korkece fve predikce, grafy predikci
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This commit is contained in:
Dusan Vojacek
2026-04-22 19:26:46 +02:00
parent ffe80679cc
commit 9ca4b4c577
10 changed files with 819 additions and 5 deletions

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@@ -4,7 +4,7 @@ from __future__ import annotations
import json
import logging
from datetime import date, datetime, timedelta
from datetime import date, datetime, timedelta, timezone
from typing import Annotated, Any
import asyncpg
@@ -522,3 +522,159 @@ async def get_site_forecast_pv_slots_range(
if not isinstance(slots, list):
slots = []
return {"slots": slots}
@router.get("/{site_id}/forecast/pv-slots-corrected")
async def get_site_forecast_pv_slots_range_corrected(
site_id: int,
db: Annotated[asyncpg.Pool, Depends(get_pg_pool)],
from_ts: datetime = Query(
...,
alias="from",
description="Začátek okna [from, to), typicky UTC zaokrouhlené na 15 min",
),
to_ts: datetime = Query(
...,
alias="to",
description="Konec polouzavřeného intervalu (max. cca 120 h za from)",
),
delta_from_ts: datetime | None = Query(
None,
alias="delta_from",
description="Začátek okna historie pro výpočet delta profilu (default: now-60d)",
),
delta_to_ts: datetime | None = Query(
None,
alias="delta_to",
description="Konec okna historie pro výpočet delta profilu (default: now)",
),
half_life_days: float = Query(
14,
ge=1,
le=90,
description="Half-life vážení (dny) pro delta profil",
),
threshold_w: int = Query(
150,
ge=0,
le=10_000,
description="Ignorovat sloty s nízkou výrobou (W) při odhadu profilu",
),
) -> dict[str, list[dict[str, Any]]]:
if to_ts <= from_ts:
raise HTTPException(status_code=422, detail="'to' must be after 'from'")
if to_ts - from_ts > timedelta(hours=120):
raise HTTPException(
status_code=422,
detail="Span between 'from' and 'to' must be at most 120 hours",
)
now = datetime.now(tz=timezone.utc)
delta_to = delta_to_ts or now
delta_from = delta_from_ts or (delta_to - timedelta(days=60))
async with db.acquire() as conn:
site_ok = await conn.fetchval(
"SELECT EXISTS(SELECT 1 FROM ems.site WHERE id = $1)", site_id
)
if not site_ok:
raise HTTPException(status_code=404, detail="Site not found")
raw = await fetch_json(
conn,
"""
select ems.fn_forecast_pv_slots_range_corrected(
$1::int,
$2::timestamptz,
$3::timestamptz,
$4::timestamptz,
$5::timestamptz,
$6::numeric,
$7::int
)
""",
site_id,
from_ts,
to_ts,
delta_from,
delta_to,
half_life_days,
threshold_w,
)
slots = raw if isinstance(raw, list) else []
if not isinstance(slots, list):
slots = []
return {"slots": [s for s in slots if isinstance(s, dict)]}
@router.get("/{site_id}/timeseries/telemetry-15m")
async def get_site_telemetry_15m_range(
site_id: int,
db: Annotated[asyncpg.Pool, Depends(get_pg_pool)],
from_ts: datetime = Query(..., alias="from", description="Začátek okna [from, to)"),
to_ts: datetime = Query(..., alias="to", description="Konec okna [from, to)"),
) -> dict[str, list[dict[str, