Model/domain/modelling/contingencies.py
Khalim Conn-Kowlessar b55ab3727f feat(modelling): wire the HHR storage bundle into the candidate pool
recommend_heating joins the free candidate pool in _candidate_recommendations;
the HHR storage bundle reaches the optimised package for an electric/off-gas
dwelling. Catalogue + contingency (legacy 0.10) gain
high_heat_retention_storage_heaters; report.py _triggers_for explains the
heating trigger (electric/off-gas main); the harness _GENERATOR_MEASURE_TYPES
forcing test covers it. ASHP + boiler bundles still to come. ADR-0024.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-05 19:22:50 +00:00

33 lines
1.1 KiB
Python

"""Per-Measure-Type contingency rates.
The one cost component carried separately from a Product's fully-loaded total
(CONTEXT.md). Mirrors the legacy `recommendations/Costs.py::Costs.CONTINGENCIES`;
extended as each measure type lands.
"""
_CONTINGENCY_RATES: dict[str, float] = {
"cavity_wall_insulation": 0.10,
"loft_insulation": 0.10,
"sloping_ceiling_insulation": 0.10,
"flat_roof_insulation": 0.10,
"suspended_floor_insulation": 0.20,
"solid_floor_insulation": 0.26,
"mechanical_ventilation": 0.26,
"external_wall_insulation": 0.26,
"internal_wall_insulation": 0.26,
"double_glazing": 0.15,
"secondary_glazing": 0.15,
"low_energy_lighting": 0.26,
"high_heat_retention_storage_heaters": 0.10,
}
def contingency_rate(measure_type: str) -> float:
"""Return the contingency rate for a Measure Type, raising if unknown
(strict — do not silently default, per the repo's strict-raise convention)."""
try:
return _CONTINGENCY_RATES[measure_type]
except KeyError as exc:
raise ValueError(
f"no contingency rate configured for measure type {measure_type!r}"
) from exc