Michele Oliosi

@Matcor Duarte this is a different issue. The original post had two different weather data sources. In your case, changing the configuration probably also changed the tracking or orientation in some way? This would explain some differences in the GlobInc variable. Take a look and compare the “general parameters” frame in the report.

near shadings : irradiance loss electrical shadings : electrical mismatch loss caused by partial shadings

The minimum height above ground is not very relevant to the near shadings. If your trackers go to 60° rotation angles: - it means they will follow the sun much lower than the 13° ones, inducing more mutual shadings if backtracking is not active - the diffuse component is also subject to more mutual shadings

You can find out the number of modules here at the bottom of the 3D scene window: Let us know if this helps, I am not sure if I understood fully your issue, sorry.

You should choose trackers to begin with, phi has no meaning in the context of fixed tilt tables.

Hi Matt, I see. In fact, the importance of shadings depends on your choice of tracking algorithm. If you use traditional true tracking, then indeed shades may be important. However, many tracking systems use backtracking, which, for low sun angles, sets the trackers at more horizontal angles, to avoid shading the direct irradiance component. When using the batch to change the pitch and number of trackers on your "array of trackers" (that is defined as an array in the 3D scene), make sure that you also change the number of modules, strings, and inverters accordingly (and if applicable).

Hi, indeed, this is a difficult task, and I am not sure how much can be done with the tools in PVsyst's 3D scene. I assume that tracker shading issues are due to the topography. The issue is mostly that the changes you want to make are at risk of being under-determined. You mention varying the module quantity and pitch, but then how do you decide the table arrangement ? Surely it will follow some rules. I can imagine that the rule would be to fill a predetermined zone as much as possible. To do this for a single simulation, I would generally employ the zone tool in PVsyst. However, there is no interaction between zones and the batch mode at the moment, so it is not useful to run a batch. In other words, this is no good in your case. The tracker shading issues is a small effect, and it will have very small differences from variant to variant. I think these differences will be well within the uncertainty of the 3D modeling to begin with. So I would suggest the following simplification: run one variant with topography and a detailed layout of trackers on it. This will give you a reference in terms of shading losses and especially electrical shading losses (which are not present on flat ground when backtracking) run your batch on a simplified array of trackers on flat ground. If you use a single Array of trackers, you can then more easily use the batch to change geometric variables or the number of modules and so on. Add the extra losses from the topography variant to the simplified variants as another loss, e.g., string mismatch. Of course, this is a crude approximation, but probably within the uncertainty of the system modeling. TLDR: this is a collection of thoughts on how to approach the problem, not sure how much it will help.

Let us know if I didn't understand the ramp-up part correctly. I am not sure if you are writing about a simple grid curtailment or something more complex.

If I understand correctly, when this event happens, there is a more restrictive grid-injection limitation or grid curtailment. There is no functionality to cover that in a single simulation, at the moment. However, you could run two simulations, one with the normal, and the other with the more restrictive grid curtailment limit. If you export the hourly CSV files (https://www.pvsyst.com/help/output_file.htm), you can then use a data analysis or spreadsheet tool to combine the data when you wish during the year.

PVsyst uses the average plane orientation for transposition calculations in an “averaged orientation” such as with trackers on a complex topography.

You are right, trackers are difficult to change into fixed tilt. Have you tried the other way around ? If I recall correctly, there is a transform option to change fixed tilt into trackers. In this way, you can only build the scene with fixed tilt and then transform it. Regarding the tilt angles, you are right, it can only go from 0° to 90° in principle. I would advise creating your scene with fixed tilt, and then rotate all tables by 180°. This should ensure that you cover the originally negative tilts. The operation of rotating all tables by 180° may be a bit technical depending on the case. I would suggest you try, and then refer to us which specific issues you encounter.

There is also this FAQ post:

Hi ! Sorry for the delay as this is a difficult question. As you point out, there is a complex hierarchy of uncertainties, some of which are well-defined, others less so. Just zooming out at first, we tend to classify the relevant uncertainties according to the use that you intend to do. As one goes down in the hierarchy, the order of magnitude of the uncertainties decreases, in general. It is an okay approximation to assume that the uncertainties are compounded with an RMS sum. The first level would be in the case of yield estimates or PXX evaluations. In this case, the dominant factor is: The year-to-year weather variability (O(5%)) The second level is in the case of comparisons with actual data, when you use measurements, or historical data as input. Here the order of magnitude can vary widely, both for the measurement uncertainty, or the parametrization (e.g., given the experience of the modeler). However, certain studies, e.g., the PVPMC blind modeling, show that this uncertainty can be higher than expected ! All in all, I would summarize these uncertainties as (O(1%)). Measurement uncertainty Parametrization uncertainty The third level is the case of tracking the differences between two system choices. For example, deciding between two cable sections. Intrinsic uncertainty of the models. This is the main factor, but each model building block has a different uncertainty. We do not have an exhaustive answer for all models. However, we estimate the base models to have a very low (negligible) uncertainty (O(0.1%)) on the overall results: One-diode model Transposition model DC to AC conversion Ohmic resistance models Some choices of model are more critical, and can yield larger uncertainties. For example, the electrical shadings partition model, in the context of complex shadings, can have a 0.5% uncertainty because many approximations are being made. However, in a context of regular rows it has very low uncertainty. Another example is the central tracker approximation for diffuse shadings, or the sub-hourly clipping effect, which not only yields an uncertainty but also tends to bias the results. Overall, we still need to publish a more exhaustive list (honestly, it is a bit of a daunting task). Conclusion To finish the discussion with a comment more on point on your question, I think that for the purpose of the PXX evaluation, you can entirely neglect the modeling uncertainty. Since the intrinsic model uncertainty is two hierarchies lower than the weather variability, it is probably masked by the uncertainties above. Some exceptions are some critical choices, such as: the partitions electrical shading model in a context of complex shadings, diffuse shading representative tracker approximation in a context with tracker patches, the sub-hourly clipping effect, the bifacial model, any other situation that requires some important approximation that is not adapted to the case studied.

Just a wild guess here, but can your 3D scene support all the changes in plane azimuth and plane tilt ? Indeed, if you change these in a 3D scene, possibly there will be collisions with other shading objects or among PV tables.

Hi, I think that you are not focusing the correct reason for the differences in your loss diagram. Indeed, the effective additional “Global irradiance on rear side” is the same in both cases, i.e., you can expect that the area contributions to the bifacial model are marginal. More important than that is the module area at the stage “Effective irradiation on collectors”. This is not an energy value, so I think the highlighting method in PVsyst failed to see the difference in area. But this is more significant. If there is a difference in area here, it means that the modules have different dimensions in some way, maybe very small. Please carefully compare all parameters of the modules. Also, please make sure that the dimensions of the 3D scene tables have not changed because of that.