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Slice 102f-prep.5: Wire N3.5 extended-heating MIT cascade (HP-gated)
SAP 10.2 Appendix N3.5 (PDF p.106-107) replaces Table 9c steps 3-4
for heat-pump packages with PCDB data — each month blends the
heating temperature Th, the unimodal (16-hour day, one 8-hour off
period per Table N7 footnote b) zone temperature, and the bimodal
(9-hour day, two off periods per Table N7) zone temperature via
Equation N5:
T = [N24,9 × Th + N16,9 × T_uni + (Nm − N16,9 − N24,9) × T_bi] / Nm
`mean_internal_temperature_monthly` gains an optional
`extended_heating_days_per_month` kwarg (12-tuple of (N24,9_m,
N16,9_m)). When provided, the orchestrator computes T_unimodal per
zone from a single 8-hour off-period reduction and blends; when
None (default — every non-HP cert) it returns T_bimodal directly,
so closed certs (001479, 0330, 9501) are bit-identical.
`cert_to_inputs` derives the per-month tuple for HP certs with PCDB
records carrying `heating_duration_code = "V"` (Variable) — the
only code lodged on modern records per SAP 10.2 PDF p.105 footnote
48. Cohort path: PSR (= max_output_kw × 1000 / (HLC × 24.2 K)) →
Table N5 PSR interpolation → cold-first day allocation. Fixed
durations "24" / "16" / "9" from legacy Table N4 are deferred —
not exercised by the cohort.
Cert 0380 SAP residual closes from +0.5999 → +0.1550 vs worksheet
88.5104. The remaining ~0.16 SAP delta is split between two
orthogonal §5 / §7 residuals (cold-month +0.008°C MIT drift from
spurious HP pump gains; sub-1e-3 efficiency bias) that the next
slices target. Pin tolerance is 1e-2 per month on worksheet (92)
to capture this slice's contract alone, with `feedback_zero_error_
strict` widening documented inline.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Khalim Conn-Kowlessar
parent
c341eba9a2
commit
2be7905637
3 changed files with 151 additions and 4 deletions
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@ -678,6 +678,45 @@ def test_api_0380_heat_pump_no_pumps_fans_kwh_per_table_4f() -> None:
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assert result.pumps_fans_kwh_per_yr == 0.0
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def test_api_0380_mean_internal_temp_matches_worksheet_92_within_1e_2() -> None:
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# Arrange — SAP 10.2 Appendix N3.5 (PDF p.107) replaces Table 9c
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# steps 3-4 for heat-pump packages with PCDB data: each month
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# blends Th, T_unimodal, T_bimodal via Equation N5, where N24,9_m
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# and N16,9_m come from Table N5 (PSR-interpolated) and the day
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# allocation algorithm.
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#
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# Cert 0380 (Mitsubishi PUZ-WM50VHA, PCDB 104568, PSR ≈ 1.43)
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# lands on Table N5 row "1.2 or more" → annual totals (3, 38) →
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# Jan(3, 28) + Dec(0, 10) extended days. Pre-fix the cascade ran
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# pure-bimodal so Jan = 17.85 vs worksheet (92) Jan = 18.95
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# (Δ -1.10) and Dec = 17.85 vs worksheet 18.16 (Δ -0.31).
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#
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# Tolerance 1e-2 absorbs a separate cold-month residual of +0.008°C
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# caused by `internal_gains_from_cert` injecting the central-heating
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# pump's gain (~7 W heating-season) for HP certs even though SAP 10.2
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# Table 4f says HP packages contribute zero pump/fan gains (line 70
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# of cert 0380's worksheet is 0.0 for every month). That residual
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# is the §5-gating concern of the next slice; this slice's contract
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# is the §7 N3.5 extended-heating cascade alone.
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doc = json.loads(_API_0380_JSON.read_text())
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epc = EpcPropertyDataMapper.from_api_response(doc)
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# Act
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inputs = cert_to_inputs(epc, prices=SAP_10_2_SPEC_PRICES)
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# Assert — pin against worksheet line (92) "MIT" 12-tuple.
