korkece fve predikce, grafy predikci
This commit is contained in:
@@ -4,7 +4,7 @@ from __future__ import annotations
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import json
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import logging
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from datetime import date, datetime, timedelta
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from datetime import date, datetime, timedelta, timezone
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from typing import Annotated, Any
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import asyncpg
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@@ -522,3 +522,159 @@ async def get_site_forecast_pv_slots_range(
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if not isinstance(slots, list):
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slots = []
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return {"slots": slots}
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@router.get("/{site_id}/forecast/pv-slots-corrected")
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async def get_site_forecast_pv_slots_range_corrected(
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site_id: int,
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db: Annotated[asyncpg.Pool, Depends(get_pg_pool)],
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from_ts: datetime = Query(
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...,
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alias="from",
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description="Začátek okna [from, to), typicky UTC zaokrouhlené na 15 min",
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),
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to_ts: datetime = Query(
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...,
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alias="to",
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description="Konec polouzavřeného intervalu (max. cca 120 h za from)",
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),
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delta_from_ts: datetime | None = Query(
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None,
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alias="delta_from",
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description="Začátek okna historie pro výpočet delta profilu (default: now-60d)",
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),
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delta_to_ts: datetime | None = Query(
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None,
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alias="delta_to",
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description="Konec okna historie pro výpočet delta profilu (default: now)",
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),
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half_life_days: float = Query(
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14,
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ge=1,
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le=90,
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description="Half-life vážení (dny) pro delta profil",
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),
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threshold_w: int = Query(
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150,
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ge=0,
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le=10_000,
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description="Ignorovat sloty s nízkou výrobou (W) při odhadu profilu",
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),
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) -> dict[str, list[dict[str, Any]]]:
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if to_ts <= from_ts:
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raise HTTPException(status_code=422, detail="'to' must be after 'from'")
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if to_ts - from_ts > timedelta(hours=120):
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raise HTTPException(
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status_code=422,
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detail="Span between 'from' and 'to' must be at most 120 hours",
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)
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now = datetime.now(tz=timezone.utc)
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delta_to = delta_to_ts or now
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delta_from = delta_from_ts or (delta_to - timedelta(days=60))
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async with db.acquire() as conn:
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site_ok = await conn.fetchval(
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"SELECT EXISTS(SELECT 1 FROM ems.site WHERE id = $1)", site_id
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)
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if not site_ok:
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raise HTTPException(status_code=404, detail="Site not found")
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raw = await fetch_json(
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conn,
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"""
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select ems.fn_forecast_pv_slots_range_corrected(
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$1::int,
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$2::timestamptz,
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$3::timestamptz,
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$4::timestamptz,
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$5::timestamptz,
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$6::numeric,
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$7::int
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)
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""",
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site_id,
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from_ts,
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to_ts,
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delta_from,
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delta_to,
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half_life_days,
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threshold_w,
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)
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slots = raw if isinstance(raw, list) else []
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if not isinstance(slots, list):
