bolster.data_sources.electricity_renewables

NI Electricity Consumption and Renewable Generation Statistics.

Published quarterly by the Department for the Economy (DfE) Northern Ireland in partnership with NISRA. Reports progress toward NI’s renewable electricity targets (80% of consumption from renewables by 2030 under the Climate Change Act (Northern Ireland) 2022).

Data Source:

Interactive report (data embedded as base64 CSV): https://datavis.nisra.gov.uk/Economy/electricity-consumption-and-renewable-generation-report.html

The report embeds ten figures as base64-encoded UTF-16 LE CSV data-URIs. This module extracts and parses the four headline time series:

renewable_pct: Rolling 12-month renewable generation as a proportion of gross final electricity consumption (%) and monthly %.
consumption: Total consumption, renewable and non-renewable generation, and net imports (rolling 12-month GWh).
generation_by_technology: Rolling 12-month generation (GWh) by technology — wind, hydro, bioenergy, landfill gas, solar PV.
generation_monthly: Monthly renewable and non-renewable generation (GWh) going back to February 2018.

Update Frequency:

Quarterly (March, June, September, December).

Coverage:

Rolling 12-month figures: January 2019 – present. Monthly generation figures: February 2018 – present.

Example

>>> from bolster.data_sources import electricity_renewables
>>> data = electricity_renewables.get_latest_data()
>>> 'renewable_pct' in data
True
>>> 'renewable_pct_rolling_12m' in data['renewable_pct'].columns
True
>>> (data['renewable_pct']['renewable_pct_rolling_12m'] > 0).all()
True

Attributes

logger

Exceptions

`ElectricityDataNotFoundError`	Electricity statistics page or data could not be retrieved.
`ElectricityValidationError`	Electricity DataFrame failed validation checks.

Functions

`get_latest_data`([force_refresh])	Download and parse the latest NI electricity and renewables statistics.
`validate_data`(df[, key])	Validate an electricity statistics DataFrame.

Module Contents

bolster.data_sources.electricity_renewables.logger[source]

exception bolster.data_sources.electricity_renewables.ElectricityDataNotFoundError[source]

Bases: Exception

Electricity statistics page or data could not be retrieved.

Initialize self. See help(type(self)) for accurate signature.

exception bolster.data_sources.electricity_renewables.ElectricityValidationError[source]

Bases: Exception

Electricity DataFrame failed validation checks.

Initialize self. See help(type(self)) for accurate signature.

bolster.data_sources.electricity_renewables.get_latest_data(force_refresh=False)[source]

Download and parse the latest NI electricity and renewables statistics.

Returns four DataFrames covering the headline series from the DfE/NISRA quarterly electricity report.

Parameters:

force_refresh (bool) – If True, bypass the local cache and re-download.

Returns:

"renewable_pct" — rolling 12-month and monthly renewable generation as % of gross final consumption.
"consumption" — rolling 12-month total consumption, renewable generation, non-renewable generation, and net imports (GWh).
"generation_by_technology" — rolling 12-month renewable generation (GWh) by technology: wind, hydro, bioenergy, landfill gas, solar PV.
"generation_monthly" — monthly renewable and non-renewable generation (GWh) going back to February 2018.

Return type:

Dictionary with keys

Raises:

ElectricityDataNotFoundError – If the datavis page cannot be fetched or no figure data is found in the HTML.
ElectricityValidationError – If the parsed data fails validation.

Example

>>> data = get_latest_data()
>>> sorted(data.keys())
['consumption', 'generation_by_technology', 'generation_monthly', 'renewable_pct']
>>> 'total_consumption_gwh' in data['consumption'].columns
True

bolster.data_sources.electricity_renewables.validate_data(df, key='renewable_pct')[source]

Validate an electricity statistics DataFrame.

Parameters:

df (pandas.DataFrame) – DataFrame from get_latest_data().
key (str) – Which sub-dataset to validate (controls required-column check). One of "renewable_pct", "consumption", "generation_by_technology", "generation_monthly".

Returns:

True if all checks pass.

Raises:

ElectricityValidationError – If the DataFrame is empty, missing required columns, has implausible values, or is too short.

Return type:

bool

Example

>>> data = get_latest_data()
>>> validate_data(data['renewable_pct'], 'renewable_pct')
True