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Modelling and optimisation of solar photovoltaic power using response surface methodology

Original scientific paper

Journal of Sustainable Development of Energy, Water and Environment Systems
ARTICLE IN PRESS (scheduled for Vol 12, Issue 04 (general)), 1120519
DOI: https://doi.org/10.13044/j.sdewes.d12.0519 (registered soon)
Abdulrahman Mohammad1, Mudhar Al-Obaidi2 , Hassan Dakkama2, Haitham Bahlol2
1 Middle Technical University, Dayala, Iraq
2 Middle Technical University, Baghdad, Iraq


Modeling and analysing the relationship between the operating conditions of solar photovoltaic module such as the solar irradiance, module temperature, wind speed, dust, air moisture and the performance metric of generated power is considered as an interesting subject. In the current study, the response surface methodology based on the D-optimal Design approach is applied to model an optimise the generated power of photovoltaic module using desirability function. The optimisation has considered the interaction of three essential independent variables including: solar irradiance (169.2-981.7) , module temperature (36.14-67.01) °C and wind speed (0.5-2.4) m/s with the generated power (dependent variable). A data set of 328 reading is collected and analysed. In this regard, the suggested response model uses two factorial order with polynomial equation. The response surface methodology model has indicated a linear relationship between the independent variables and power generated with a coefficient of determination of 98.45%. The optimal operating conditions of 968.04  solar irradiance, module temperature 41.82 °C and wind speed 1.67 m/s are obtained with a maximum desirability function of 0.985. This in turn has elaborated a maximum generated power of 128.883 W. Interestingly, this optimised power is in corroboration with the experimental value of 127.1 W at the same conditions. Notably, the module temperature has a considerable negative influence on the generated power.


Keywords: Photovoltaic (PV); Power; Solar irradiance; Module temperature; Response surface methodology (RSM); Optimisation.

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