Prediction of the optimum slope and surface azimuth angles using the Genetic Algorithm

In this paper, the Genetic Algorithm is applied to calculate the optimum slope and surface azimuth angles for solar collectors to receive maximum solar radiation. An area of Iran is selected to verify the results of this algorithm. The optimum angles and the collector input solar energies for these angles are calculated in hourly, daily, monthly, seasonally and yearly bases respectively. Then, the influence of different combinations of solar radiation components on the optimum slope angle and the energy gain is investigated. The results show that the Genetic Algorithm is a useful technique to find the optimum angles specifically when the number of independent parameters is large. The results show that the daily, monthly and yearly optimum surface azimuth angles for receiving the maximum solar energy are zero. Adjusting the collector at the daily optimum slope angle slightly increases the collector input energy compared with the case of monthly optimum slope angle so that the gain of solar energy is almost the same. The results also show that the hourly optimum surface azimuth angle is not zero and mounting the solar collector at the hourly optimum slope and azimuth angles increases the input energy significantly compared with the case of daily optimum angles. It is shown that the optimum slope angles are mostly dependent on the beam solar radiation. Furthermore, the results indicate that the optimum slope angles of solar collector and Photovoltaic panels are almost the same.

► Calculating the optimum slope and surface azimuth angles of solar collectors.
► Using the Genetic Algorithm to estimate the maximum gain of solar energy.
► Comparing the solar energy gain in different optimum angles.
► Comparing the energy gain for solar collectors and photovoltaic panels.