| Model | Parameter |
<1d n=672 |
1d n=672 |
2d n=672 |
3d n=631 |
4d n=615 |
5d n=615 |
6d n=615 |
7d n=615 |
8d n=615 |
9d n=615 |
10d n=615 |
11d n=615 |
12d n=580 |
13d n=236 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AgilePredict | MAE | 0.08 | 2.16 | 4.27 | 4.67 | 4.48 | 4.44 | 4.50 | 4.68 | 4.63 | 4.80 | 4.65 | 4.33 | 4.22 | 5.14 |
| AgilePredict | RMSE | 0.45 | 3.64 | 7.04 | 8.29 | 8.37 | 8.22 | 8.44 | 8.58 | 8.61 | 8.63 | 8.77 | 8.12 | 6.55 | 7.43 |
| AgilePredict | Bias | +0.08 | +1.19 | +0.16 | -0.26 | -0.32 | -0.08 | -0.29 | -0.85 | -0.57 | -0.44 | -0.54 | -0.32 | -0.39 | -1.03 |
| Model | Offset | n | MAE | RMSE | Bias |
|---|---|---|---|---|---|
| AgilePredict | <1d | 672 | 0.08 | 0.45 | +0.08 |
| AgilePredict | 1d | 672 | 2.16 | 3.64 | +1.19 |
| AgilePredict | 2d | 672 | 4.27 | 7.04 | +0.16 |
| AgilePredict | 3d | 631 | 4.67 | 8.29 | -0.26 |
| AgilePredict | 4d | 615 | 4.48 | 8.37 | -0.32 |
| AgilePredict | 5d | 615 | 4.44 | 8.22 | -0.08 |
| AgilePredict | 6d | 615 | 4.50 | 8.44 | -0.29 |
| AgilePredict | 7d | 615 | 4.68 | 8.58 | -0.85 |
| AgilePredict | 8d | 615 | 4.63 | 8.61 | -0.57 |
| AgilePredict | 9d | 615 | 4.80 | 8.63 | -0.44 |
| AgilePredict | 10d | 615 | 4.65 | 8.77 | -0.54 |
| AgilePredict | 11d | 615 | 4.33 | 8.12 | -0.32 |
| AgilePredict | 12d | 580 | 4.22 | 6.55 | -0.39 |
| AgilePredict | 13d | 236 | 5.14 | 7.43 | -1.03 |
This chart compares the actual agile price with predictions made for the selected lead time.
The prediction offset is measured from when the forecast was created to the price slot being predicted.
MAE is the average absolute error, in p/kWh.
RMSE is similar but gives more weight to larger errors.
Bias is the average signed error, so positive means predictions were too high and negative means they were too low.