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123 lines
4.2 KiB
Python
123 lines
4.2 KiB
Python
"""Behaviour of the Optimiser under a goal-aligned objective (ADR-0062): a
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Scenario whose goal is Reducing CO2 emissions / Energy Savings optimises its
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own metric, not SAP. The caller supplies group signals already measured in the
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objective's currency; the optimiser must price everything *it* computes — the
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forced Measure Dependency signals — in the same currency, so a ventilation
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that costs SAP but is carbon-neutral cannot sink a carbon-improving wall.
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"""
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from __future__ import annotations
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from typing import Sequence
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from datatypes.epc.domain.epc_property_data import (
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BuildingPartIdentifier,
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EpcPropertyData,
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)
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from domain.modelling.measure_type import MeasureType
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from domain.modelling.optimisation.optimiser import (
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MeasureDependency,
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OptimisedPackage,
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ScoredOption,
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optimise_package,
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)
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from domain.modelling.recommendation import Cost, MeasureOption
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from domain.modelling.scoring.package_scorer import Score
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from domain.modelling.simulation import (
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BuildingPartOverlay,
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EpcSimulation,
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VentilationOverlay,
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)
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from tests.domain.sap10_calculator.worksheet._elmhurst_worksheet_000490 import (
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build_epc,
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)
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_WALL_OVERLAY = EpcSimulation(
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building_parts={
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BuildingPartIdentifier.MAIN: BuildingPartOverlay(wall_insulation_type=2)
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}
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)
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_VENT_OVERLAY = EpcSimulation(
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ventilation=VentilationOverlay(mechanical_ventilation_kind="EXTRACT_OR_PIV_OUTSIDE")
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)
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def _scored(
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measure_type: str, *, gain: float, cost: float, overlay: EpcSimulation
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) -> ScoredOption:
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return ScoredOption(
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option=MeasureOption(
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measure_type=MeasureType(measure_type),
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description=measure_type,
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overlay=overlay,
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cost=Cost(total=cost, contingency_rate=0.0),
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),
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sap_gain=gain,
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)
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class _CarbonScorer:
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"""A stub where the wall is a small carbon win (−20 kg/yr) and a large SAP
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win (+6), while its forced ventilation is carbon-neutral but SAP-ruinous
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(−30): SAP-priced dependency signals sink the wall; carbon-priced ones
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keep it."""
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def score(
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self, baseline: EpcPropertyData, simulations: Sequence[EpcSimulation]
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) -> Score:
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sap, co2 = 60.0, 500.0
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for sim in simulations:
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if sim.ventilation is not None:
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sap -= 30.0
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for part in sim.building_parts.values():
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if part.wall_insulation_type is not None:
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sap += 6.0
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co2 -= 20.0
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return Score(
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sap_continuous=sap, co2_kg_per_yr=co2, primary_energy_kwh_per_yr=0.0
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)
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def _carbon_reduction(score: Score) -> float:
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return -score.co2_kg_per_yr
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def test_dependency_signals_are_priced_in_the_objective_currency() -> None:
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# Arrange — the wall's signal (supplied by the caller, +20 kg CO2 saved)
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# and the ventilation it forces in (carbon-neutral). Under legacy SAP
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# pricing the ventilation's −30 SAP would outweigh the wall's +20 signal
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# and the package would collapse to nothing.
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groups: list[list[ScoredOption]] = [
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[_scored("cavity_wall_insulation", gain=20.0, cost=1000.0, overlay=_WALL_OVERLAY)],
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]
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dependency = MeasureDependency(
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triggers=frozenset({MeasureType.CAVITY_WALL_INSULATION}),
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required=ScoredOption(
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option=MeasureOption(
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measure_type=MeasureType.MECHANICAL_VENTILATION,
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description="mechanical_ventilation",
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overlay=_VENT_OVERLAY,
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cost=Cost(total=300.0, contingency_rate=0.0),
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),
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sap_gain=0.0,
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),
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)
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# Act — a Reducing-CO2 brief: maximise carbon reduction within budget.
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package: OptimisedPackage = optimise_package(
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groups=groups,
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scorer=_CarbonScorer(),
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baseline_epc=build_epc(),
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budget=5000.0,
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target_sap=None,
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dependencies=[dependency],
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objective=_carbon_reduction,
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)
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# Assert — the wall survives with its ventilation: the dependency is worth
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# 0 kg CO2, not −30 SAP, so the package is a net +20 kg saving.
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assert {s.option.measure_type for s in package.selected} == {
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"cavity_wall_insulation",
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"mechanical_ventilation",
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}
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assert abs(package.score.co2_kg_per_yr - 480.0) <= 1e-9
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