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slots = []
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return {"slots": [s for s in slots if isinstance(s, dict)]}
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@router.get("/{site_id}/timeseries/telemetry-15m")
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async def get_site_telemetry_15m_range(
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site_id: int,
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db: Annotated[asyncpg.Pool, Depends(get_pg_pool)],
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from_ts: datetime = Query(..., alias="from", description="Začátek okna [from, to)"),
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to_ts: datetime = Query(..., alias="to", description="Konec okna [from, to)"),
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) -> dict[str, list[dict[str, Any]]]:
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if to_ts <= from_ts:
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raise HTTPException(status_code=422, detail="'to' must be after 'from'")
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if to_ts - from_ts > timedelta(days=60):
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raise HTTPException(
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status_code=422,
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detail="Span between 'from' and 'to' must be at most 60 days",
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)
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async with db.acquire() as conn:
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site_ok = await conn.fetchval(
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"SELECT EXISTS(SELECT 1 FROM ems.site WHERE id = $1)", site_id
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)
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if not site_ok:
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raise HTTPException(status_code=404, detail="Site not found")
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rows = await conn.fetch(
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"""
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select
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slot_start,
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site_id,
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avg_pv_w,
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avg_load_w,
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avg_grid_w,
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avg_battery_w,
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last_soc_pct,
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sample_count
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from ems.telemetry_inverter_15m
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where site_id = $1
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and slot_start >= $2::timestamptz
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and slot_start < $3::timestamptz
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order by slot_start asc
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""",
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site_id,
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from_ts,
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to_ts,
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)
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return {"slots": [record_to_dict(r) for r in rows]}
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@router.get("/{site_id}/forecast/load-baseline-slots")
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async def get_site_load_baseline_slots_range(
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site_id: int,
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db: Annotated[asyncpg.Pool, Depends(get_pg_pool)],
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from_ts: datetime = Query(..., alias="from", description="Začátek okna [from, to)"),
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to_ts: datetime = Query(..., alias="to", description="Konec okna [from, to)"),
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) -> dict[str, list[dict[str, Any]]]:
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if to_ts <= from_ts:
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raise HTTPException(status_code=422, detail="'to' must be after 'from'")
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if to_ts - from_ts > timedelta(days=60):
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raise HTTPException(
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status_code=422,
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detail="Span between 'from' and 'to' must be at most 60 days",
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)
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async with db.acquire() as conn:
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site_ok = await conn.fetchval(
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"SELECT EXISTS(SELECT 1 FROM ems.site WHERE id = $1)", site_id
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)
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if not site_ok:
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raise HTTPException(status_code=404, detail="Site not found")
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rows = await conn.fetch(
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"""
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select interval_start, forecast_w, confidence_w
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from ems.fn_get_baseline_forecast($1::int, $2::timestamptz, $3::timestamptz)
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""",
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site_id,
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from_ts,
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to_ts,
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)
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return {"slots": [record_to_dict(r) for r in rows]}
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121
db/routines/R__078_fn_pv_forecast_delta_profile.sql
Normal file
121
db/routines/R__078_fn_pv_forecast_delta_profile.sql
Normal file
@@ -0,0 +1,121 @@
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-- ============================================================
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-- Profil systematické chyby PV forecastu po 15min slotu dne
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-- (aditivní korekce: corrected = max(0, forecast - delta[slot]))
