ems/backend/services/planning/solver_v2.py

# backend/services/planning/solver_v2.py
#
# EMS plánovač v2 — ČISTÉ ekonomické jádro (Fáze 3).
#
# Filozofie: objective = reálné peníze (nákup − prodej + degradace − terminal
# hodnota energie). Žádné heuristické penalty z constants.py, žádné pre-solver
# fáze/okna/kotvy. Chování (neg-sell příprava, evening export, arbitráž) má
# VYPLYNOUT z cen a fyziky, ne z ručně laděných vah.
#
# Co zůstává (tvrdá pravidla — fyzika, HW, CLAUDE.md):
#   - bilance sběrnice, SoC dynamika s účinnostmi, výkonové stropy
#   - curtailment jen pole A (pravidlo 5); GEN cutoff binárka pole B (pravidlo 6)
#   - block_export_on_negative_sell → ge == 0 při sell < 0 (pravidlo 6, KV1)
#   - buy < 0 → ge == 0 (žádná pumpa import−export přes jeden elektroměr; import
#     je omezen breakerem — pravidlo 7)
#   - export z BATERIE ⇒ koncové SoC ≥ arb floor (pravidlo 19; PV export floor nevynucuje)
#   - zákaz současného importu a exportu (binárka)
#   - load-first Deye: bc_pv + ge_pv jen z PV přebytku nad zátěží
#   - EV deadline, TUV look-ahead, provozní režimy (legitimní constraints)
#   - noční SoC polštář: plán nesmí kalkulovat s vybitím až na min_soc — chyba
#     predikce noční spotřeby by znamenala neplánovaný noční nákup. Velikost
#     z DB (planner_night_baseload_buffer_percent → slot.night_baseload_buffer_wh,
#     klesá k 0 do rána); porušení je PLACENÉ cenou buy daného slotu (riziko
#     zpětného nákupu), takže extrémní sell špička ho smí racionálně prodat.
#   - PV-risk front-load: v okně sell<0 je nabíjení z PV zdarma kdykoliv →
#     indiference v čase; odložení ale spoléhá na predikci (večerní mrak).
#     Malá prémie za držení energie dřív (DB planner_pv_risk_frontload_czk_kwh)
#     vede k "nabít plným výkonem hned, pak řezat A" — emergentně, bez rampy.
#
# Vědomé odchylky od v1 (změří harness):
#   - SQL masky allow_charge / allow_discharge_export se IGNORUJÍ (jsou to
#     výstupy charge-slot-budget heuristik, ne fyzika)
#   - EV náklady jen přes bilanci (v1 je účtuje navíc v objective — dvojí započtení)
#   - import breaker je tvrdý strop (v1 měkký s 10 Kč/kWh)
#   - nedodaná EV energie má explicitní cenu místo infeasibility

from __future__ import annotations

import logging
import time
from typing import Any, Optional

import pulp

from services.planning.constants import (
    INTERVAL_H,
    SOLVER_TIME_LIMIT,
)
from services.planning.types import (
    DispatchResult,
    PlanningSlot,
    _prague_dow_hour,
)
from services.planning.heuristics import _dispatch_grid_setpoint_w

logger = logging.getLogger(__name__)

V2_BUILD_TAG = "v2-clean-2026-06-11"

# Cena za vypnutí GEN portu (mikroinvertory pole B): reálné riziko/opotřebení
# cyklování stykače — drobná, ale nenulová, aby cutoff platil jen při sell < 0.
V2_GEN_CUTOFF_CZK_KWH = 2.0
# SELF_SUSTAIN: export je nežádoucí, ale tvrdé ge=0 by s neřiditelným polem B
# a plnou baterií bylo infeasible — vysoká cena funguje jako ventil.
V2_SELF_SUSTAIN_EXPORT_CZK_KWH = 100.0
# Cena nedodané EV energie do deadline (Kč/kWh) — místo tvrdé infeasibility.
V2_EV_UNMET_CZK_KWH = 50.0
# Nepatrný tie-break proti zbytečnému curtailu při cenové indiferenci (Kč/kWh).
V2_CURTAIL_TIEBREAK_CZK_KWH = 0.001


def _terminal_value_czk_per_wh(slots: list[PlanningSlot], battery: Any) -> float:
    """Shadow cena zbytkové energie: průměrný buy prvních 24 h × DB faktor (pravidlo 16)."""
    n24 = min(len(slots), int(24 / INTERVAL_H))
    avg_buy = sum(float(s.buy_price) for s in slots[:n24]) / max(1, n24)
    factor = float(getattr(battery, "planner_terminal_soc_value_factor", 1.0) or 1.0)
    return max(0.0, avg_buy) * factor / 1000.0


