d4a8c02b54
SAP 10.2 Appendix M1 §6 (PDF p.94, lines 5510-5513): "apply the normal import electricity price to PV energy used within the dwelling and the 'electricity sold to grid, PV' price from Table 12 to the energy exported. In the case of the former, use a weighted average of high and low rates (Table 12a)." `_pv_dwelling_import_price_gbp_per_kwh` was returning the bare off-peak LOW rate (5.50 p/kWh on a 7-hour tariff) for the PV-used-in-dwelling credit. PV self-consumption displaces the dwelling's "all other uses" electricity (lighting / appliances / pumps), which on an off-peak tariff bills at the Table 12a Grid 2 ALL_OTHER_USES weighted blend, not the low rate. On simulated case 19 the worksheet (252)/(269) credits PV-used-in-dwelling at 14.3110 p/kWh = 0.90 × 15.29 + 0.10 × 5.50; we credited it at 5.50, under-crediting onsite PV by ~£0.088/kWh on every off-peak PV cert. Fix delegates to `_other_fuel_cost_gbp_per_kwh(tariff, prices)` (the same ALL_OTHER_USES rate): STANDARD tariff still returns the flat Table 32 code 30 13.19 p/kWh (golden cohort unchanged — all 2412 tests pass); off-peak returns the weighted high/low blend. Call sites now pass the resolved `_rdsap_tariff(epc)`. The now-unused `_off_peak_low_rate_gbp_per_kwh_via_meter_heuristic` (its only caller) is removed. 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 | ||
| 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