the Genetic Algorithm. Energy and Buildings, 43, 2998-3005. https://doi.org/10.1016/j.enbuild.2011.07.013.

6. Tabet, I., Touafek, K., Bellel, N., Bouarroudj, N., Khelifa, A., & Adouane, M. (2014). Optimization of angle of inclination of the hybrid photovoltaic-thermal solar collector using particle swarm optimization algorithm. Journal of Renewable and Sustainable Energy 6, 053116. https://doi.org/10.1063/1.4896956.

7. Saouane, I., Chaker, A., Zaidi, B., & Shekhar, C. (2017). Optimal angle of polycrystalline silicon solar panels placed in a building using the ant colony optimization algorithm. European Physical Journal Plus, 132. 106. https://doi.org/10.1140/epjp/i2017-11381-4.

8. Datta, S., Bhattacharya, S., & Roy, P. (2016). Artificial Intelligence Based Solar Panel Tilt Angle Optimization and Its Hardware Implementation for Efficiency Enhancement. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 5(10), 7830-7842. https://doi.org/10.15662/ijareeie.2016.0510006.

9. Ramamurthi, P. V., & Nadar, E. R. Samuel (2020). IoT-Based “Energy Monitoring and Controlling of an Optimum Inclination Angle of the Solar Panels”. IETE Journal of Research. https://doi.org/10.1080/03772063.2020.1754301.

10. Calabrò, E. (2013). An Algorithm to Determine the Optimum Tilt Angle of a Solar Panel from Global Horizontal Solar Radiation. Journal of Renewable Energy, 307547. https://doi.org/10.1155/2013/307547.

11. Ismail, M. S., Moghavvemi, M., & Mahlia, T. M. I. (2013). Analysis and Evaluation of Various Aspects of Solar Radiation in the Palestinian Territories. Energy Conversion and Management, 73, 57-68. https://doi.org/10.1016/j.enconman.2013.04.026.

12. Karaveli, A. B., & Akinoglu, B. G. (2018). Estimating daily global solar radiation in hot semi-arid climate using an efficient hybrid intelligent system. International Journal of Green Energy, 15. https://doi.org/10.1140/epjp/s13360-022-02398-z.

13. Rajkumar, K., & Kumar, K. A. (2023). Application of firefly algorithm for power estimations of solar photovoltaic power plants. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 45. https://doi.org/10.1080/15567036.2021.1916653.

14. Jaouane, M., Fakkahi, A., Ed-Dahmouny, A., El-Bakkari, K., Turker Tuzemen, A., Arraoui, R., Sali, A., & Ungan, F. (2023). Modeling and simulation of the influence of quantum dots density on solar cell properties. European Physical Journal Plus, 138. 148. https://doi.org/10.1140/epjp/s13360-023-03736-5.

15. Yang, X.-S., & He, X. (2013). Bat algorithm: literature review and applications. International Journal of Bio-Inspired Computation, 141-149. https://doi.org/10.1504/IJBIC.2013.055093.

16. Document Technique Réglementaire, D. T. R. C 3-4 (2005). Règles de calcul des rapports calorifique des bâtiments “CLIMATISATION” fascicule 2. Centre National d’Etudes et de Recherches Intégrées du Bâtiment. Ministère de L’habitat, Algérie.

17. Jims, G., Wessley, J., Narciss Starbell, R., & Sandhya, S. (2017). Modelling of Optimal Tilt Angle for Solar Collectors Across Eight Indian Cities. International journal of renewable energy research.  https://doi.org/10.20508/ijrer.v7i1.4729.g6996.

• < Prev
• Next >