Model 2.9
- Citation Author(s):
-
Konstantinos Theodorakos
- Submitted by:
- Konstantinos Theodorakos
- Last updated:
Abstract
Model 2.9
Clustered-meter average monthly ratios
Monthly (kWh) consumption clustering:
1. Twelve clustering models (one per month of signup): Spectral Clustering
2. Clustering using (daily kWh) consumption extracted features. Cluster count set to 4 (empirically better than the 5 or 6 suggested by the elbow distortion method).
Forecasting for a meter: Using the mean monthly consumption + in-cluster month-to-month ratios.
Clustering
Features (170) from weekend/weekday and full series:
- Statistical: median, variance, quantiles, ...
- Time-series: autocorrelations, trends, seasonalities, ...
Post-processing of clustering data: Standardization.
Time-series preprocessing:
- Hourly resampling -> 8h moving average -> daily resampling.
