Currently, photovoltaic (PV) installations target a maximization of annual energy yield. However, as the grid penetration of PV is increasing, PV electricity generation will need to match better with local load profiles. Especially the seasonal variabilities remain challenging. While wind and PV tend to have complementary seasonal variability, wind turbine installation faces limitations especially in densely populated areas. In this paper, we discuss how this challenge may be addressed with climate- and consumption-specific PV module technology. In particular, we demonstrate how the temperature coefficient of a PV system can impact the energy yield throughout the year. In colder climates, higher temperature coefficients allow for a better energy balance, favoring production in colder seasons without a significant reduction of yearly energy yield. Simulations for locations at high latitude, and colder climates, indicate that higher temperature coefficients and improved low-light behavior not only enable a higher energy yield in cold seasons, but also negligible losses in the overall yearly energy yield compared to lower temperature coefficients and slightly better low-light behavior. Simulations show that these results can be obtained using commercial PV modules. More broadly, they indicate how PV module technology may be optimized depending on the location and climate.

With the growing competition of utility-scale photovoltaic (PV) plants to provide electricity to the grid, accurate energy yield simulation is becoming essential. Apart from irradiance, forced convection can have an equally significant impact on solar cell temperature, which in turn affects the power output, hence the energy yield. As a consequence, the wind must be taken into account for an accurate estimation of PV installations' energy yield. However, no earlier studies have systematically investigated the impact of wind on precise energy yield simulation. In this study, we investigate how sensitive is PV module's output to forced convection. First, we reveal a significant deviation between the simulated PV module's energy yield and cell temperature compared to experimental results in case dynamic wind effects are neglected. Secondly, for controlled incremental forced convection with a steady state scenario, we show that for higher wind speed the change of PV module's cell temperature and power output is small with different forced convection. Whereas, for the low wind speed, small changes of forced convection imply a larger variation of the PV module's cell temperature and power output. This shows that for high wind speed region energy yield estimation is less sensitive on modelling errors. Whereas for the low wind speed region it is highly sensitive.