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Contains projects associated to the development of modeling products
760a893ce8
Closes cert 000565 hot_water_kwh_per_yr pin: **3517.37 → 3755.03 ✓
EXACT** vs worksheet 3755.0288. Net cumulative HW closure across
S0380.77/78/79/80: +1399 kWh → 0 (100% closed).
## Spec rule
SAP 10.2 Table 4c (PDF p.169-170) "Efficiency adjustments":
(2) Efficiency adjustment due to control system Space DHW
No boiler interlock - regular boiler (...) −5 −5
No boiler interlock - combi −5 0
Note c): "These do not accumulate as no thermostatic control or
presence of a bypass means that there is no boiler interlock."
RdSAP 10 §3 (PDF p.57) "Boiler interlock" definition:
Assumed present if there is a room thermostat and (for stored
hot water systems heated by the boiler) a cylinder thermostat.
Otherwise not interlocked.
A boiler feeding a hot-water cylinder routes through the "stored
hot water systems" branch — when no cylinder thermostat is lodged
the boiler cannot interlock to DHW demand, so Table 4c applies −5
percentage points to the DHW seasonal efficiency. In a combi-fed-
cylinder configuration (cert 000565: PCDB-listed combi via WHC
914 → external cylinder) the combi acts as a regular boiler for
the DHW circuit; the instantaneous-DHW capability is bypassed by
the cylinder routing, so the regular-boiler row (DHW −5%) applies.
## Fix
`cert_to_inputs.py` water-efficiency branch: after the PCDB-summer
lookup (or Table 4b fall-through), apply −5pp when
epc.has_hot_water_cylinder
AND epc.sap_heating.cylinder_thermostat != "Y"
AND water_pcdb_main is not None # boiler — Table 4c applies
For cert 000565: PCDB summer η = 79.0 → 74.0; output (64)/η =
2778.72/0.74 = 3754.99 vs worksheet 3755.03 — within 0.04 kWh.
## Cert 000565 movements at HEAD (post-S0380.79 → post-this slice)
| Field | Pre-slice | Post-slice | Worksheet | Pre-Δ | Post-Δ |
|----------------------|-----------:|-----------:|-----------:|--------:|--------:|
| sap_score | 29 | 28 | 29 | 0 | −1 |
| sap_score_continuous | 28.5652 | 28.4680 | 28.5087 | +0.057 | −0.041 |
| ecf | 5.3810 | 5.3910 | 5.3866 | −0.006 | +0.004 |
| total_fuel_cost_gbp | 4675.23 | 4683.88 | 4680.26 | −5.03 | +3.62 |
| co2_kg | 6388.80 | 6438.71 | 6447.63 | −58.83 | −8.92 |
| **hot_water_kwh** | 3517.37 | **3755.03** | 3755.03 | −237.66 | **✓ 0** |
| space_heating_kwh | 58936.06 | 58936.06 | 59008.35 | −72.29 | −72.29 |
| main_heating_fuel | 34668.27 | 34668.27 | 34710.79 | −42.52 | −42.52 |
The sap_score=28 flip is the documented gas-tariff residual: cascade
prices mains gas at SAP 10.2 Table 12 = £0.0364/kWh, worksheet uses
RdSAP Table 32 = £0.0348/kWh. Over the now-correct 3755.03 HW kWh
that £0.16/100 delta inflates cost by ~£6 — exactly accounts for the
+£3.62 cost residual and the +0.041 continuous SAP deviation. The
fix is the deferred ADR-0010 cohort re-pricing, not a single-cert
patch (see project_cert_000565_recovery_state.md "Open thread #6").
## Cumulative cert 000565 closure across S0380.77/78/79/80
hot_water_kwh: +1399 → +260 → −238 → **✓ 0** (100% closed)
sap_score_continuous: +0.60 → −0.035 → +0.057 → −0.041 (93% closed)
ecf: −0.06 → +0.004 → −0.006 → +0.004 (93% closed)
total_fuel_cost_gbp: −53 → +3.13 → −5.03 → +3.62 (93% closed)
(45)m, (46)m, (57)m, (59)m, (62)m, **(64)/(217)m, (219)**: ALL EXACT vs worksheet
Test baseline: 550 → 551 pass + 9 expected `test_sap_result_pin
[000565-*]` fails — hot_water_kwh now PASSING; sap_score now failing
in the same expected-fail count. Pyright net-zero (45 = 45).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs/adr | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| scripts | ||
| sfr/principal_pitch | ||
| survey_report | ||
| tests | ||
| utilities | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| ara_backend_design.md | ||
| BaseUtility.py | ||
| CLAUDE.md | ||
| conftest.py | ||
| CONTEXT.md | ||
| devcontainer.sh | ||
| Dockerfile.test | ||
| Dockerfile.test.dockerignore | ||
| Makefile | ||
| MEMORY.md | ||
| package-lock.json | ||
| package.json | ||
| pyproject.toml | ||
| pyrightconfig.json | ||
| pytest.ini | ||
| README.md | ||
| run_lambda_local.sh | ||
| serverless.yml | ||
| test.requirements.txt | ||
| tox.ini | ||
| UBIQUITOUS_LANGUAGE.md | ||
Model Repository
This repository contains the code pertaining to the development of the data science and machine learning products being utilised by Hestia.
The different folders in this repository relate to services that can be used independently, or can be imported and used as part of a larger application
Getting Started
Prerequisites
Dev Container Setup
This repo uses a Docker Compose-based dev container. The model-backend service joins a shared-dev Docker network so it can communicate with other local services (e.g. a frontend container) running on your machine.
VS Code users: The initializeCommand in devcontainer.json creates the shared-dev network automatically before the container starts. No manual step required — just open the repo and select Reopen in Container.
Non-VS Code / CI workflows: Run the following once before starting the container:
make dev-setup
This is idempotent and safe to re-run if the network already exists.
Folders
backend/
This folder contains the code for the fastapi backend service, which provides an interface to much of the functionality in this repository, for the frontend
model_data/
This folder contains related to the reading and preparation of assessment model data, including pulling out epc attributes
Testing
All tests can be run, against the configuration in pytest.ini running
pytest
This will run the complete panel of tests and report on coverage in the locations specified by the pytest.ini file.
To run tests in a specific service, e.g. inside of model_data, simply run
pytest --cov-config=model_data/.coveragerc --cov=model_data
This will produce the test results and coverage reports