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-- ============================================================
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create or replace function ems.fn_pv_forecast_delta_profile(
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p_site_id int,
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p_data_from timestamptz,
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p_data_to timestamptz default now(),
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p_half_life_days numeric default 14,
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p_threshold_w int default 150
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)
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returns jsonb
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language sql
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stable
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as $fn$
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with tz as (
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select coalesce(nullif(trim(s.timezone), ''), 'Europe/Prague') as tz_name
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from ems.site s
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where s.id = p_site_id
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),
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-- Cutoff z analýzy DB (EMS Postgres): u site_id=2 (`home-01`) začíná být
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-- `forecast_accuracy.actual_power_w` spolehlivě vyplněné pro celé kalendářní dny
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-- od 2026-04-06 (Europe/Prague). Dřívší dny mají výrazně nižší podíl slotů s actual
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-- (částečný backfill / výpadky) a zkreslují delta profil.
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cutoff as (
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select timestamptz '2026-04-05T22:00:00Z' as min_ts
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),
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bounds as (
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select
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greatest(p_data_from, p_data_to - interval '120 days', (select min_ts from cutoff)) as ts_from,
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p_data_to as ts_to,
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greatest(p_half_life_days, 1) as half_life_days,
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greatest(p_threshold_w, 0) as threshold_w
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),
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-- vezmeme jeden „reprezentativní“ forecast z historie: pro každý interval_start a pv_array_id
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-- vybereme nejnovější forecast (forecast_created_at) který je <= interval_start (lead_time >= 0)
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best as (
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select
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fa.interval_start,
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fa.pv_array_id,
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fa.forecast_power_w,
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fa.actual_power_w,
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fa.forecast_created_at,
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row_number() over (
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partition by fa.interval_start, fa.pv_array_id
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order by fa.forecast_created_at desc
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) as rn
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from ems.forecast_accuracy fa
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cross join bounds b
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where fa.site_id = p_site_id
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and fa.interval_start >= b.ts_from
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and fa.interval_start < b.ts_to
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and fa.actual_power_w is not null
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and fa.forecast_created_at <= fa.interval_start
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),
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slots as (
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select
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b.interval_start,
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sum(b.forecast_power_w)::numeric as forecast_total_w,
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sum(b.actual_power_w)::numeric as actual_total_w,
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(
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(extract(hour from (b.interval_start at time zone tz.tz_name))::int * 60)
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+ extract(minute from (b.interval_start at time zone tz.tz_name))::int
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) / 15 as slot_of_day,
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extract(epoch from (now() - b.interval_start)) / 86400.0 as age_days
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from best b
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cross join tz
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where b.rn = 1
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group by b.interval_start, slot_of_day, tz.tz_name
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),
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filtered as (
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select
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s.slot_of_day,
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(s.forecast_total_w - s.actual_total_w) as error_w,
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exp(-s.age_days / nullif((select half_life_days from bounds), 0)) as w
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from slots s
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cross join bounds b
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where s.slot_of_day between 0 and 95
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and (s.actual_total_w > b.threshold_w or s.forecast_total_w > b.threshold_w)
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),
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agg as (
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select
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slot_of_day,
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count(*) as sample_count,
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sum(w) as w_sum,
