Case Study

This example wind farm in West Texas highlights how the hourly variation in locational marginal emissions (LME) results in high and low-impact RECs. Figure 1 below shows a time series graph of the wind farm's energy generation, carbon impact, and the distribution of LMEs. The blue line depicts energy generation, and the red bars illustrate the carbon impact calculated from LME data. This wind farm operates in a region with high penetration of CFE, and the grid operator often uses curtailment to balance the grid. This curtailment is seen in the left peak of the LME frequency distribution graph. This peak represents the hours when the carbon impact of generation is meager, and RECs issued for generation during these times should be valued accordingly.

Since the LME varies hourly, energy generated during low grid marginal emissions periods results in lower carbon impact. January 6th is a relatively high generation day, but because LME was low, carbon impact was low. Conversely, January 11th is a day of similar generation but a much higher carbon impact.

Fig. 1: Generation & Carbon Impact Time Series

The hourly power meter and LME data are used to issue the PECs shown below in Fig. 2. Each box represents an hourly PEC, which is colored by carbon impact, with red indicating low impact and green indicating high impact.

Fig. 2: PEC Issuance

This batch of PECs can now be sorted and organized into bins of carbon impact that highlight how different classes of PECs can be created to add value to transactions. Every CFE project will have a range of carbon impact, and now the information is available for informed procurement.

Fig. 3: Distribution of Carbon Impact across Issued PECs