def _arb_floor_wh(battery: Any) -> float:
    """Podlaha SoC pro export z baterie (pravidlo 19): ekonomická rezerva z DB."""
    floor = getattr(battery, "arb_floor_wh", None)
    if floor is None:
        floor = getattr(battery, "reserve_soc_wh", None)
    return max(float(floor or 0.0), float(battery.min_soc_wh))


def solve_dispatch_v2(
    slots: list[PlanningSlot],
    battery: Any,
    heat_pump: Any,
    grid: Any,
    ev_sessions: list,
    vehicles: list,
    current_soc_wh: float,
    current_tuv_temp_c: float,
    *,
    tuv_delta_stats: Optional[dict[tuple[int, int], float]] = None,
    operating_mode: str = "AUTO",
    planner_version: str | None = None,
) -> tuple[list[DispatchResult], int, dict[str, Any]]:
    """Čistý ekonomický MILP; rozhraní kompatibilní se solve_dispatch (v1)."""
    if not slots:
        raise RuntimeError("solve_dispatch_v2 requires at least one slot")
    t0 = time.monotonic()
    T = len(slots)
    om = (operating_mode or "AUTO").upper()
    EV = min(len(vehicles), 2)

    max_imp = float(grid.max_import_power_w)
    max_exp = float(grid.max_export_power_w)
    max_chg = float(battery.max_charge_power_w)
    max_dis = float(battery.max_discharge_power_w)
    eff_c = float(battery.charge_efficiency)
    eff_d = float(battery.discharge_efficiency)
    deg = float(battery.degradation_cost_czk_kwh)
    soc_min = float(battery.min_soc_wh)
    soc_max = float(battery.soc_max_wh)
    usable = float(battery.usable_capacity_wh)
    arb_floor = _arb_floor_wh(battery)
    terminal = _terminal_value_czk_per_wh(slots, battery)
    block_neg_sell = bool(getattr(grid, "block_export_on_negative_sell", False))
    gen_cutoff_avail = bool(getattr(grid, "deye_gen_microinverter_cutoff_enabled", False))
    soc0 = min(max(float(current_soc_wh), soc_min), soc_max)

    prob = pulp.LpProblem("dispatch_v2", pulp.LpMinimize)

    gi = [pulp.LpVariable(f"gi_{t}", 0, max_imp) for t in range(T)]
    ge_pv = [pulp.LpVariable(f"gepv_{t}", 0, max_exp) for t in range(T)]
    ge_bat = [pulp.LpVariable(f"gebat_{t}", 0, max_exp) for t in range(T)]
    bc_pv = [pulp.LpVariable(f"bcpv_{t}", 0, max_chg) for t in range(T)]
    bc_gi = [pulp.LpVariable(f"bcgi_{t}", 0, max_chg) for t in range(T)]
    bd = [pulp.LpVariable(f"bd_{t}", 0, max_dis) for t in range(T)]
    ca = [pulp.LpVariable(f"ca_{t}", 0, max(0, int(slots[t].pv_a_forecast_w))) for t in range(T)]
    soc = [pulp.LpVariable(f"soc_{t}", soc_min, soc_max) for t in range(T)]
    hp = [pulp.LpVariable(f"hp_{t}", 0, float(heat_pump.rated_heating_power_w)) for t in range(T)]
    y_imp = [pulp.LpVariable(f"yimp_{t}", cat=pulp.LpBinary) for t in range(T)]
    z_exp = [pulp.LpVariable(f"zexp_{t}", cat=pulp.LpBinary) for t in range(T)]
    z_gen = (
        [pulp.LpVariable(f"zgen_{t}", cat=pulp.LpBinary) for t in range(T)]
        if gen_cutoff_avail
        else None
    )
    ev_direct = [
        [
            pulp.LpVariable(f"evd_{e}_{t}", 0, min(float(vehicles[e].max_charge_power_w), max_imp))
            for t in range(T)
        ]
        for e in range(EV)
    ]
    ev_via_bat = [
        [
            pulp.LpVariable(f"evb_{e}_{t}", 0, float(vehicles[e].max_charge_power_w))
            for t in range(T)
        ]
        for e in range(EV)
    ]
    ev_unmet: list = []  # slack Wh per session (cena V2_EV_UNMET_CZK_KWH)
    nb_buffer_wh = [max(0.0, float(s.night_baseload_buffer_wh or 0.0)) for s in slots]
    nb_slack = [
        pulp.LpVariable(f"nbs_{t}", 0, nb_buffer_wh[t]) if nb_buffer_wh[t] > 0 else None
        for t in range(T)
    ]

