# 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) # # 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) 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}" # 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) 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, }, "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