9950226267
SAP 10.2 §4 line 7700 + Table 3 (PDF p.159) define the primary circuit
loss for cylinders heated indirectly through primary pipework:
(59)m = n_m × 14 × [{0.0091 × p + 0.0245 × (1 − p)} × h + 0.0263]
Inputs:
p pipework insulation fraction — Table 3 rows: 0.0 uninsulated,
0.1 first 1 m, 0.3 all accessible, 1.0 fully insulated. RdSAP §3
default table (PDF p.56) supplies p by construction age band:
bands A-J → 0.0, K, L, M → 1.0.
h hours per day of primary circulation, winter / summer split:
• no cylinder thermostat → 11 / 3
• thermostat, NOT separately timed → 5 / 3
• thermostat, separately timed → 3 / 3
("Use summer value for June, July, August and September and
winter value for other months" — spec p.159 footer.)
Spec p.159 lists the zero-loss configurations:
- electric immersion heater
- combi boiler
- CPSU
- thermal store within single casing
- separate boiler + thermal store within 1.5 m insulated pipe
- direct-acting electric boiler
- heat pump from PCDB with HW vessel integral to package
The cohort gate is now PCDB-aware: HP main + PCDB Table 362 record
`hw_vessel_mode != 1` (i.e. non-integral) → primary loss applies. All
7 cohort ASHPs lodge `hw_vessel_mode = 2` (separate and specified)
per Table 362 records 104568 (Mitsubishi) and 102421 (Daikin).
Cert 0380 (band D → p=0.0; cylinder thermostat + separately-timed →
h=3 / 3) lands (59)Jan = 31 × 14 × (0.0245 × 3 + 0.0263) = 43.3132
kWh/month (test pinned at 1e-4 vs cert's dr87 worksheet).
Cumulative cert 0380 API state:
HW kWh/yr 431.4 → 653.1 (target 878, slice 102e closes via η_water)
SAP 92.3 → 91.2 (delta to worksheet 88.51 now +2.73, was +3.75)
Cohort regression: cert 0390-2954 (oil boiler + cylinder, age F →
band A-J p=0.0) now picks up ~516 kWh/yr primary loss, tightening PE
residual -27.50 → -26.01 and CO2 -2.66 → -2.52 (improvements). The
higher HW fuel shifts SAP residual -6 → -7. Re-pinned with slice-102d
note. Closed combi boiler certs (001479, 0330, 9501) unaffected:
has_hot_water_cylinder=false gates the primary-loss override to None.
|
||
|---|---|---|
| .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