    def _connected(e: int, t: int) -> bool:
        return bool(slots[t].ev1_connected if e == 0 else slots[t].ev2_connected)

    for t in range(T):
        s = slots[t]
        pv_a = max(0.0, float(s.pv_a_forecast_w))
        pv_b = max(0.0, float(s.pv_b_forecast_w))
        pv_a_net = pv_a - ca[t]
        pv_b_eff = pv_b - (pv_b * z_gen[t] if z_gen is not None else 0.0)

        ev_total_t = pulp.lpSum(
            ev_direct[e][t] + ev_via_bat[e][t] for e in range(EV)
        )
        load_site = float(s.load_baseline_w) + ev_total_t + hp[t]

        # bilance sběrnice (W)
        prob += (
            pv_a_net + pv_b_eff + gi[t] + bd[t]
            == load_site + bc_pv[t] + bc_gi[t] + ge_pv[t] + ge_bat[t]
        ), f"balance_{t}"

        # SoC dynamika (Wh)
        prev = soc0 if t == 0 else soc[t - 1]
        prob += (
            soc[t]
            == prev
            + (bc_pv[t] + bc_gi[t]) * eff_c * INTERVAL_H
            - bd[t] / eff_d * INTERVAL_H
        ), f"soc_{t}"

        # výkonové stropy
        prob += bc_pv[t] + bc_gi[t] <= max_chg, f"chg_cap_{t}"
        prob += ge_pv[t] + ge_bat[t] <= max_exp, f"exp_cap_{t}"

        # PV cesty omezené dostupnou výrobou (load-first vynucuje HW; bilance účtuje energii)
        prob += bc_pv[t] + ge_pv[t] <= pv_a_net + pv_b_eff, f"pv_src_{t}"
        # bc_gi jen ze sítě:
        prob += bc_gi[t] <= gi[t], f"bcgi_src_{t}"
        # vybíjení kryje dům + EV-via-bat + export z baterie
        prob += ge_bat[t] + pulp.lpSum(ev_via_bat[e][t] for e in range(EV)) <= bd[t], f"bd_split_{t}"

        # zákaz současného importu a exportu
        prob += gi[t] <= max_imp * y_imp[t], f"imp_excl_{t}"
        prob += ge_pv[t] + ge_bat[t] <= max_exp * (1 - y_imp[t]), f"exp_excl_{t}"

        # pravidlo 19: export z baterie ⇒ SoC ≥ arb floor
        prob += ge_bat[t] <= max_exp * z_exp[t], f"zexp_link_{t}"
        prob += soc[t] >= arb_floor - (soc_max - soc_min) * (1 - z_exp[t]), f"zexp_floor_{t}"

        # noční SoC polštář (viz hlavička): soft floor nad min_soc
        if nb_slack[t] is not None:
            prob += soc[t] >= soc_min + nb_buffer_wh[t] - nb_slack[t], f"night_buf_{t}"

        # tvrdá cenová pravidla
        if float(s.buy_price) < 0.0:
            prob += ge_pv[t] + ge_bat[t] == 0, f"neg_buy_noexp_{t}"
        if float(s.sell_price) < 0.0 and block_neg_sell:
            prob += ge_pv[t] + ge_bat[t] == 0, f"neg_sell_block_{t}"

        # EV dostupnost
        for e in range(EV):
            if not _connected(e, t):
                prob += ev_direct[e][t] == 0
                prob += ev_via_bat[e][t] == 0
            else:
                prob += ev_direct[e][t] + ev_via_bat[e][t] <= float(
                    vehicles[e].max_charge_power_w
                )

        # provozní režimy (tvrdé constraints dle operating-modes.md)
        if om == "SELF_SUSTAIN":
            prob += gi[t] <= float(s.load_baseline_w), f"ss_gi_{t}"
        elif om == "PRESERVE":
            prob += bc_pv[t] == 0
            prob += bc_gi[t] == 0
            prob += bd[t] == 0
        elif om == "CHARGE_CHEAP":
            prob += ge_pv[t] + ge_bat[t] == 0
            prob += bd[t] == 0

