No description
9e77b35ff4
Single algorithm with two passes:
Pass 1 — greedy self-consumption (real-firmware default):
For each hour, charge any surplus, discharge into any demand.
This nails sunny days: battery fills from morning surplus, exports
only after capacity is reached, drains during evening peak.
Pass 2 — daily price-spread arbitrage on the residual capacity:
For each UTC day, repeatedly find the most profitable
cheap-charge → expensive-discharge pair (positive after round-trip
efficiency), execute it, recompute SoC trajectory, repeat until no
profitable cycle remains. Discharge must fit within hourly demand
for plug-in batteries (no grid push). Sees only that day's prices,
matching what a Tibber/Frank-style smart-charging controller does
with day-ahead price visibility.
Effect:
- Sunny weeks (June 17-19): unchanged — greedy fill + evening discharge.
- No-sun weeks (Feb 7+): now generates arbitrage savings instead of €0.
- Mixed weeks: greedy handles surplus, arbitrage handles the rest.
Updated: test_grid_arbitrage_kicks_in_on_no_sun_days replaces the prior
"greedy doesn't arbitrage" test; now verifies the dispatcher charges
cheap hours and discharges expensive ones when no PV is available.
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| data/raw | ||
| docs | ||
| scripts | ||
| src/pluginbattery | ||
| tests | ||
| .env.example | ||
| .gitignore | ||
| CLAUDE.md | ||
| Dockerfile | ||
| Procfile | ||
| pyproject.toml | ||
| README.md | ||
| uv.lock | ||
pluginbattery
Backtest the actual ROI of a home battery against real historical electricity prices and solar irradiance.
Answers: "If I had owned this battery (plug-in or installed) over the last N years, what would it have actually saved me?"
See CLAUDE.md for project intent, open decisions, and assumptions.