Daily Duration Curve

Contents

Daily Duration Curve#

Goal

Display a duration curve (sum frequency) of daily electricity consumption. The curve ranks daily totals from highest to lowest, revealing how many days exceed a given consumption level.

Data Basis

The dataset flatElectricity.csv contains cumulative electricity meter readings at 15-minute intervals (columns: time, FlatA_Ele, FlatB_Ele, FlatC_Ele, FlatD_Ele; separator ;). We use FlatA_Ele, compute consumption via diff(), and sum it per day, keeping only days without missing readings.

Data Preparation#

import pandas as pd

url = "https://raw.githubusercontent.com/retomarek/edap/main/edap/sampleData/flatElectricity.csv"
raw = pd.read_csv(url, sep=";")

# Parse timestamp and set as index
raw["time"] = pd.to_datetime(raw["time"])
raw = raw.set_index("time")

# Consumption per 15 minutes from the cumulative meter readings (kWh)
consumption = raw["FlatA_Ele"].diff()

# Daily sums of complete days only (all 96 quarter-hours have a reading):
# without min_count, days with missing data would show up as low or zero
# consumption
daily = consumption.resample("D").sum(min_count=96).dropna()

# Build clean 2-column DataFrame [timestamp, value]
df = daily.reset_index()
df.columns = ["timestamp", "value"]
df.head()

	timestamp	value
0	2018-12-01	14.324
1	2018-12-02	14.141
2	2018-12-03	12.444
3	2018-12-04	7.954
4	2018-12-05	5.732

Visualization#

from pyedautils.plots import plot_sum_frequency

fig = plot_sum_frequency(df, resolution="daily", reverse=True,
                         title="Electricity — Daily Duration Curve",
                         ylab="Electricity [kWh/d]")
fig.show()