Help CenterWe calculate an hourly price curve by adjusting forward block prices to capture hourly variance.
To convert the monthly block prices to hourly prices, we use hourly scalars. We derive the scalars by looking at the variability in hourly prices from the past three years across Houston, North, West, and South hubs. Specifically, we divide each hourly price by its respective monthly block price (7x8, 5x16, or 2x16) to match the format of the forward block prices.
Below is a table showing how we calculate these historical scalars in excel.
| Settlement Point | Date | Hour Ending | Price | Block | Avg Block Price | Scalar |
| HB_HOUSTON | 3/1/24 | 0:00 | $ 13.00 | 7x8 | $ 13.76 | 0.94 |
| HB_HOUSTON | 3/1/24 | 1:00 | $ 14.31 | 7x8 | $ 13.76 | 1.04 |
| HB_HOUSTON | 3/1/24 | 2:00 | $ 13.06 | 7x8 | $ 13.76 | 0.95 |
| HB_HOUSTON | 3/1/24 | 3:00 | $ 11.96 | 7x8 | $ 13.76 | 0.87 |
| HB_HOUSTON | 3/1/24 | 4:00 | $ 11.59 | 7x8 | $ 13.76 | 0.84 |
| HB_HOUSTON | 3/1/24 | 5:00 | $ 13.37 | 7x8 | $ 13.76 | 0.97 |
| HB_HOUSTON | 3/1/24 | 6:00 | $ 18.56 | 7x8 | $ 13.76 | 1.35 |
| HB_HOUSTON | 3/1/24 | 7:00 | $ 38.66 | 7x16 | $ 24.50 | 1.58 |
| HB_HOUSTON | 3/1/24 | 8:00 | $ 27.65 | 7x16 | $ 24.50 | 1.13 |
| HB_HOUSTON | 3/1/24 | 9:00 | $ 17.26 | 7x16 | $ 24.50 | 0.70 |
| HB_HOUSTON | 3/1/24 | 10:00 | $ 13.71 | 7x16 | $ 24.50 | 0.56 |
| HB_HOUSTON | 3/1/24 | 11:00 | $ 12.41 | 7x16 | $ 24.50 | 0.51 |
| HB_HOUSTON | 3/1/24 | 12:00 | $ 11.58 | 7x16 | $ 24.50 | 0.47 |
| HB_HOUSTON | 3/1/24 | 13:00 | $ 11.24 | 7x16 | $ 24.50 | 0.46 |
| HB_HOUSTON | 3/1/24 | 14:00 | $ 10.69 | 7x16 | $ 24.50 | 0.44 |
| HB_HOUSTON | 3/1/24 | 15:00 | $ 9.63 | 7x16 | $ 24.50 | 0.39 |
| HB_HOUSTON | 3/1/24 | 16:00 | $ 9.17 | 7x16 | $ 24.50 | 0.37 |
| HB_HOUSTON | 3/1/24 | 17:00 | $ 10.36 | 7x16 | $ 24.50 | 0.42 |
| HB_HOUSTON | 3/1/24 | 18:00 | $ 26.11 | 7x16 | $ 24.50 | 1.07 |
| HB_HOUSTON | 3/1/24 | 19:00 | $ 48.60 | 7x16 | $ 24.50 | 1.98 |
| HB_HOUSTON | 3/1/24 | 20:00 | $ 19.93 | 7x16 | $ 24.50 | 0.81 |
| HB_HOUSTON | 3/1/24 | 21:00 | $ 16.56 | 7x16 | $ 24.50 | 0.68 |
| HB_HOUSTON | 3/1/24 | 22:00 | $ 13.93 | 7x16 | $ 24.50 | 0.57 |
| HB_HOUSTON | 3/1/24 | 23:00 | $ 13.44 | 7x8 | $ 13.76 | 0.98 |
| HB_HOUSTON | 3/2/24 | 0:00 | $ 11.10 | 7x8 | $ 13.76 | 0.81 |
| HB_HOUSTON | 3/2/24 | 1:00 | $ 11.36 | 7x8 | $ 13.76 | 0.83 |
| HB_HOUSTON | 3/2/24 | 2:00 | $ 10.22 | 7x8 | $ 13.76 | 0.74 |
| HB_HOUSTON | 3/2/24 | 3:00 | $ 9.91 | 7x8 | $ 13.76 | 0.72 |
| HB_HOUSTON | 3/2/24 | 4:00 | $ 10.04 | 7x8 | $ 13.76 | 0.73 |
| HB_HOUSTON | 3/2/24 | 5:00 | $ 12.05 | 7x8 | $ 13.76 | 0.88 |
We calculate scalars for each hour of each month. For hour 5 (5:00am) in October, for example, we calculate 31 distinct scalars representing each day in October. Since we look at three years of data, our set of scalars for this hour is three times as large, 93 in total. To estimate the future value of hour 5 in October, we start by selecting a scalar from these 93 possibilities. We follow this process for every hour of every day for the next 20 years.
Once we multiply the randomly selected scalar by the relevant block price, we get a new price forecast with hourly granularity.
This methodology for producing hourly scalars relies on historical prices that reflect the market conditions of the past. Next, we adjust our scalars to reflect how those market conditions are expected to change in the future.