Solar Power Generation Modelling - the US NY ISO case
The renewable energy transition is occurring rapidly, and at Speedwell Climate, we have gained expertise in modeling renewable electricity production based on asset data. Currently, we are focused on analyzing the US NY Independent System Operator. We recently released our Wind Power Generation tradable index for this region and are now in the final stages of publishing our Solar Power Generation index. This particular case presents an interesting modeling scenario that I would like to share with you.
Our indices rely on comprehensive modeling of installed capacity. Our process begins by gathering all available information regarding the installed capacity, including the following details:
I must emphasize that obtaining this information is no easy task. We have dedicated employees who act as detectives, meticulously scouring governmental websites, farm websites, public sources, and even paid sources for information. One common challenge we encounter is determining when additional installed capacity is connected to the grid. While we sometimes have access to this information, it is often unavailable. There are various reasons for this, but the primary reason is that the process of connecting a new solar farm to the grid is gradual.
To clarify, when a new solar farm is constructed, the process typically spans several months to even a year or two. The installed capacity gradually connects to the grid as the farm is being built. The same gradual connection process applies to rooftop installations, which occur throughout the year.
This gradual nature poses significant challenges when modeling power generation from renewables, as we strive to compare our index with published data whenever possible (and when we have confidence in the official data). In the case of NY ISO, we had access to the initial and final installed capacity data for all sub-regions throughout the year. We then utilized our model to determine when newly installed capacity was connected to the grid.
To illustrate the challenges we face, let's examine the final output. The chart below depicts the daily solar production, comparing the actual published data with the Speedwell Solar Index for NYISO, adjusted for installed capacity changes over the course of the year:
Using a Scatterplot chart, let us compare the hourly data:
To me, despite some Actual data errors (the "zeros" on the Y-axis), there is no doubt the index works well, but this is hiding the change in capacity during the year.
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Let us take a step back and let us model the generated solar power as at the beginning of 2022:
We can see a marked difference between the two time-series around September 2022. This same difference can be seen using a scatterplot for the hourly data:
By closely analyzing this chart, we can gain insights into the discrepancies between the actual data and our model, highlighting the complexities and nuances associated with accurately predicting solar power generation. ?Using either chart, we can see there is at least one marked difference between the two time-series during the year. We then feedback this information to our team who now have dates they can work with to precisely find out when installed capacity was newly added.
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Overall, the renewable energy landscape is evolving rapidly, and our commitment at Speedwell Climate is to refine our modeling techniques continuously. Despite the challenges in gathering precise information on installed capacity and tracking gradual connections to the grid, we aim to provide reliable and insightful indices that contribute to a deeper understanding of renewable energy generation.
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For now, the Speedwell Climate US NYISO Solar Power Generation Index is ready for release. Enjoy!
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Speedwell Climate is the leading provider of data for the climate risk transfer business. We also provide the Speedwell Environmental System for pricing and managing climate derivative contracts. Speedwell Climate also provides independent valuations of weather derivatives, quanto pricing, and portfolios of climate risks.
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