Abstract
The optimal integration of Photovoltaic (PV) systems into an electric grid is dependent upon the total output power of the PV system. To optimize the output power of a PV system, the modules must be positioned at an optimal tilt angle (OTA) to maximize the absorption of solar radiations. This research focused on a mathematical model to optimize incident solar radiation. The proposed model is used to determine the OTA and evaluate its impact on the optimum configuration and power output capacity using MATLAB for six cities located in different temperature zones across Pakistan. The isotropic and anisotropic models have been used to calculate the total solar radiations (H(T)) on a sloped surface. During the summer season, all four selected models present similar findings in terms of the monthly average daily solar radiations on the tilted surface. During the winter season, the anisotropic models performed better than the isotropic models. The anisotropic model achieved a 14.82% energy increase in January and a 0.16% increase in June compared to the isotropic model. We present monthly and annual OTA calculated from the anisotropic model. The OTA has been determined for the H(T) across slope values ranging from 0° to 90° with a 1° resolution. The monthly OTA using anisotropic model for the Faisalabad, Lahore, Multan, RYK, Islamabad and Karachi ranges from 7° to 54°, 7° to 53°, 6° to 52°, 5° to 52°, 10° to 58° and 1° to 50° and the annual OTA for cities has been calculated to be 30.5°, 30.25°, 29.33°, 28.66°, 33.34° and 25.5° respectively. Utilizing the OTA calculated from the selected model, a PV array with a rated power of 52.200 kW has been used to analyze the system performance. The annual average output power at the monthly OTA results in gains of 8.83%, 9.40%, 9.78%, 9.77%, 9.82%, and 9.91% compared to the annual OTA. This research study is particularly beneficial for researchers and the industry in deploying PV systems across different climatic zones of Pakistan, intending to maximize output power while minimizing energy costs.