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worksheet_mit_92 = (
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18.9539, 18.0081, 18.3466, 18.8491, 19.3582, 19.8174,
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20.0288, 20.0064, 19.6975, 19.0702, 18.3966, 18.1573,
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)
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for m, (cascade, ws) in enumerate(zip(
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inputs.mean_internal_temp_monthly_c, worksheet_mit_92
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)):
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assert abs(cascade - ws) < 1e-2, (
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f"month {m + 1}: cascade={cascade:.4f} vs worksheet={ws:.4f}"
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)
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def test_api_9501_room_in_roof_surfaces_populated() -> None:
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# Arrange — cert 9501's API JSON lodges measured RR detail under
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# `sap_room_in_roof.room_in_roof_details`: two gable walls
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@ -126,6 +126,8 @@ from domain.sap10_calculator.worksheet.heat_transmission import (
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from domain.sap10_calculator.climate.appendix_u import external_temperature_c
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from domain.sap10_calculator.worksheet.mean_internal_temperature import (
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MeanInternalTemperatureResult,
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allocate_extended_heating_days_to_months,
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extended_heating_days_from_psr_variable,
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mean_internal_temperature_monthly,
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)
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from domain.sap10_calculator.worksheet.energy_requirements import (
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@ -2026,6 +2028,43 @@ def _heat_pump_apm_efficiencies(
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return (main_heating_efficiency, water_efficiency_pct)
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def _heat_pump_extended_heating_days_per_month(
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*,
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main: Optional[MainHeatingDetail],
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hp_record: Optional["HeatPumpRecord"],
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hlc_annual_avg_w_per_k: float,
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) -> Optional[tuple[tuple[int, int], ...]]:
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"""SAP 10.2 Appendix N3.5 (PDF p.106-107) — per-month (N24,9, N16,9)
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day allocations for a heat-pump package's extended heating schedule.
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Returns None when extended heating doesn't apply, so the upstream
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`mean_internal_temperature_monthly` orchestrator falls through to
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the standard SAP heating schedule (bimodal 9-hour day).
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Only the Variable heating-duration case is handled here — per
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footnote 48 (PDF p.105) "Daily heating durations of 24, 16 and 9
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hours are retained for legacy purposes" and modern PCDB Table 362
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records always lodge "V". The fixed "24" / "16" branches would
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need a different allocation path (Table N4: 365 days at one mode)
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that the cohort never exercises; deferred until a cert demands it.
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"""
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if main is None or main.main_heating_category != 4:
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return None
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if hp_record is None or hp_record.heating_duration_code != "V":
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return None
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if hp_record.max_output_kw is None or hp_record.max_output_kw <= 0:
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return None
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if hlc_annual_avg_w_per_k <= 0:
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return None
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psr = (hp_record.max_output_kw * 1000.0) / (
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hlc_annual_avg_w_per_k * _SAP_DESIGN_HEAT_LOSS_DELTA_T_K
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)
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n24, n16 = extended_heating_days_from_psr_variable(psr=psr)
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return allocate_extended_heating_days_to_months(
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n24_9_year=n24, n16_9_year=n16,
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)
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def _primary_loss_applies(
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main: Optional[MainHeatingDetail],
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cylinder_present: bool,
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@ -2552,6 +2591,11 @@ def cert_to_inputs(
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ht.total_w_per_k + 0.33 * dim.volume_m3 * ventilation.effective_monthly_ach[m]
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for m in range(12)
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)
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extended_heating_days = _heat_pump_extended_heating_days_per_month(
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main=main,
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hp_record=pcdb_hp_record,
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hlc_annual_avg_w_per_k=hlc_annual_avg_w_per_k,
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)
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mit_result = mean_internal_temperature_monthly(
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monthly_external_temp_c=tuple(
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external_temperature_c(climate, m)
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@ -2565,6 +2609,7 @@ def cert_to_inputs(
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responsiveness=responsiveness_value,
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living_area_fraction=living_area_fraction_value,
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control_temperature_adjustment_c=0.0,
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extended_heating_days_per_month=extended_heating_days,
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)
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# SAP10.2 §8 — compose (98c)m via the orchestrator. Reuses the per-month
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@ -21,7 +21,7 @@ Table 9b (page 184), Table 9c (page 185).
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Final
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from typing import Final, Optional
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from domain.sap10_calculator.worksheet.utilisation_factor import utilisation_factor
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@ -242,6 +242,10 @@ def off_period_temperature_reduction_c(
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_LIVING_AREA_OFF_HOURS: Final[tuple[float, float]] = (7.0, 8.0)
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_ELSEWHERE_OFF_HOURS_TYPE_12: Final[tuple[float, float]] = (7.0, 8.0)
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_ELSEWHERE_OFF_HOURS_TYPE_3: Final[tuple[float, float]] = (9.0, 8.0)
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# SAP 10.2 Appendix N3.5 Table N7 footnote (b): "heating 0700-2300" =
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# 16 hours on, one 8-hour off period for both zones regardless of
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# control type. Used by Equation N5's T_unimodal term.
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_UNIMODAL_OFF_HOURS: Final[float] = 8.0
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@dataclass(frozen=True)
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@ -317,6 +321,7 @@ def mean_internal_temperature_monthly(
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control_temperature_adjustment_c: float = 0.0,
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secondary_fraction: float = 0.0,
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secondary_responsiveness: float = 1.0,
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extended_heating_days_per_month: Optional[tuple[tuple[int, int], ...]] = None,
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) -> MeanInternalTemperatureResult:
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"""SAP 10.2 §7 orchestrator — chain Table 9c steps 1–9 for all 12 months.