    # EV deadline (s placeným slackem místo infeasibility)
    for e in range(EV):
        sess = ev_sessions[e] if e < len(ev_sessions) else None
        if sess is None or not getattr(sess, "energy_needed_wh", 0):
            continue
        t_dl = next(
            (t for t in range(T) if slots[t].interval_start >= sess.target_deadline),
            T - 1,
        )
        unmet = pulp.LpVariable(f"ev_unmet_{e}", 0, float(sess.energy_needed_wh))
        ev_unmet.append(unmet)
        prob += (
            pulp.lpSum(
                (ev_direct[e][t] + ev_via_bat[e][t]) * INTERVAL_H
                for t in range(t_dl + 1)
                if _connected(e, t)
            )
            + unmet
            >= float(sess.energy_needed_wh)
        ), f"ev_deadline_{e}"

    # TUV look-ahead (převzato z v1 — komfortní constraint, ne heuristika)
    rated_hp = float(heat_pump.rated_heating_power_w)
    if tuv_delta_stats and rated_hp > 0 and getattr(heat_pump, "tuv_min_temp_c", None):
        tuv_pred = float(current_tuv_temp_c)
        tgt = float(getattr(heat_pump, "tuv_target_temp_c", 55.0) or 55.0)
        thr = float(heat_pump.tuv_min_temp_c) + 5.0
        for t in range(T):
            dow, hour = _prague_dow_hour(slots[t].interval_start)
            delta = tuv_delta_stats.get((dow, hour), -0.1)
            tuv_pred += float(delta) * INTERVAL_H
            if tuv_pred < thr:
                prob += (
                    pulp.lpSum(hp[s_] for s_ in range(max(0, t - 8), t + 1))
                    >= rated_hp * 0.5
                ), f"tuv_heat_{t}"
                tuv_pred = tgt
        if float(current_tuv_temp_c) < float(heat_pump.tuv_min_temp_c):
            prob += hp[0] >= rated_hp * 0.8, "tuv_emergency"

    # ---------------- objective: jen reálné peníze ----------------
    wh = INTERVAL_H / 1000.0  # W → kWh za slot
    cash = pulp.lpSum(
        gi[t] * float(slots[t].buy_price) * wh
        - (ge_pv[t] + ge_bat[t]) * float(slots[t].sell_price) * wh
        for t in range(T)
    )
    degradation = pulp.lpSum(
        0.5 * (bc_pv[t] + bc_gi[t] + bd[t]) * deg * wh for t in range(T)
    )
    extras = pulp.lpSum(ca[t] * V2_CURTAIL_TIEBREAK_CZK_KWH * wh for t in range(T))
    if z_gen is not None:
        extras += pulp.lpSum(
            max(0.0, float(slots[t].pv_b_forecast_w)) * z_gen[t] * V2_GEN_CUTOFF_CZK_KWH * wh
            for t in range(T)
        )
    if om == "SELF_SUSTAIN":
        extras += pulp.lpSum(
            (ge_pv[t] + ge_bat[t]) * V2_SELF_SUSTAIN_EXPORT_CZK_KWH * wh for t in range(T)
        )
    if ev_unmet:
        extras += pulp.lpSum(u * V2_EV_UNMET_CZK_KWH / 1000.0 for u in ev_unmet)
    nb_terms = [
        nb_slack[t] / 1000.0 * max(0.0, float(slots[t].buy_price))
        for t in range(T)
        if nb_slack[t] is not None
    ]
    if nb_terms:
        extras += pulp.lpSum(nb_terms)
    frontload = float(getattr(battery, "planner_pv_risk_frontload_czk_kwh", 0.0) or 0.0)
    neg_idx = [t for t in range(T) if float(slots[t].sell_price) < 0.0]
    if frontload > 0 and neg_idx:
        # odměna za soc[t] v neg slotech = dřívější nabití vyhrává při indiferenci
        extras -= pulp.lpSum(soc[t] / 1000.0 * frontload for t in neg_idx)

    prob += cash + degradation + extras - terminal * soc[T - 1]

    solver = (
        pulp.HiGHS_CMD(msg=False, timeLimit=SOLVER_TIME_LIMIT)
        if pulp.HiGHS_CMD().available()
        else pulp.PULP_CBC_CMD(msg=False, timeLimit=SOLVER_TIME_LIMIT)
    )
    status = prob.solve(solver)
    duration_ms = int((time.monotonic() - t0) * 1000)
    status_str = pulp.LpStatus[status]
    if status_str != "Optimal":
        # v2 nemá relax řetězec — model je navržen tak, aby byl feasible
        # (placené slacky místo tvrdých kotev). Ne-Optimal je skutečná chyba.
        raise RuntimeError(f"solver_v2: {status_str}")

