Performance Analysis of Grid-Connected Solar Photovoltaic Systems under Variable Environmental Conditions
Description
The increasing demand for clean and sustainable energy has accelerated the deployment of grid-connected solar photovoltaic systems across residential, commercial, and utility-scale applications. While solar photovoltaic technology offers significant environmental and economic benefits, its performance is highly dependent on environmental conditions such as solar irradiance, temperature, and atmospheric factors. Variations in these parameters influence power output, system efficiency, and grid stability. This study presents a comprehensive performance analysis of grid-connected solar photovoltaic systems operating under variable environmental conditions. The research examines the impact of irradiance fluctuations, temperature variation, and seasonal changes on power generation efficiency, voltage stability, and energy yield. Mathematical modeling and empirical performance assessment are employed to evaluate system behavior. The findings highlight the critical role of environmental factors in photovoltaic performance and emphasize the need for adaptive control strategies to enhance system reliability and efficiency.
Files
IJAEAFEB26V3A0202.pdf
Files
(300.0 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:5febbbd0db253ff15802df622c20be9b
|
300.0 kB | Preview Download |
Additional details
Identifiers
Dates
- Issued
-
2026-02-08The increasing demand for clean and sustainable energy has accelerated the deployment of grid-connected solar photovoltaic systems across residential, commercial, and utility-scale applications. While solar photovoltaic technology offers significant environmental and economic benefits, its performance is highly dependent on environmental conditions such as solar irradiance, temperature, and atmospheric factors. Variations in these parameters influence power output, system efficiency, and grid stability. This study presents a comprehensive performance analysis of grid-connected solar photovoltaic systems operating under variable environmental conditions. The research examines the impact of irradiance fluctuations, temperature variation, and seasonal changes on power generation efficiency, voltage stability, and energy yield. Mathematical modeling and empirical performance assessment are employed to evaluate system behavior. The findings highlight the critical role of environmental factors in photovoltaic performance and emphasize the need for adaptive control strategies to enhance system reliability and efficiency.
References
- [1] J. A. Duffie and W. A. Beckman, Solar Engineering of Thermal Processes, 4th ed. Hoboken, NJ, USA: Wiley, 2013. [2] G. M. Masters, Renewable and Efficient Electric Power Systems, 2nd ed. Hoboken, NJ, USA: Wiley, 2013. [3] E. Skoplaki and J. A. Palyvos, "On the temperature dependence of photovoltaic module electrical performance: A review of efficiency/power correlations," Solar Energy, vol. 83, no. 5, pp. 614–624, 2009. [4] S. A. Kalogirou, "Solar energy engineering: Processes and systems," Progress in Energy and Combustion Science, vol. 30, no. 3, pp. 231–295, 2004. [5] T. Markvart and L. Castaner, Practical Handbook of Photovoltaics: Fundamentals and Applications, 2nd ed. Oxford, U.K.: Elsevier, 2012. [6] H. Patel and V. Agarwal, "MATLAB-based modeling to study the effects of partial shading on PV array characteristics," IEEE Trans. Energy Convers., vol. 23, no. 1, pp. 302–310, Mar. 2008. [7] A. Luque and S. Hegedus, Handbook of Photovoltaic Science and Engineering, 2nd ed. Chichester, U.K.: Wiley, 2011. [8] N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, "Optimization of perturb and observe maximum power point tracking method," IEEE Trans. Power Electron., vol. 20, no. 4, pp. 963–973, Jul. 2005. [9] A. Dolara, G. C. Lazaroiu, S. Leva, and G. Manzolini, "Experimental investigation of partial shading scenarios on PV systems," Energy Procedia, vol. 83, pp. 330–339, 2015. [10] International Electrotechnical Commission, Photovoltaic System Performance Monitoring – Guidelines for Measurement, Data Exchange and Analysis, IEC 61724, Geneva, Switzerland, 2017. [11] Ministry of New and Renewable Energy, Government of India, Annual Report 2022–23, New Delhi, India, 2023. [12] A. Mellit and S. Kalogirou, "Artificial intelligence techniques for photovoltaic applications: A review," Progress in Energy and Combustion Science, vol. 34, no. 5, pp. 574–632, 2008