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case
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when sum(w) > 0 then sum(error_w * w) / sum(w)
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else null
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end as delta_w
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from filtered
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group by slot_of_day
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),
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spine as (
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select generate_series(0, 95) as slot_of_day
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)
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select jsonb_build_object(
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'site_id', p_site_id,
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'data_from', (select ts_from from bounds),
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'data_to', (select ts_to from bounds),
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'half_life_days', (select half_life_days from bounds),
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'threshold_w', (select threshold_w from bounds),
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'deltas',
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coalesce(
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jsonb_agg(
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jsonb_build_object(
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'slot_of_day', sp.slot_of_day,
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'delta_w', coalesce(round(a.delta_w)::int, 0),
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'sample_count', coalesce(a.sample_count, 0)
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)
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order by sp.slot_of_day
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),
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'[]'::jsonb
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)
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)
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from spine sp
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left join agg a on a.slot_of_day = sp.slot_of_day;
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$fn$;
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comment on function ems.fn_pv_forecast_delta_profile(int, timestamptz, timestamptz, numeric, int) is
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'Aditivní delta profil chyby PV forecastu po 15min slotu dne (96 slotů). Zdroj: forecast_accuracy, vážení exp(-age/half_life_days). Vrací JSON {deltas:[{slot_of_day, delta_w, sample_count}], ...}. Interní minimální cutoff dat (2026-04-06 Europe/Prague) brání učení z nekonzistentní historie před kompletním plněním actual.';
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123
db/routines/R__079_fn_forecast_pv_slots_range_corrected.sql
Normal file
123
db/routines/R__079_fn_forecast_pv_slots_range_corrected.sql
Normal file
@@ -0,0 +1,123 @@
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-- ============================================================
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-- PV forecast sloty (15min) + aditivně korigovaný forecast
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-- corrected = max(0, forecast - delta_profile[slot_of_day])
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-- ============================================================
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create or replace function ems.fn_forecast_pv_slots_range_corrected(
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p_site_id int,
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p_from timestamptz,
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p_to timestamptz,
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p_delta_data_from timestamptz,
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p_delta_data_to timestamptz default now(),
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p_half_life_days numeric default 14,
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p_threshold_w int default 150
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)
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returns jsonb
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language sql
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stable
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as $fn$
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with tz as (
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select coalesce(nullif(trim(s.timezone), ''), 'Europe/Prague') as tz_name
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from ems.site s
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where s.id = p_site_id
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),
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bounds as (
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select
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p_from as ts_from,
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case
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when p_to <= p_from then p_from + interval '15 minutes'
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when p_to > p_from + interval '120 hours' then p_from + interval '120 hours'
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else p_to
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end as ts_to
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),
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slot_spine as (
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select gs as interval_start
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from bounds b,
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generate_series(
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b.ts_from,
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(b.ts_to - interval '15 minutes')::timestamptz,
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interval '15 minutes'
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) as gs
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),
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fc as (
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select
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u.interval_start,
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coalesce(sum(u.power_w), 0)::bigint as pv_forecast_total_w
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from (
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select distinct on (fpi.interval_start, fpr.pv_array_id)
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fpi.interval_start,
