Use Capacity Factor instead of (or in addition to) Windspeed to assess sites

[somerandomsequence]

From discussion with Lindsay Sheridan at our first demo. Note that capacity factor is defined as the amount a turbine would be utilized at a given location due to the wind resource available as compared to the ideal. So, a 15 kWh turbine that reaches rated power at a 5 mps windspeed would have a CF of 1.0 at a site with winds >= 5 mps all the time. Here is the full message from Lindsay:

Hi WindWatts friends!

After the great demo earlier this week, I was thinking about how we classify the low, moderate, and high wind resource categories. Due to some pressure to get the tool out the door, I don’t think we were able to put a lot of research into those ranges. If I recall correctly, we set low as anything under 3 or 3.5 m/s, based on that being cut-in speed. I can’t at all remember what we chose for the threshold between moderate and high – maybe 5 m/s?

Anyways, I think we can make some improvements here if you’re open to it. I was checking around at a location in Colorado that gave a “moderate” resource assessment in WindWatts based on the annual average wind speed, but if you calculated the capacity factor based on the resultant energy production, it was only 9%. That’s pretty low. And it’s not even considering losses which would make it lower.

What if we do low, moderate, and high according to capacity factor instead? We’ve got all the ingredients: energy production/(8760 hours x turbine capacity). What if we did low as anything below 15%, moderate as 15-25%, and high as 25%+? I think that would make more sense and align with what our users would expect to see.

Happy to chat further if you think it’s a worthwhile idea!

Lindsay

[somerandomsequence]

Related to #6

[RLiNREL]

Copied from #160

Summarizing the conversations on CF based resource classification instead of hard coded 3 and 5 m/s for low, medium, high resources.

The simple 3 m/s and 5m/s wind speed threshold for low/medium/high resources may be inadequate because the same wind speed has different implications depending on turbine size and hub height. Capacity factor based approaches can help solve this problem:

CF_estimated = AEP_estimated / AEP_max, where AEP_max = Rated Power × 8760 hours

To determine the thresholds:

1. Based on DW and Land-Based Wind Market Reports and customer satisfaction:
   Low (Red): <15% CF
   Medium (Yellow): 15-25% CF
   High (Green): >25% CF
2. Incorporated futures study for economic feasibility and system cost, e.g., higher $/kw for small turbines

[RLiNREL]

Copied from #6 for linear gradient idea

From discussion with Lindsay Sheridan after our last demo. We were thinking we could have a linear gradient/gauge with a mark, something like the below that is placed below the windspeed or capacity factor. If we made the colors in the gradient proportional to the actual distribution and put the cut-points for low/mod/high on the gradient, it would also visually communicate something about the CF distribution and how we are making the cuts without needing to expressly define high/med/low in a tooltip etc.