Short-Term Decomposition

Goal

Decompose high-resolution power data over a short period to reveal daily consumption patterns and short-term trends.

Data Basis

Power measurements at 15-minute intervals (decomposition_short.csv) bundled with the pyedautils package. 480 data points covering 5 days.

Data Preparation

import pandas as pd
from importlib import resources

data_path = resources.files("pyedautils") / "data" / "decomposition_short.csv"
df = pd.read_csv(data_path, sep=";")
df.head()

	timestamp	value
0	2015-01-26 00:00:00	86.0
1	2015-01-26 00:15:00	100.0
2	2015-01-26 00:30:00	60.0
3	2015-01-26 00:45:00	82.0
4	2015-01-26 01:00:00	90.0

Visualization

from pyedautils.plots import plot_decomposition

fig = plot_decomposition(
    data=df,
    period=96,
    s_window=193,
    title="Time Series Decomposition over 5 Days",
    ylab="Power [kW]",
)
fig.show()