pluginbattery/scripts/compare_with_store.py

#!/usr/bin/env python3
"""Run a scenario through both our LP and the cracked store calculator.

This lets us see, for any battery / PV / saldering / rate combination, what
thuisbatterijgids.nl claims you'll save vs what the actual physics permit.

Examples:
    # Reproduce the dynamic-mode tests:
    python scripts/compare_with_store.py --capacity 1.92 --power 0.8 --cost 700 --retail 0.25
    python scripts/compare_with_store.py --capacity 5.12 --power 0.8 --cost 1339 --retail 0.25
    python scripts/compare_with_store.py --capacity 5.12 --power 2.5 --cost 1339 --retail 0.25

    # Fixed retail, no saldering:
    python scripts/compare_with_store.py --fixed --retail 0.28
"""
from __future__ import annotations

import argparse

from pluginbattery.sim import (
    Battery,
    apply_nl_tariff,
    load_hourly,
    oracle_daily_schedule,
    simulate,
)
from pluginbattery.store_calc import (
    Scenario,
    StoreParams,
    payback_years,
    quote as store_quote,
)


def main() -> None:
    p = argparse.ArgumentParser(description=__doc__)
    # Battery
    p.add_argument("--capacity", type=float, default=1.92, help="Battery capacity in kWh")
    p.add_argument("--power", type=float, default=0.8, help="Battery in/out power in kW")
    p.add_argument("--cost", type=float, default=700, help="Battery price (incl. VAT) in EUR")
    p.add_argument("--eta", type=float, default=0.88, help="LP round-trip efficiency")
    # Tariff
    p.add_argument("--retail", type=float, default=0.25, help="Average retail EUR/kWh")
    p.add_argument("--demand", type=float, default=4000.0, help="Annual demand kWh/yr")
    p.add_argument("--fixed", action="store_true",
                   help="Fixed-rate mode (no time-of-day variation; kills arbitrage)")
    p.add_argument("--saldering", action="store_true",
                   help="Full saldering on (export = retail). Default: no saldering.")
    # Inflation
    p.add_argument("--inflation", type=float, default=0.03)
    args = p.parse_args()

    # ─── Honest LP ─────────────────────────────────────────────────────
    base = load_hourly("data/raw"); base = apply_nl_tariff(base)
    df = base.copy()

    # Demand scaling — scale the entire signed signal so existing-PV exports
    # scale with the household.
    annual_net_demand = base["raw_demand_kw"].sum() * (8766.0 / len(base))
    df["raw_demand_kw"] = base["raw_demand_kw"] * (args.demand / annual_net_demand)

    # Retail price.
    if args.fixed:
        df["eur_per_kwh"] = args.retail
        epex_in_use = base["epex_eur_per_kwh"]  # raw EPEX kept
    else:
        scale = args.retail / base["eur_per_kwh"].mean()
        df["eur_per_kwh"] = base["eur_per_kwh"] * scale
        df["epex_eur_per_kwh"] = base["epex_eur_per_kwh"] * scale
        epex_in_use = df["epex_eur_per_kwh"]

    # Saldering.
    if args.saldering:
        df["export_eur_per_kwh"] = df["eur_per_kwh"]
    else:
        df["export_eur_per_kwh"] = 0.0  # post-saldering default in this script

    has_existing_pv = bool((df["raw_demand_kw"] < 0).any())

    bat = Battery(
        capacity_kwh=args.capacity,
        max_charge_kw=args.power,
        max_discharge_kw=args.power,
        round_trip_eff=args.eta,
        allows_export=False,
    )
    out = simulate(df, bat, oracle_daily_schedule(df, bat))
    lp_year1 = float(out["savings"].sum())
    lp_payback = payback_years(lp_year1, args.cost, args.inflation)

    # ─── Store calculator (cracked) ────────────────────────────────────
    avg_epex_used = float(epex_in_use.mean())
    store_params = StoreParams(avg_epex_eur_per_kwh=avg_epex_used)
    scenario = Scenario(
        capacity_kwh=args.capacity,
        max_charge_kw=args.power,
        battery_cost_eur=args.cost,
        avg_retail_eur_per_kwh=args.retail,
        has_pv=has_existing_pv,
        has_saldering=args.saldering,
        dynamic_rate=not args.fixed,
    )
    sq = store_quote(scenario, store_params, inflation=args.inflation)

    # ─── Report ─────────────────────────────────────────────────────────
    print(f"Scenario:")
    print(f"  Battery        : {args.capacity} kWh / {args.power} kW / €{args.cost:.0f}")
    print(f"  Tariff         : avg retail €{args.retail}, "
          f"{'FIXED' if args.fixed else 'DYNAMIC'} rate, "
          f"{'WITH' if args.saldering else 'NO'} saldering")
    print(f"  PV             : {'existing PV in meter signal' if has_existing_pv else 'no measurable existing PV'}")
    print(f"  Net demand     : {args.demand:.0f} kWh/yr")
    print(f"  Inflation      : {args.inflation*100:.1f}%/yr")
    print()
    print(f"{'':22s}  {'year-1 €':>10s}  {'payback':>9s}")
    print(f"  {'Honest LP':20s}  €{lp_year1:>8.2f}    {lp_payback:>5.2f} yr")
    print(f"  {'Store calculator':20s}  €{sq['year1_total']:>8.2f}    {sq['payback_years']:>5.2f} yr")
    if sq["dynamic_arbitrage"] > 0 or sq["pv_self_consumption"] > 0:
        print(f"     ↳ arbitrage     €{sq['dynamic_arbitrage']:>8.2f}")
        print(f"     ↳ self-consume  €{sq['pv_self_consumption']:>8.2f}")
    if sq["year1_total"] > 0:
        ratio = sq["year1_total"] / max(lp_year1, 1e-9)
        print()
        print(f"  Store overstates savings by {ratio:.2f}× "
              f"(€{sq['year1_total'] - lp_year1:+.2f}/yr)")


if __name__ == "__main__":
    main()