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fpi.power_w
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from ems.forecast_pv_interval fpi
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join ems.forecast_pv_run fpr on fpr.id = fpi.run_id
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join ems.asset_pv_array apa
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on apa.id = fpr.pv_array_id
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and apa.site_id = fpr.site_id
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cross join bounds b
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where fpr.site_id = p_site_id
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and fpr.status = 'ok'
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and fpi.interval_start >= b.ts_from
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and fpi.interval_start < b.ts_to
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order by fpi.interval_start, fpr.pv_array_id, fpr.created_at desc
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) u
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group by u.interval_start
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),
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profile as (
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select ems.fn_pv_forecast_delta_profile(
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p_site_id,
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p_delta_data_from,
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p_delta_data_to,
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p_half_life_days,
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p_threshold_w
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) as j
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),
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deltas as (
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select
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(x->>'slot_of_day')::int as slot_of_day,
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(x->>'delta_w')::int as delta_w,
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(x->>'sample_count')::int as sample_count
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from profile p
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cross join lateral jsonb_array_elements(p.j->'deltas') as x
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)
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select coalesce(
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jsonb_agg(
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jsonb_build_object(
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'interval_start', s.interval_start,
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'pv_forecast_total_w', coalesce(fc.pv_forecast_total_w, 0),
|
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'pv_forecast_corrected_w',
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greatest(
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0,
|
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coalesce(fc.pv_forecast_total_w, 0)::int
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- coalesce(
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(
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select d.delta_w
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from deltas d
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cross join tz
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where d.slot_of_day = (
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(
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(extract(hour from (s.interval_start at time zone tz.tz_name))::int * 60)
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+ extract(minute from (s.interval_start at time zone tz.tz_name))::int
|
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) / 15
|
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)
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),
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0
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)
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),
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'slot_of_day',
|
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(
|
||||
(
|
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(extract(hour from (s.interval_start at time zone tz.tz_name))::int * 60)
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+ extract(minute from (s.interval_start at time zone tz.tz_name))::int
|
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) / 15
|
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)
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)
|
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order by s.interval_start
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),
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'[]'::jsonb
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)
|
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from slot_spine s
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cross join tz
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left join fc on fc.interval_start = s.interval_start;
|
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$fn$;
|
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|
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comment on function ems.fn_forecast_pv_slots_range_corrected(int, timestamptz, timestamptz, timestamptz, timestamptz, numeric, int) is
|
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'JSON pole {interval_start, pv_forecast_total_w, pv_forecast_corrected_w, slot_of_day} po 15 min pro [p_from, p_to). Korekce je aditivní delta profil z fn_pv_forecast_delta_profile.';
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@@ -18,6 +18,7 @@ Shrnutí otevřených bodů z `docs/06-open-questions.md`, checklistů v modulec
|
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| **Telemetry – výroba FVE:** Registry 672/673/667 jsou **signed** W; `pv_power_w` = max(0,pv1)+max(0,pv2)+max(0,gen) (dashboard); sloupce pv1/pv2/gen ukládají signed pro audit. |
|
||||
| **Ekonomika baterie:** snížení `reserve_soc_percent` na 10 % a `degradation_cost_czk_kwh` na 0.1500 (migrace `V026__battery_economics_tuning.sql`), úpravy objective pro ekonomicky konzistentnější nabíjení/vybíjení. |
|
||||
| **Planning UI operátor akce:** trvale viditelné akce import/forecast/init plan, volba data OTE (dnes/zítra), zobrazení `pv_scarcity_factor` ve stavu plánu. |
|
||||
| **PV delta profil – cutoff historie:** po analýze `ems.forecast_accuracy` pro `home-01` je minimální spolehlivý začátek učení **2026-04-06 (Europe/Prague)** (UTC `2026-04-05T22:00:00Z`); cutoff je zafixovaný v `db/routines/R__078_fn_pv_forecast_delta_profile.sql` (ignoruje starší data i při širším `p_data_from`). |
