Populate the UK prepayment-meter input from LCFS

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Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
52/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
python
Ambito
data-engineering

Direzione di ricerca

Start with packages/microcosm-build/src/microcosm/build/uk_runtime/lcfs_consumption.py, especially the consumption-stage code linked in the issue, and trace how LCFS donor fields are cleaned, imputed, and exported. Find the UK stage tests and add focused coverage for the requested classification and propagation cases. Done means the input is exported, the weighted estimate is reported, and its comparison clearly states benchmark differences.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Summary

PolicyEngine/policyengine-uk#2098 adds the household input uses_energy_prepayment_meter to calculate the Great Britain Energy Price Guarantee prepayment discount from July 2023 through March 2024. Microcosm's current UK LCFS consumption stage does not read a gas or electricity payment-method field and does not include this boolean in UK_LCFS_CONSUMPTION_OUTPUT_COLUMNS. Population simulations therefore default the model input to false and calculate no prepayment discount.

The government reported that the July 2023 change covered around three million prepayment-meter households across Great Britain and reduced a typical annual bill by around £21. Prepayment meter customers to pay less for energy from today

Current implementation: uk_runtime/lcfs_consumption.py

Requested implementation

  • Identify the LCFS gas and electricity payment-method fields and document their code values.
  • Derive a household-level uses_energy_prepayment_meter boolean, including an explicit rule for mixed payment methods and missing responses.
  • Carry or impute the boolean from the LCFS donor into the UK household frame and include it in the exported PolicyEngine UK dataset.
  • Add focused UK stage tests for donor cleaning, output propagation, deterministic assignment, and export compatibility.
  • Report the weighted number and share of Great Britain households classified as using a prepayment meter.
  • Compare that result with an official benchmark, stating differences in reference period, geography, and whether the benchmark counts households, customers, accounts, or meters.

Related issue and repository boundary

PolicyEngine/policyengine-uk-data#539 tracks the same missing input in the UK input pipeline and will remain open. This issue tracks the implementation required in Microcosm's direct LCFS consumption stage and current UK population build. The two implementations should use the same source-field interpretation and classification rules.

Dependency

The model can calculate the discount for an individual household when a caller supplies uses_energy_prepayment_meter. A Microcosm population release must carry this input before the discount has a nonzero aggregate effect in population simulations.

Lingua principale
Python
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0
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