    # ---------------- DispatchResult assembly (parita s v1) ----------------
    def _val(var) -> float:
        v = pulp.value(var)
        return float(v) if v is not None else 0.0

    results: list[DispatchResult] = []
    for t in range(T):
        s = slots[t]
        bc_tot = _val(bc_pv[t]) + _val(bc_gi[t])
        bd_v = _val(bd[t])
        batt_w = round(bc_tot - bd_v)
        ge_pv_w = round(_val(ge_pv[t]))
        ge_bat_w = round(_val(ge_bat[t]))
        gi_w = _val(gi[t])
        ge_w = float(ge_pv_w + ge_bat_w)
        grid_w, export_mode = _dispatch_grid_setpoint_w(
            gi_w=gi_w,
            ge_w=ge_w,
            ge_bat_w=float(ge_bat_w),
            ge_pv_w=float(ge_pv_w),
            max_export_power_w=int(max_exp),
        )
        if batt_w < 0 and grid_w < 0:
            deye_mode = "SELL"
        elif batt_w > 0 and grid_w > 0:
            deye_mode = "CHARGE"
        else:
            deye_mode = "PASSIVE"
        gen_cut = bool(round(_val(z_gen[t]))) if z_gen is not None else None
        hp_v = _val(hp[t])
        hp_on = hp_v > rated_hp * 0.5 if rated_hp > 0 else False
        cash_t = gi_w * float(s.buy_price) * wh - ge_w * float(s.sell_price) * wh
        pen_t = 0.0
        if gen_cut:
            pen_t += max(0.0, float(s.pv_b_forecast_w)) * V2_GEN_CUTOFF_CZK_KWH * wh
        results.append(
            DispatchResult(
                interval_start=s.interval_start,
                battery_setpoint_w=batt_w,
                battery_soc_target=round(_val(soc[t]) / usable * 100.0, 2),
                grid_setpoint_w=grid_w,
                export_limit_w=int(max_exp) if grid_w < 0 else 0,
                export_mode=export_mode,
                deye_physical_mode=deye_mode,
                deye_gen_cutoff_enabled=gen_cut,
                ev1_setpoint_w=(
                    round(_val(ev_direct[0][t]) + _val(ev_via_bat[0][t]))
                    if EV > 0 and s.ev1_connected
                    else None
                ),
                ev2_setpoint_w=(
                    round(_val(ev_direct[1][t]) + _val(ev_via_bat[1][t]))
                    if EV > 1 and s.ev2_connected
                    else None
                ),
                ev1_via_bat_w=round(_val(ev_via_bat[0][t])) if EV > 0 else 0,
                ev2_via_bat_w=round(_val(ev_via_bat[1][t])) if EV > 1 else 0,
                heat_pump_enabled=hp_on,
                heat_pump_setpoint_w=int(rated_hp) if hp_on else 0,
                pv_a_curtailed_w=round(_val(ca[t])),
                expected_cost_czk=round(cash_t, 4),
                effective_buy_price=float(s.buy_price),
                effective_sell_price=float(s.sell_price),
                is_predicted_price=bool(s.is_predicted_price),
                cashflow_czk=round(cash_t, 4),
                battery_arbitrage_czk=0.0,
                penalty_czk=round(pen_t, 4),
                green_bonus_czk=float(getattr(s, "green_bonus_czk_per_slot", 0.0) or 0.0),
            )
        )

    snapshot: dict[str, Any] = {
        "version": planner_version or "v2-clean",
        "planner_build_tag": V2_BUILD_TAG,
        "inputs": {
            "operating_mode": om,
            "current_soc_wh": soc0,
            "terminal_czk_per_wh": round(terminal, 8),
            "arb_floor_wh": arb_floor,
            "block_export_on_negative_sell": block_neg_sell,
            "gen_cutoff_available": gen_cutoff_avail,
            "slot_count": T,
            "ev_sessions": sum(1 for x in ev_sessions if x is not None),
            "masks_ignored": True,
            "night_buffer_slots": sum(1 for b in nb_buffer_wh if b > 0),
            "pv_risk_frontload_czk_kwh": frontload if neg_idx else 0.0,
            "night_buffer_max_wh": round(max(nb_buffer_wh), 1) if nb_buffer_wh else 0,
        },
        "objective_terms": {
            "cash_czk": round(float(pulp.value(cash)), 3),
            "degradation_czk": round(float(pulp.value(degradation)), 3),
            "extras_czk": round(float(pulp.value(extras)), 3) if not isinstance(extras, float) else 0.0,
            "terminal_value_czk": round(terminal * _val(soc[T - 1]), 3),
            "ev_unmet_wh": [round(_val(u), 1) for u in ev_unmet],
        },
        "solver_duration_ms": duration_ms,
        "solver_status": status_str,
    }
    return results, duration_ms, snapshot