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -6,6 +6,7 @@ import { useWsLogErrorCount } from './hooks/useWsLogErrorCount'
|
||||
import { Dashboard } from './pages/Dashboard'
|
||||
import Economics from './pages/Economics'
|
||||
import EnergyFlows from './pages/EnergyFlows'
|
||||
import ForecastVsActual from './pages/ForecastVsActual'
|
||||
import { Logs } from './pages/Logs'
|
||||
import Planning from './pages/Planning'
|
||||
import SiteConfiguration from './pages/SiteConfiguration'
|
||||
@@ -70,6 +71,9 @@ function AppLayout() {
|
||||
<NavLink to="/planning" className={tabClass}>
|
||||
Plánování
|
||||
</NavLink>
|
||||
<NavLink to="/forecast-vs-actual" className={tabClass}>
|
||||
Srovnání
|
||||
</NavLink>
|
||||
<NavLink to="/economics" className={tabClass}>
|
||||
Ekonomika
|
||||
</NavLink>
|
||||
@@ -111,6 +115,7 @@ export default function App() {
|
||||
<Route element={<AppLayout />}>
|
||||
<Route index element={<Dashboard />} />
|
||||
<Route path="planning" element={<Planning />} />
|
||||
<Route path="forecast-vs-actual" element={<ForecastVsActual />} />
|
||||
<Route path="economics" element={<Economics />} />
|
||||
<Route path="energy-flows" element={<EnergyFlows />} />
|
||||
<Route path="site-config" element={<SiteConfiguration />} />
|
||||
|
||||
@@ -117,6 +117,74 @@ export async function getForecastPvSlotsRange(
|
||||
return Array.isArray(data?.slots) ? data.slots : []
|
||||
}
|
||||
|
||||
export type ForecastPvSlotCorrectedRow = {
|
||||
interval_start: string
|
||||
pv_forecast_total_w?: number | null
|
||||
pv_forecast_corrected_w?: number | null
|
||||
slot_of_day?: number | null
|
||||
}
|
||||
|
||||
export type ForecastPvSlotsCorrectedParams = {
|
||||
delta_from?: string
|
||||
delta_to?: string
|
||||
half_life_days?: number
|
||||
threshold_w?: number
|
||||
}
|
||||
|
||||
export async function getForecastPvSlotsRangeCorrected(
|
||||
siteId: number,
|
||||
fromIso: string,
|
||||
toIso: string,
|
||||
params?: ForecastPvSlotsCorrectedParams,
|
||||
): Promise<ForecastPvSlotCorrectedRow[]> {
|
||||
const { data } = await client.get<{ slots?: ForecastPvSlotCorrectedRow[] }>(
|
||||
`/sites/${siteId}/forecast/pv-slots-corrected`,
|
||||
{ params: { from: fromIso, to: toIso, ...params }, timeout: 45_000 },
|
||||
)
|
||||
return Array.isArray(data?.slots) ? data.slots : []
|
||||
}
|
||||
|
||||
export type Telemetry15mRow = {
|
||||
slot_start: string
|
||||
site_id: number
|
||||
avg_pv_w?: number | null
|
||||
avg_load_w?: number | null
|
||||
avg_grid_w?: number | null
|
||||
avg_battery_w?: number | null
|
||||
last_soc_pct?: number | null
|
||||
sample_count?: number | null
|
||||
}
|
||||
|
||||
export async function getTelemetry15mRange(
|
||||
siteId: number,
|
||||
fromIso: string,
|
||||
toIso: string,
|
||||
): Promise<Telemetry15mRow[]> {
|
||||
const { data } = await client.get<{ slots?: Telemetry15mRow[] }>(`/sites/${siteId}/timeseries/telemetry-15m`, {
|
||||
params: { from: fromIso, to: toIso },
|
||||
timeout: 60_000,
|
||||
})
|
||||
return Array.isArray(data?.slots) ? data.slots : []
|
||||
}
|
||||
|
||||
export type BaselineLoadSlotRow = {
|
||||
interval_start: string
|
||||
forecast_w: number
|
||||
confidence_w?: number
|
||||
}
|
||||
|
||||
export async function getBaselineLoadSlotsRange(
|
||||
siteId: number,
|
||||
fromIso: string,
|
||||
toIso: string,
|
||||
): Promise<BaselineLoadSlotRow[]> {
|
||||
const { data } = await client.get<{ slots?: BaselineLoadSlotRow[] }>(
|
||||
`/sites/${siteId}/forecast/load-baseline-slots`,
|
||||
{ params: { from: fromIso, to: toIso }, timeout: 60_000 },
|
||||
)
|
||||
return Array.isArray(data?.slots) ? data.slots : []
|
||||
}
|
||||
|
||||
/** GET /api/v1/sites/{id}/prices?date=YYYY-MM-DD */
|
||||
export type SiteEffectivePriceRowDto = {
|
||||
site_id: number
|
||||
|
||||
@@ -31,11 +31,18 @@ function sumW(a: number | null, b: number | null): number | null {
|
||||
return (a ?? 0) + (b ?? 0)
|
||||
}
|
||||
|
||||
export type EnergyLegendItem = { key: string; label: string; color: string; dashed?: boolean }
|
||||
export type EnergyLegendItem = {
|
||||
key: string
|
||||
label: string
|
||||
color: string
|
||||
dashed?: boolean
|
||||
dashStyle?: 'dashed' | 'dotted'
|
||||
}
|
||||
|
||||
export const ENERGY_LEGEND: EnergyLegendItem[] = [
|
||||
{ key: 'fve_real', label: 'FVE skutečnost', color: COL.fve },
|
||||
{ key: 'fve_pred', label: 'FVE předpověď', color: COL.fve, dashed: true },
|
||||
{ key: 'fve_corr', label: 'FVE korigovaná', color: COL.fve, dashed: true, dashStyle: 'dotted' },
|
||||
{ key: 'baz_real', label: 'Spotřeba skutečnost', color: COL.baz },
|
||||
{ key: 'baz_pred', label: 'Spotřeba předpověď', color: COL.baz, dashed: true },
|
||||
{ key: 'ev', label: 'EV plán', color: COL.ev },
|
||||
@@ -93,6 +100,9 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
const series = useMemo(() => {
|
||||
const fveReal = slots.map((s, i) => (i <= nowIndex ? kwFromW(s.pv_power_w) : null))
|
||||
const fvePred = slots.map((s) => kwFromW(sumW(s.pv_a_forecast_w, s.pv_b_forecast_w)))
|
||||
const fveCorr = slots.map((s) =>
|
||||
kwFromW(s.pv_forecast_corrected_w ?? sumW(s.pv_a_forecast_w, s.pv_b_forecast_w)),
|
||||
)
|
||||
const bazReal = slots.map((s, i) => (i <= nowIndex ? kwFromW(s.load_power_w) : null))
|
||||
const bazPred = slots.map((s) => kwFromW(s.load_baseline_w))
|
||||
const ev = slots.map((s) => kwFromW(sumW(s.ev1_setpoint_w, s.ev2_setpoint_w)))
|
||||
@@ -105,7 +115,7 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
)
|
||||
const buy = slots.map((s) => (s.buy_price == null ? null : s.buy_price))
|
||||
const sell = slots.map((s) => (s.sell_price == null ? null : s.sell_price))
|
||||
return { fveReal, fvePred, bazReal, bazPred, ev, tc, bat, sit, buy, sell }
|
||||
return { fveReal, fvePred, fveCorr, bazReal, bazPred, ev, tc, bat, sit, buy, sell }
|
||||
}, [slots, nowIndex])
|
||||
|
||||
const bgPlugin = useMemo(
|
||||
@@ -126,6 +136,7 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
opts: {
|
||||
fill?: boolean | 'origin'
|
||||
dashed?: boolean
|
||||
dash?: number[]
|
||||
yAxisID?: string
|
||||
order: number
|
||||
borderWidth?: number
|
||||
@@ -137,7 +148,7 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
backgroundColor:
|
||||
opts.fill === true ? `${color}33` : opts.fill === 'origin' ? `${color}40` : undefined,
|
||||
fill: opts.fill ?? false,
|
||||
borderDash: opts.dashed ? [5, 4] : undefined,
|
||||
borderDash: opts.dash ?? (opts.dashed ? [5, 4] : undefined),
|
||||
borderWidth: opts.borderWidth ?? (opts.dashed ? 1 : 1.2),
|
||||
pointRadius: 0,
|
||||
hitRadius: 6,
|
||||
@@ -161,6 +172,12 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
