Initial import: home-battery ROI simulator + cracked thuisbatterijgids calc
- Hourly data exporter (InfluxDB → CSV) for prices, P1, irradiance. - LP-based 24h-foresight oracle dispatch with SoC-consistent state engine. - Reverse-engineered thuisbatterijgids.nl formula (matches their quotes to within €0.50 across three battery configs). - Catalog scraper for the 52 batteries on thuisbatterijgids.net via their /wp-json REST endpoint. - Web app (Flask) that ranks every catalog battery by honest payback and contrasts with the store's quote, deployable via the included Procfile.
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Michiel Berger
commit
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scripts/compare_batteries.py
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scripts/compare_batteries.py
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#!/usr/bin/env python3
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"""Run the 24h-foresight oracle for several battery configs and print a comparison.
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Saves per-hour CSVs for each config plus a summary table. Tariff: NL consumer.
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With --pv-kwp > 0, synthesizes PV output from horizontal irradiance and treats
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saldering as full export credit at consumer price (NL pre-2027).
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"""
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from __future__ import annotations
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import argparse
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import csv
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import re
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from pathlib import Path
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from pluginbattery.sim import (
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Battery,
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apply_nl_tariff,
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load_hourly,
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oracle_daily_schedule,
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simulate,
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synthesize_pv,
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)
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CONFIGS = [
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(
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"EcoFlow Stream AC (1.92 kWh, 0.8 kW, plug-in)",
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Battery(
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capacity_kwh=1.92,
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max_charge_kw=0.8,
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max_discharge_kw=0.8,
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round_trip_eff=0.90,
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allows_export=False,
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),
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700.0,
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),
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(
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"Marstek 5.12 kWh plug-in (800 W)",
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Battery(
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capacity_kwh=5.12,
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max_charge_kw=0.8,
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max_discharge_kw=0.8,
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round_trip_eff=0.90,
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allows_export=False,
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),
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1339.0,
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),
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(
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"Marstek 5.12 kWh hardwired (2.5 kW)",
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Battery(
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capacity_kwh=5.12,
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max_charge_kw=2.5,
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max_discharge_kw=2.5,
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round_trip_eff=0.90,
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allows_export=False,
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),
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1339.0,
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),
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]
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def slugify(s: str) -> str:
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s = re.sub(r"[^a-zA-Z0-9]+", "_", s).strip("_").lower()
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return s
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def payback_years(year1_savings: float, cost: float, inflation: float = 0.0) -> float:
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"""Solve Σ_{k=0}^{N-1} year1 × (1 + i)^k = cost for N.
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With inflation = 0, reduces to cost / year1. With inflation > 0, the
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closed form is N = log(1 + cost × i / year1) / log(1 + i).
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"""
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if year1_savings <= 0:
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return float("inf")
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if inflation == 0.0:
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return cost / year1_savings
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import math
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return math.log(1 + cost * inflation / year1_savings) / math.log(1 + inflation)
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def main() -> None:
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument(
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"--pv-kwp", type=float, default=0.0,
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help="PV system size in kWp. 0 = no solar (default).",
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)
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parser.add_argument(
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"--pv-target", type=float, default=900.0,
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help="Calibrate PV to this annual yield in kWh/kWp/year. Default 900 = NL norm.",
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)
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parser.add_argument(
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"--saldering", choices=["none", "full"], default="none",
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help="'full' = export at consumer price (NL pre-2027). "
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"'none' = export at raw EPEX (post-2027 default).",
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)
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parser.add_argument(
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"--export-rate", type=float, default=None,
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help="Fixed export EUR/kWh, e.g. 0 for 'no compensation' (sales-calculator style). "
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"Overrides --saldering when set.",
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)
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parser.add_argument(
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"--price-mult", type=float, default=1.0,
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help="Scale consumer price by this factor (default 1.0). Use ~1.5 to project "
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"from our 2023-24 backtest prices to current 2025 retail levels.",
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)
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parser.add_argument(
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"--flat-retail", type=float, default=None,
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help="Replace time-varying consumer price with a flat EUR/kWh value (kills arbitrage). "
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"Mirrors the 'fixed rate' switch on online sales calculators.",
