Imagine this scenario: You have a substantial dataset collected over years of PhD research. You publish a paper outlining the long-term phenomena observed in your data. As is customary in scientific research, you address questions and raise new ones. As you delve deeper into the subject matter, drawing from your existing knowledge and the latest research, you discover something unexpected. Your initial hypotheses or even the dataset itself may seem questionable. However, upon revisiting your notes, data, and theoretical framework, you embark on a cyclical process of exploration. You repeatedly examine your notes, theory, notes, data, and so on, refining your understanding and gradually unraveling the puzzle.

The case mentioned here served as the starting point for the paper recently published in Nature Communications Engineering, titled "Energy losses in photovoltaic generators due to wind patterns." In a previous publication, my colleagues and I identified a medium-term, year-by-year variation related to mismatch losses, evaluated monthly. At the time, we lacked a satisfactory explanation for this phenomenon. Suspecting a connection to wind patterns, I began analyzing local wind measurements and their corresponding temperature variations. To quantify the real impact of wind on energy losses in a large photovoltaic generator, considering the well-established influence of wind on standalone PV/PVT systems, I believed a numerical assessment was necessary. While observing this impact for the first time in a larger system, the key was to numerically determine how increased wind speed would benefit energy production, drawing on the extensive literature regarding the advantages of PV cooling. Surprisingly, my results demonstrated an increase in energy losses with rising wind speed, as assessed through the experimental analysis of mismatch losses between photovoltaic modules. Initially, this unexpected outcome might lead one to suspect data errors. Therefore, it was time to revisit the theoretical underpinnings of our analysis. Again. 

The temperature differences induced by the wind

First, we can envision the photovoltaic generator as a flat plate exposed to a fluid, in this case, wind. Imagine wind flowing parallel to the photovoltaic generator, transitioning from laminar to turbulent flow. At the initial stage of laminar flow, heat transfer is high, but it quickly decreases until the transition zone where turbulence begins to develop. As the boundary layer thickens due to turbulent development, heat transfer from the panels to the air decreases. Consequently, temperatures tend to be higher with more developed turbulence. This generates temperature differences within the photovoltaic generator, with greater differences at higher wind speeds. Conversely, lower or even zero wind speeds result in lower temperature differences.

Two observations are noteworthy:

1. Temperature differences increase proportionally to in-plane irradiance. Photovoltaic panels are more sensitive to wind incidence and, consequently, temperature differences at higher irradiance values.

2. The temperature distribution remains consistent even when the photovoltaic generator is not generating electricity, reinforcing the notion that the thermal behavior within photovoltaic generators is primarily governed by fluid mechanics properties rather than any effects of the Joule effect. Additionally, this suggests that wind-induced losses occur in all types of photovoltaic generators, regardless of their underlying technology.

While one might argue that this is an idealized scenario, as the photovoltaic generator is exposed to natural, inherently turbulent wind, the presented observations demonstrate that temperature distributions behave as expected in an ideal case, explained accurately by fluid mechanics properties. These considerations could potentially simplify large-scale analysis, such as for a photovoltaic plant exposed to regional wind patterns. Moreover, this same behavior occurs even when wind reaches the photovoltaic generator diagonally, both from the front and rear sides.

What about the benefits of PV cooling?

Having established the relationship between temperatures and wind incidence, the next step is to examine how mismatch losses behave in similar conditions. Contrary to expectations of increased energy with higher wind speeds, mismatch losses actually increase with rising wind speeds. Conversely, lower mismatch loss values are observed when wind speeds are low or nonexistent.

While many scientific publications have highlighted the potential benefits of wind for cooling photovoltaic panels, this is only partially correct. The results indicate that temperatures can vary significantly, even between adjacent modules, especially if they are positioned at the beginning of the airflow due to the rapid decrease in heat transfer before the regime transition. Therefore, the question arises: How many modules must be present before we can consider this a loss? Perhaps just a few, maybe even two.

A similar mismatch loss pattern occurs annually. The highest values are observed during the warmest months in this region, when a thermal low over the Iberian Peninsula induces southerly and southwesterly winds. For this specific south-oriented generator, winds from these directions are responsible for the higher mismatch loss values.

As we can see, for larger photovoltaic generators, the story is a bit different.

Does this mean that the energy yield estimations were wrong?

No, absolutely not. The key point is that local wind patterns, often overlooked, must be considered for accurate energy estimation throughout the lifespan of a photovoltaic power plant, even though the observed losses may be relatively small. As photovoltaic module manufacturing technology advances, differences between modules tend to decrease further. Therefore, every detail matters in reducing uncertainties in energy yield estimations.

While many studies have explored the potential benefits of harnessing wind, even in large installations, these results suggest another avenue to consider. The impact of wind on energy production from large photovoltaic power plants remains uncertain. It's possible that wind, by inducing thermal variations within the photovoltaic generator, could accelerate module aging. Additionally, wind patterns in a specific location may need to be factored in throughout the plant's lifespan, as they can change over decades due to global climate change.

There are still unanswered questions, and some may take time to resolve. The answer is blowin’ the wind.