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Slice 3 of the Solar PV Recommendation Generator (ADR-0026). Per roof segment,
back-solve the effective overshading factor ZPV from Google's expected
generation against SAP's own unshaded annual output:
ZPV = (yearlyEnergyDcKwh × 0.955) / (0.8 × kWp × S)
reusing the calculator's Appendix U3.3 annual solar radiation S via a new
public seam `pv_annual_solar_radiation_kwh_per_m2`. Dividing Google's
generation by SAP's S cancels orientation/tilt and isolates shading; the
result snaps to the RdSAP bucket {1:1.0, 2:0.8, 3:0.5, 4:0.35} via the
ADR-0026 midpoint cutpoints (≥0.90→1, 0.65–0.90→2, 0.425–0.65→3, <0.425→4;
ZPV>1→1). The real London example's planes all back-solve to ZPV>1 → code 1.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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| .. | ||
| fixtures | ||
| __init__.py | ||
| _elmhurst_recommendation.py | ||
| test_ashp_cost_inputs.py | ||
| test_elmhurst_cascade_pins.py | ||
| test_floor_recommendation.py | ||
| test_glazing_recommendation.py | ||
| test_heating_recommendation.py | ||
| test_lighting_recommendation.py | ||
| test_measure_dependency.py | ||
| test_optimiser.py | ||
| test_overlay_applicator.py | ||
| test_package_scorer.py | ||
| test_plan.py | ||
| test_plan_valuation.py | ||
| test_products.py | ||
| test_roof_recommendation.py | ||
| test_scoring.py | ||
| test_solar_overshading.py | ||
| test_solar_potential.py | ||
| test_valuation.py | ||
| test_ventilation_recommendation.py | ||
| test_wall_recommendation.py | ||
| test_window_extraction_001431.py | ||