Hot dry climate regions enjoy high solar irradiation, albeit with high ambient temperatures. These two factors have a contradictory effect on the power generated from PV systems. This work studies the combined effect of high ambient temperature and high irradiation on the net performance of PV systems. The study is based on monitoring a grid-connected 5 kW PV system installed on the rooftop of the Energy Research Center of the University of Khartoum, Sudan. The performance was monitored by meteorological and power measurement equipment from April 2017 to March 2018. The results showed stable power output from the PV system with an average final yield of 4.57 kWh/kWp and a 0.21 standard deviation from this average value. The stability in power output is due to the compensation of the efficiency degradation due to high temperature by high irradiation in summer. This is combined with the relatively low irradiation in winter compensated by the low temperature effect in winter. The annual deviation of the temperature and irradiation is small in Khartoum due to its proximity to the equator. The semi desert climate, offers Khartoum notably few annual cloudy hours. These characteristics were compared with the annual performance of other countries with different climates. The conclusion from this work on hot dry regions is that despite the negative effect of temperature, the annual output power from the system tends to be stable due to the substitution contributed by the regionally high radiation and the relatively cool winter climate.

This paper presents a simplified dimensionless model for predicting the electrical performance of photovoltaic (PV) modules under varying irradiance and temperature conditions. Unlike conventional equivalent-circuit models that require detailed parameter extraction, the proposed approach employs dimensional analysis to establish direct relationships between key PVoperating points and normalized environmental variables, without assuming a predefined physical model. The model is validated using experimental datasets from Sandia National Laboratories, covering a wide range of irradiance (100–1100 W/m²) and module temperatures (15°C–75°C). Model accuracy is evaluated using normalized root mean square error (nRMSE). The results demonstrate strong predictive capability, with average nRMSE values below 2.5% for maximum power point voltage and current, below 1% for maximum power, and low errors for open-circuit voltage and short-circuit current. The proposed model provides a computationally efficient and accurate alternative to conventional PV models. Moreover, the dimensionless framework offers strong potential for predicting the performance of complex multiphysics energy systems, where conventional equivalent-circuit-based approaches are often difficult to apply or fail to achieve satisfactory accuracy.

This paper presents a simplified dimensionless model for predicting the electrical performance of photovoltaic (PV) modules under varying irradiance and temperature conditions. Unlike conventional equivalent-circuit models that require detailed parameter extraction, the proposed approach employs dimensional analysis to establish direct relationships between key PV operating points and normalized environmental variables, without assuming a predefined physical model. The model is validated using experimental datasets from Sandia National Laboratories, covering a wide range of irradiance (100–1100 W/m²) and module temperatures (15–75 °C). Model accuracy is evaluated using normalized root mean square error (nRMSE). The results demonstrate strong predictive capability, with average nRMSE values below 2.5% for maximum power point voltage and current, below 1% for maximum power, and low errors for open-circuit voltage and short-circuit current. To the best of the authors’ knowledge, this represents the first application of the Buckingham $\pi$ theorem to derive dimensionless scaling laws for predicting PV module electrical characteristics under varying irradiance and temperature conditions. The proposed model provides a computationally efficient and accurate alternative to conventional PV models. Moreover, the dimensionless framework offers strong potential for predicting the performance of complex multiphysics energy systems, where conventional equivalent-circuit-based approaches are often difficult to apply or fail to achieve satisfactory accuracy.