Nowadays, material manufacturers are engineering module materials to optimize the energy production of the PV modules. One of the elements which can be influenced is the optical scattering of a material. In this study, we quantified the effect of a scattering front encapsulant on the energy production of PV modules. First, a wavelength-dependent scattering model was developed in the ray-tracing software PVlighthouse. This model was used to find the optimal scattering conditions, looking at the photo-generated current for a glass-glass PV module with flat front surface. It was shown that a gain of +0.63 mA/cm² can be obtained for optimal scattering conditions. The scattering is mostly beneficial when the light strikes the module surface at a perpendicular angle. The outcome of the optimization study was implemented in IMEC’s energy yield simulation framework. This framework was used to estimate the energy gain of PV module with scattering front encapsulant when installed in Kuwait’s desert. It was shown that an energy production gain of 1.8% can be expected in case of a glass-glass module with flat front surface and ARC coating.

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.

Reconfigurable photovoltaic modules represent an effective solution to improve PV system resilience to partial shading. Indeed, the availability of different configurations increases energy generation under non-uniform conditions. However, the additional components that are active under uniform conditions lead to higher losses compared to equivalent static solutions. This paper presents a methodology for the design of optimized reconfigurable PV modules, balancing losses under uniform conditions and gain under partial shading. First, feasible reconfigurable module instantiations are selected given some design constraints. Then, the search space is further reduced by taking into account the typical operating conditions of the module. Finally, the best module layouts are chosen based on performance consideration. Results for a specific case study are presented to show the feasibility of the proposed methodology.

PV module testing under standard conditions is an important and well-established procedure, which plays a vital role in module rating. However, PV modules rarely operate at standard conditions therefore their field performance should be predicted based on long term outdoor monitoring or by means of models – so called energy yield models, which combine PV module characteristics with varying environmental conditions. The present work employs a bottom-up, physics-based energy yield modelling approach, which accounts to the interacting optical, thermal and electrical mechanisms in a detailed manner. Additionally, measured data is used for the accurate calibration of the models. Such an approach permits to explore the influence of cell- and module technology details on energy yield under any specific environmental conditions. The present work employs such a method to evaluate the influence of Silicon solar cell technology on energy yield under desert and moderate climates, where the interplay of different irradiance and ambient temperature levels result in a challenging PV performance prediction problem. The purpose of this work is to identify the best-suited solar cell technologies and to understand the underlying mechanisms, which lead to superior PV performance under specific climate conditions. The study is performed by means of physics-based exploratory energy yield simulations with detailed resolution of the thermal effects. Our comparison of four different cell technologies in monofacial modules highlights that superior illumination-dependent performance can contribute to annual energy yield enhancement under both moderate and desert climates amounting to 1.75% and 0.4%, respectively; while a 0.04%/°C advantage in relative temperature coefficient increases annual energy yield (by 1.2%) only under a desert climate.