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)
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parser.add_argument(
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"--price-inflation", type=float, default=0.0,
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help="Annual energy-price inflation rate (e.g. 0.03 for 3%%). Affects payback only; "
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"year-1 savings displayed are nominal.",
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)
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args = parser.parse_args()
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df = load_hourly("data/raw")
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df = apply_nl_tariff(df)
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if args.flat_retail is not None:
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df["eur_per_kwh"] = float(args.flat_retail)
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elif args.price_mult != 1.0:
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df["eur_per_kwh"] = df["eur_per_kwh"] * args.price_mult
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pv_note = "no solar"
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if args.pv_kwp > 0:
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df = synthesize_pv(df, kwp=args.pv_kwp, target_kwh_per_kwp_per_year=args.pv_target)
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pv_kwh_year = float(df["pv_kwh"].sum() * 8766.0 / len(df))
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pv_note = f"{args.pv_kwp:.1f} kWp PV, calibrated to {pv_kwh_year:.0f} kWh/yr"
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if args.export_rate is not None:
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df["export_eur_per_kwh"] = float(args.export_rate)
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sald_note = f"export = {args.export_rate:.3f} EUR/kWh (fixed)"
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elif args.saldering == "none":
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df["export_eur_per_kwh"] = df["epex_eur_per_kwh"]
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sald_note = "no saldering (export = raw EPEX)"
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else:
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sald_note = "full saldering (export = consumer price)"
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if args.flat_retail is not None:
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price_note = f"FLAT €{args.flat_retail}/kWh (fixed-rate mode)"
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elif args.price_mult != 1.0:
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price_note = f"EPEX × 1.21 + 0.136 × {args.price_mult:.2f}"
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else:
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price_note = "EPEX × 1.21 + 0.136 (dynamic, as in raw data)"
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print(f"Window: {df.index[0]} → {df.index[-1]}, {len(df)} hours")
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print(f"Tariff: import = {price_note}; {sald_note}")
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if args.price_inflation > 0:
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print(f"Payback uses {args.price_inflation*100:.1f}%/yr energy-price inflation")
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print(f"Solar : {pv_note}\n")
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# Headline figures with no battery, just for context.
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g_no = df["demand_kwh"] - df.get("pv_kwh", 0)
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imp_p = df["eur_per_kwh"]
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exp_p = df.get("export_eur_per_kwh", df["eur_per_kwh"])
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cost_no_battery_total = float((g_no.where(g_no > 0, 0) * imp_p +
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g_no.where(g_no < 0, 0) * exp_p).sum())
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import_kwh = float(g_no.where(g_no > 0, 0).sum())
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export_kwh = float(-g_no.where(g_no < 0, 0).sum())
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print(f" Without battery: {import_kwh:6.0f} kWh imported, {export_kwh:6.0f} kWh exported, "
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f"net bill €{cost_no_battery_total:.2f}\n")
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out_dir = Path("data/processed")
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out_dir.mkdir(parents=True, exist_ok=True)
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summary_rows = []
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header = (
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f"{'Battery':47s}{'€/yr saved':>12s}{'cycles':>9s}"
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f"{'kWh shifted':>13s}{'payback':>10s}"
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)
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print(header)
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print("-" * len(header))
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for name, battery, price in CONFIGS:
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schedule = oracle_daily_schedule(df, battery)
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sim = simulate(df, battery, schedule)
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savings = float(sim["savings"].sum())
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kwh_shifted = float(sim["discharge_kwh"].sum())
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cycles = kwh_shifted / battery.capacity_kwh
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payback = payback_years(savings, price, args.price_inflation)
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sim.to_csv(out_dir / f"hourly_{slugify(name)}.csv")
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summary_rows.append(
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{
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"battery": name,
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"capacity_kwh": battery.capacity_kwh,
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"max_charge_kw": battery.max_charge_kw,
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"max_discharge_kw": battery.max_discharge_kw,
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"price_eur": price,
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"pv_kwp": args.pv_kwp,
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"saldering": args.saldering,
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"annual_savings_eur": round(savings, 2),
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"kwh_shifted": round(kwh_shifted, 1),
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"equivalent_cycles": round(cycles, 1),
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"payback_years": round(payback, 2),
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"price_inflation": args.price_inflation,
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}
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)
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print(
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f"{name:47s}€{savings:9.2f}{cycles:9.1f}{kwh_shifted:11.0f} kWh"
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f"{payback:7.2f} yr"
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)
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summary_path = out_dir / "comparison.csv"
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with summary_path.open("w", newline="") as f:
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writer = csv.DictWriter(f, fieldnames=summary_rows[0].keys())
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writer.writeheader()
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writer.writerows(summary_rows)
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print(f"\nSummary -> {summary_path}")
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print(f"Per-hour outputs -> {out_dir}/hourly_*.csv")
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if __name__ == "__main__":
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main()
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