4911c56200
SAP 10.2 Table 12a Grid 1 (PDF p.191): secondary heating is a direct- acting electric room heater (RdSAP 10 §A.2.2 default), on the "Other systems including direct-acting electric" row — 7-hour high-rate fraction 1.00, 10-hour 0.50. A room heater runs on demand, mostly at the high rate; it does NOT earn the 100%-low-rate of overnight storage charging. `_secondary_fuel_cost_gbp_per_kwh` previously returned the flat off-peak LOW rate (5.50 p, £0.0550) for every off-peak electric secondary, under- charging by 9.79 p/kWh. New `_secondary_off_peak_rate_gbp_per_kwh` mirrors `_space_heating_fuel_cost_gbp_per_kwh`: it blends the Table 12a high-rate fraction (OTHER_DIRECT_ACTING_ELECTRIC) against the Table 32 high/low rates, with the 18-/24-hour fallback to the low rate. Simulated case 19 (electric storage main + electric secondary, Dual/7-hour meter) is the worksheet case (242): "Space heating - secondary (1.00*15.29 + 0.00*5.50)" → 15.29 p/kWh = £0.1529. This was the primary cat-7-cluster cost driver: total cost 1485.68 → 1835.53 (worksheet 1816.58), SAP cont 60.11 → 50.67 (worksheet ~51.22). Remaining +19 cost is HW/space-heating kWh (next slices). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
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| sap worksheets | ||
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| sfr/principal_pitch | ||
| survey_report | ||
| tests | ||
| utilities | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
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| __init__.py | ||
| ara_backend_design.md | ||
| BaseUtility.py | ||
| CLAUDE.md | ||
| conftest.py | ||
| CONTEXT.md | ||
| devcontainer.sh | ||
| Dockerfile.test | ||
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| 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