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@ -340,6 +345,14 @@ def mean_internal_temperature_monthly(
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Defaults 0 (single-main); used to compute weighted R
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per Table 9b: R_eff = (1-frac)·R_primary + frac·R_secondary.
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Case 2 (different parts heated) deferred — no fixture.
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extended_heating_days_per_month SAP 10.2 Appendix N3.5 — 12-tuple of
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(N24,9_m, N16,9_m) for heat-pump packages with
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PCDB data. When provided, the orchestrator
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replaces Table 9c steps 3-4 with Equation N5
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(blending Th, T_unimodal, T_bimodal). When
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None (the default — every non-HP cert), the
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standard SAP heating schedule applies: T_zone
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= T_bimodal directly.
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"""
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effective_responsiveness = (
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(1.0 - secondary_fraction) * responsiveness
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@ -370,7 +383,7 @@ def mean_internal_temperature_monthly(
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)
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# Living area — steps 1-4
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eta_l, t_l = _zone_mean_temp_with_per_zone_eta(
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eta_l, t_l_bimodal = _zone_mean_temp_with_per_zone_eta(
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heating_temperature_c=_T_H1_C,
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off_hours_first=_LIVING_AREA_OFF_HOURS[0],
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off_hours_second=_LIVING_AREA_OFF_HOURS[1],
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@ -379,14 +392,13 @@ def mean_internal_temperature_monthly(
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time_constant_h=tau,
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)
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eta_living.append(eta_l)
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t_1.append(t_l)
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# Elsewhere — steps 5-6
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t_h2_m = elsewhere_heating_temperature_c(
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heat_loss_parameter=hlp, control_type=control_type,
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)
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t_h2.append(t_h2_m)
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eta_e, t_e = _zone_mean_temp_with_per_zone_eta(
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eta_e, t_e_bimodal = _zone_mean_temp_with_per_zone_eta(
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heating_temperature_c=t_h2_m,
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off_hours_first=elsewhere_off_hours[0],
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off_hours_second=elsewhere_off_hours[1],
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@ -395,6 +407,57 @@ def mean_internal_temperature_monthly(
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time_constant_h=tau,
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)
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eta_elsewhere.append(eta_e)
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# SAP 10.2 Appendix N3.5 Equation N5 — when the caller provides
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# per-month (N24,9, N16,9) day allocations, blend Th / T_unimodal
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# / T_bimodal for each zone. T_unimodal applies one 8-hour off
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# period per Table N7 footnote (b) at the same η as the bimodal
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# path (η depends on Th + HLC only, not the heating schedule).
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if extended_heating_days_per_month is not None:
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n24_m, n16_m = extended_heating_days_per_month[m]
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days_m = _DAYS_IN_MONTH[m]
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u_uni_living = off_period_temperature_reduction_c(
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off_period_hours=_UNIMODAL_OFF_HOURS,
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heating_temperature_c=_T_H1_C,
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external_temperature_c=ext,
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responsiveness=effective_responsiveness,
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total_gains_w=gains,
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heat_transfer_coefficient_w_per_k=h,
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utilisation_factor=eta_l,
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time_constant_h=tau,
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)
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t_l_unimodal = _T_H1_C - u_uni_living
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u_uni_elsewhere = off_period_temperature_reduction_c(
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off_period_hours=_UNIMODAL_OFF_HOURS,
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heating_temperature_c=t_h2_m,
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external_temperature_c=ext,
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responsiveness=effective_responsiveness,
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total_gains_w=gains,
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heat_transfer_coefficient_w_per_k=h,
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utilisation_factor=eta_e,
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time_constant_h=tau,
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)
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t_e_unimodal = t_h2_m - u_uni_elsewhere
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t_l = extended_zone_mean_temperature_c(
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heating_temperature_c=_T_H1_C,
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t_bimodal_c=t_l_bimodal,
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t_unimodal_c=t_l_unimodal,
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n24_9_m=n24_m,
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n16_9_m=n16_m,
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days_in_month=days_m,
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)
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t_e = extended_zone_mean_temperature_c(
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heating_temperature_c=t_h2_m,
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t_bimodal_c=t_e_bimodal,
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t_unimodal_c=t_e_unimodal,
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n24_9_m=n24_m,
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n16_9_m=n16_m,
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days_in_month=days_m,
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)
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else:
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t_l = t_l_bimodal
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t_e = t_e_bimodal
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t_1.append(t_l)
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t_2.append(t_e)
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# Blend (step 7) + Table 4e adj (step 8)
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