035303e9f8
SAP 10.2 worksheet block 12b (CO2) / 13b (PE) for community heating
"CHP and boilers" (SAP code 302). Per unit of network heat fuel
H = (307)+(310) the effective generation factor is:
chp×100/(362)×f_fuel − chp×(361)/(362)×f_disp + (1−chp)×100/(367)×f_fuel
(363)/(463) CHP fuel = chp_frac × 100/heat_eff × f_fuel
(364)/(464) less credit = −chp_frac × elec_eff/heat_eff × f_disp
(368)/(468) boiler fuel = (1−chp_frac) × 100/boiler_eff × f_fuel
f_fuel = Table 12 heat-network fuel factor (the CHP unit and the back-up
boilers burn the same community fuel — verified vs CH2 gas / CH4 oil /
CH6 coal worksheets (363)/(368)); f_disp = Table 12f (PDF p.196) credit
for the CHP-generated electricity. RdSAP 10 §C (p.58) defaults: heat eff
50% (362), electrical eff 25% (361), boiler eff 80% (367); CHP heat frac
0.35 per-cert via community_heating_chp_fraction.
New `_heat_network_code_302_effective_factor` + Table 12f flexible
constants (0.420 CO2 / 2.369 PE) + RdSAP §C efficiency constants, wired
into all four factor helpers (main + HW, CO2 + PE) ahead of the existing
single-fuel / 1-over-heat-source-eff path. The worksheet (368)/(468)
boiler emissions DISPLAY rounded/mis-aligned in the PDF, but the
(373)/(473)/(386)/(486) totals reconcile only with the boiler at the
full Table 12 factor — verified EXACT.
Two spec citations applied:
- Table 12f flexible-operation default for RdSAP community CHP is an
Elmhurst engine choice (Table 12f notes make "standard" the default);
mirrored per [[feedback-software-no-special-handling]] and documented
in SAP_CALCULATOR.md §8.3.
- Table 12 heat-network oil/biodiesel CO2 (codes 53/56) corrected
0.298 → 0.335 per Table 12 (p.189) "assumes 'gas oil'"; the code-302
oil cascade (CH4) was the first to exercise it. PE 1.180 was already
correct. No other variant uses these codes (no regression).
Closures (CO2 + PE only — the CHP credit does not touch cost/SAP):
CH2 (CHP/Gas) CO2 −1411.49→+0.0000, PE +1331.23→+0.0000 EXACT
CH4 (CHP/Oil) CO2 −4378.24→−0.0000, PE +319.81→−0.0000 EXACT
CH6 (CHP/Coal) CO2/PE re-pinned (+2411.54 / +5023.48) — its worksheet
lodges a manual DLF=1.0 the Summary doesn't carry, so
cascade DLF=1.45 over-scales H; same root as the CH6
SAP −7.49 / cost +£172 (separate DLF front).
CH2/CH4 are now CO2+PE-exact but still carry the heat-network cost/SAP
residual (+0.5277 SAP / −£12.16 cost, exposed by S0380.175 — cost-side,
untouched here). CH3 unchanged (code 304 community-HP COP front).
Corpus state: 37 variants EXACT on all four metrics (incl. CH1);
remaining residuals are CH2/CH4 cost+SAP, CH3 CO2+PE (HP COP), CH6
all-metric (DLF quirk). 2223 pass + 1 skip + 0 fail (tolerances 1e-4 all
metrics per S0380.181); pyright net-zero 43→43.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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|---|---|---|
| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| sap worksheets/heating systems examples | ||
| 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