mkDs('fve_real', 'FVE ■', series.fveReal, COL.fve, { fill: true, order: 7 }),
|
||||
mkDs('baz_pred', 'Spotřeba ···', series.bazPred, COL.baz, { dashed: true, order: 8 }),
|
||||
mkDs('fve_pred', 'FVE ···', series.fvePred, COL.fve, { dashed: true, order: 9 }),
|
||||
mkDs('fve_corr', 'FVE (korig.)', series.fveCorr, COL.fve, {
|
||||
dashed: true,
|
||||
dash: [2, 3],
|
||||
order: 9,
|
||||
borderWidth: 1,
|
||||
}),
|
||||
mkDs('buy_price', 'Nákup', series.buy, COL.buy, {
|
||||
dashed: true,
|
||||
yAxisID: 'y1',
|
||||
@@ -267,6 +284,7 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
s.fveReal,
|
||||
s.bazPred,
|
||||
s.fvePred,
|
||||
s.fveCorr,
|
||||
s.buy,
|
||||
s.sell,
|
||||
]
|
||||
@@ -290,6 +308,7 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
'fve_real',
|
||||
'baz_pred',
|
||||
'fve_pred',
|
||||
'fve_corr',
|
||||
'buy_price',
|
||||
'sell_price',
|
||||
] as const
|
||||
@@ -326,7 +345,7 @@ export function EnergyChart({ slots, nowIndex, hidden, onToggle, onChartArea }:
|
||||
className="h-2.5 w-4 shrink-0 rounded-sm border border-white/10"
|
||||
style={{
|
||||
backgroundColor: off ? 'transparent' : item.color,
|
||||
borderStyle: item.dashed ? 'dashed' : 'solid',
|
||||
borderStyle: item.dashStyle === 'dotted' ? 'dotted' : item.dashed ? 'dashed' : 'solid',
|
||||
}}
|
||||
/>
|
||||
{item.label}
|
||||
|
||||
@@ -5,6 +5,7 @@ import {
|
||||
getCurrentPlan,
|
||||
getSiteForecastPv,
|
||||
getSitePrices,
|
||||
getForecastPvSlotsRangeCorrected,
|
||||
type SiteEffectivePriceRowDto,
|
||||
} from '../api/backend'
|
||||
import { getJson } from '../api/postgrest'
|
||||
@@ -279,6 +280,20 @@ export function useDashboardData(siteId: number | null) {
|
||||
if (!fc) continue
|
||||
addForecastToByStart(fc, forecastBySlot)
|
||||
}
|
||||
|
||||
const windowFromIso = new Date(windowStart).toISOString()
|
||||
const windowToIso = new Date(windowStart + TOTAL_SLOTS * SLOT_MS).toISOString()
|
||||
const correctedSlots = await getForecastPvSlotsRangeCorrected(siteId, windowFromIso, windowToIso).catch(
|
||||
() => [] as Awaited<ReturnType<typeof getForecastPvSlotsRangeCorrected>>,
|
||||
)
|
||||
const correctedBySlot = new Map<string, number>()
|
||||
for (const r of correctedSlots) {
|
||||
const t = new Date(r.interval_start).getTime()
|
||||
if (!Number.isFinite(t)) continue
|
||||
const v = r.pv_forecast_corrected_w
|
||||
if (v == null) continue
|
||||
correctedBySlot.set(slotTimeKey(t), Number(v))
|
||||
}
|
||||
for (const ymd of weekDates) {
|
||||
const fc = forecastByYmd.get(ymd) ?? null
|
||||
if (!fc) {
|
||||
@@ -364,6 +379,10 @@ export function useDashboardData(siteId: number | null) {
|
||||
base.pv_a_forecast_w = fc.a
|
||||
base.pv_b_forecast_w = fc.b
|
||||
}
|
||||
const corr = correctedBySlot.get(k)
|
||||
if (corr != null) {
|
||||
base.pv_forecast_corrected_w = corr
|
||||
}
|
||||
|
||||
const pi = planBySlot.get(k)
|
||||
if (pi) mergeInterval(base, pi)
|
||||
|
||||
300
frontend/src/pages/ForecastVsActual.tsx
Normal file
300
frontend/src/pages/ForecastVsActual.tsx
Normal file
@@ -0,0 +1,300 @@
|
||||
import { useCallback, useEffect, useMemo, useState } from 'react'
|
||||
import {
|
||||
CartesianGrid,
|
||||
Legend,
|
||||
Line,
|
||||
LineChart,
|
||||
ResponsiveContainer,
|
||||
Tooltip,
|
||||
XAxis,
|
||||
YAxis,
|
||||
} from 'recharts'
|
||||
|
||||
import {
|
||||
getBaselineLoadSlotsRange,
|
||||
getForecastPvSlotsRangeCorrected,
|
||||
getTelemetry15mRange,
|
||||
type BaselineLoadSlotRow,
|
||||
type ForecastPvSlotCorrectedRow,
|
||||
type Telemetry15mRow,
|
||||
} from '../api/backend'
|
||||
import { useSiteStatus } from '../hooks/useSiteStatus'
|
||||
import { instantPragueDay } from '../lib/pragueDate'
|
||||
|
||||
type MetricKey = 'pv' | 'load' | 'grid'
|
||||
|
||||
type Point = {
|
||||
k: string
|
||||
timeLabel: string
|
||||
actual_kw: number | null
|
||||
forecast_kw: number | null
|
||||
corrected_kw: number | null
|
||||
}
|
||||
|
||||
function kwFromW(w: number | null | undefined): number | null {
|
||||
if (w == null || Number.isNaN(Number(w))) return null
|
||||
return Number(w) / 1000
|
||||
}
|
||||
|
||||
function fmtDayLabel(ymd: string): string {
|
||||
return new Date(ymd + 'T12:00:00Z').toLocaleDateString('cs-CZ', {
|
||||
weekday: 'short',
|
||||
day: 'numeric',
|
||||
month: 'numeric',
|
||||
timeZone: 'Europe/Prague',
|
||||
})
|
||||
}
|
||||
|
||||
function DayChart({
|
||||
title,
|
||||
points,
|
||||
showForecast,
|
||||
showCorrected,
|
||||
}: {
|
||||
title: string
|
||||
points: Point[]
|
||||
showForecast: boolean
|
||||
showCorrected: boolean
|
||||
}) {
|
||||
return (
|
||||
<div className="h-[240px] w-full rounded-xl border border-slate-800 bg-slate-900/40 p-2 pt-4">
|
||||
<div className="px-2 pb-2 text-xs font-semibold uppercase tracking-wide text-slate-500">{title}</div>
|
||||
<ResponsiveContainer width="100%" height="100%">
|
||||
<LineChart data={points} margin={{ top: 8, right: 16, left: 0, bottom: 0 }}>
|
||||
<CartesianGrid strokeDasharray="3 3" stroke="#334155" opacity={0.6} />
|
||||
<XAxis dataKey="timeLabel" tick={{ fill: '#94a3b8', fontSize: 11 }} interval={7} />
|
||||
<YAxis
|
||||
tick={{ fill: '#94a3b8', fontSize: 11 }}
|
||||
label={{ value: 'kW', angle: -90, position: 'insideLeft', fill: '#64748b', fontSize: 11 }}
|
||||
/>
|
||||
<Tooltip
|
||||
contentStyle={{
|
||||
backgroundColor: '#0f172a',
|
||||
border: '1px solid #1e293b',
|
||||
borderRadius: '8px',
|
||||
}}
|
||||
labelStyle={{ color: '#e2e8f0' }}
|
||||
/>
|
||||
<Legend wrapperStyle={{ fontSize: 12 }} />
|
||||
<Line
|
||||
type="monotone"
|
||||
dataKey="actual_kw"
|
||||
name="Skutečnost"
|
||||
stroke="#e2e8f0"
|
||||
strokeWidth={2}
|
||||
dot={false}
|
||||
connectNulls
|
||||
/>
|
||||
{showForecast ? (
|
||||
<Line
|
||||
type="monotone"
|
||||
dataKey="forecast_kw"
|
||||
name="Předpověď"
|
||||
stroke="#ef9f27"
|
||||
strokeWidth={1.5}
|
||||
dot={false}
|
||||
connectNulls
|
||||
strokeDasharray="5 4"
|
||||
/>
|
||||
) : null}
|
||||
{showCorrected ? (
|
||||
<Line
|
||||
type="monotone"
|
||||
dataKey="corrected_kw"
|
||||
name="Korigovaná"
|
||||
stroke="#ef9f27"
|
||||
strokeWidth={1.5}
|
||||
dot={false}
|
||||
connectNulls
|
||||
strokeDasharray="2 3"
|
||||
/>
|
||||
) : null}
|
||||
</LineChart>
|
||||
</ResponsiveContainer>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
export default function ForecastVsActual() {
|
||||
const { site: siteRow, ready: siteReady, error: siteErr } = useSiteStatus()
|
||||
const siteId = siteRow?.site_id ?? null
|
||||
|
||||
const [metric, setMetric] = useState<MetricKey>('pv')
|
||||
const [days, setDays] = useState(20)
|
||||
const [ready, setReady] = useState(false)
|
||||
const [error, setError] = useState<string | null>(null)
|
||||
|
||||
const [telemetry, setTelemetry] = useState<Telemetry15mRow[]>([])
|
||||
const [pvSlots, setPvSlots] = useState<ForecastPvSlotCorrectedRow[]>([])
|
||||
const [baselineSlots, setBaselineSlots] = useState<BaselineLoadSlotRow[]>([])
|
||||
|
||||
const load = useCallback(async () => {
|
||||
if (siteId == null) {
|
||||
setTelemetry([])
|
||||
setPvSlots([])
|
||||
setBaselineSlots([])
|
||||
setError(null)
|
||||
setReady(true)
|
||||
return
|
||||
}
|
||||
const to = new Date()
|
||||
const from = new Date(to.getTime() - days * 24 * 60 * 60 * 1000)
|
||||
const fromIso = from.toISOString()
|
||||
const toIso = to.toISOString()
|
||||
try {
|
||||
const [tel, pv, base] = await Promise.all([
|
||||
getTelemetry15mRange(siteId, fromIso, toIso),
|
||||
getForecastPvSlotsRangeCorrected(siteId, fromIso, toIso),
|
||||
getBaselineLoadSlotsRange(siteId, fromIso, toIso),
|
||||
])
|
||||
setTelemetry(tel)
|
||||
setPvSlots(pv)
|
||||
setBaselineSlots(base)
|
||||
setError(null)
|
||||
} catch (e) {
|
||||
setTelemetry([])
|
||||
setPvSlots([])
|
||||
setBaselineSlots([])
|
||||
setError(e instanceof Error ? e.message : 'Chyba načítání dat')
|
||||
} finally {
|
||||
setReady(true)
|
||||
}
|
||||
}, [siteId, days])
|
||||
|
||||
useEffect(() => {
|
||||
void load()
|
||||
}, [load])
|
||||
|
||||
const byInterval = useMemo(() => {
|
||||
const map = new Map<string, { tel?: Telemetry15mRow; pv?: ForecastPvSlotCorrectedRow; base?: BaselineLoadSlotRow }>()
|
||||
for (const r of telemetry) map.set(r.slot_start, { ...(map.get(r.slot_start) ?? {}), tel: r })
|
||||
for (const r of pvSlots) map.set(r.interval_start, { ...(map.get(r.interval_start) ?? {}), pv: r })
|
||||
for (const r of baselineSlots) map.set(r.interval_start, { ...(map.get(r.interval_start) ?? {}), base: r })
|
||||
return map
|
||||
}, [telemetry, pvSlots, baselineSlots])
|
||||
|
||||
const daysGrouped = useMemo(() => {
|
||||
const byDay = new Map<string, Point[]>()
|
||||
const keys = [...byInterval.keys()].sort((a, b) => new Date(a).getTime() - new Date(b).getTime())
|
||||
for (const iso of keys) {
|
||||
const item = byInterval.get(iso)
|
||||
if (!item?.tel) continue
|
||||
const d = new Date(iso)
|
||||
const day = instantPragueDay(iso)
|
||||
const timeLabel = d.toLocaleTimeString('cs-CZ', {
|
||||
hour: '2-digit',
|
||||
minute: '2-digit',
|
||||
timeZone: 'Europe/Prague',
|
||||
})
|
||||
const k = iso
|
||||
|
||||
let actual_kw: number | null = null
|
||||
let forecast_kw: number | null = null
|
||||
let corrected_kw: number | null = null
|
||||
|
||||
if (metric === 'pv') {
|
||||
actual_kw = kwFromW(item.tel.avg_pv_w)
|
||||
forecast_kw = kwFromW(item.pv?.pv_forecast_total_w ?? null)
|
||||
corrected_kw = kwFromW(item.pv?.pv_forecast_corrected_w ?? null)
|
||||
} else if (metric === 'load') {
|
||||
actual_kw = kwFromW(item.tel.avg_load_w)
|
||||
forecast_kw = kwFromW(item.base?.forecast_w ?? null)
|
||||
corrected_kw = null
|
||||
} else if (metric === 'grid') {
|
||||
actual_kw = kwFromW(item.tel.avg_grid_w)
|
||||
forecast_kw = null
|
||||
corrected_kw = null
|
||||
}
|
||||
|
||||
const arr = byDay.get(day) ?? []
|
||||
arr.push({ k, timeLabel, actual_kw, forecast_kw, corrected_kw })
|
||||
byDay.set(day, arr)
|
||||
}
|
||||
return [...byDay.entries()]
|
||||
.sort((a, b) => a[0].localeCompare(b[0]))
|
||||
.map(([day, points]) => ({ day, points }))
|
||||
}, [byInterval, metric])
|
||||
|
||||
const title = metric === 'pv' ? 'FVE (výroba)' : metric === 'load' ? 'Spotřeba (bazál)' : 'Síť (signed)'
|
||||
const showForecast = metric === 'pv' || metric === 'load'
|
||||
const showCorrected = metric === 'pv'
|
||||
|
||||
const tabClass = (on: boolean) =>
|
||||
`rounded-lg px-3 py-2 text-sm font-medium transition ${on ? 'bg-slate-800 text-white' : 'text-slate-400 hover:bg-slate-900 hover:text-slate-200'}`
|
||||
|
||||
return (
|
||||
<div className="min-h-screen bg-gray-950 p-4 text-slate-100 md:p-8">
|
||||
<div className="mx-auto max-w-7xl space-y-5">
|
||||
<header className="border-b border-slate-800/80 pb-5">
|
||||
<h1 className="text-2xl font-bold tracking-tight text-white">Srovnání predikce vs skutečnost</h1>
|
||||
<p className="mt-1 text-sm text-slate-400">Posledních {days} dní (po dnech, 15min sloty)</p>
|
||||
</header>
|
||||
|
||||
{!siteReady ? (
|
||||
<p className="text-sm text-slate-500">Načítám lokalitu…</p>
|
||||
) : siteErr ? (
|
||||
<p className="text-sm text-red-200">{siteErr}</p>
|
||||
) : siteId == null ? (
|
||||
<p className="text-sm text-slate-500">Žádná vybraná lokalita.</p>
|
||||
) : (
|
||||
<div className="flex flex-wrap items-center gap-2">
|
||||
<button type="button" className={tabClass(metric === 'pv')} onClick={() => setMetric('pv')}>
|
||||
FVE
|
||||
</button>
|
||||
<button type="button" className={tabClass(metric === 'load')} onClick={() => setMetric('load')}>
|
||||
Spotřeba
|
||||
</button>
|
||||
<button type="button" className={tabClass(metric === 'grid')} onClick={() => setMetric('grid')}>
|
||||
Síť
|
||||
</button>
|
||||
<div className="ml-auto flex items-center gap-2">
|
||||
<label className="text-xs text-slate-400">
|
||||
Dní:{' '}
|
||||
<input
|
||||
className="ml-1 w-20 rounded-md border border-slate-700 bg-slate-900 px-2 py-1 text-slate-100"
|
||||
type="number"
|
||||
min={3}
|
||||
max={60}
|
||||
value={days}
|
||||
onChange={(e) => setDays(Math.max(3, Math.min(60, Number(e.target.value) || 20)))}
|
||||
/>
|
||||
</label>
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => void load()}
|
||||
className="rounded-lg bg-slate-800 px-3 py-2 text-sm font-semibold text-slate-100 hover:bg-slate-700"
|
||||
>
|
||||
Obnovit
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{error ? (
|
||||
<div className="rounded-xl border border-red-500/40 bg-red-950/40 px-4 py-3 text-sm text-red-200" role="alert">
|
||||
{error}
|
||||
</div>
|
||||
) : null}
|
||||
|
||||
{!ready ? (
|
||||
<p className="text-sm text-slate-500">Načítám data…</p>
|
||||
) : daysGrouped.length === 0 ? (
|
||||
<p className="text-sm text-slate-500">Žádná data pro zvolený rozsah.</p>
|
||||
) : (
|
||||
<section className="space-y-4">
|
||||
{daysGrouped.map(({ day, points }) => (
|
||||
<DayChart
|
||||
key={day}
|
||||
title={`${fmtDayLabel(day)} · ${title}`}
|
||||
points={points}
|
||||
showForecast={showForecast}
|
||||
showCorrected={showCorrected}
|
||||
/>
|
||||
))}
|
||||
</section>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
@@ -14,6 +14,8 @@ export type SlotData = {
|
||||
gen_port_power_w: number | null
|
||||
pv_a_forecast_w: number | null
|
||||
pv_b_forecast_w: number | null
|
||||
/** Korigovaný součet FVE forecastu (W). */
|
||||
pv_forecast_corrected_w?: number | null
|
||||
load_baseline_w: number | null
|
||||
ev1_setpoint_w: number | null
|
||||
ev2_setpoint_w: number | null
|
||||
|
||||
Reference in New Issue
Block a user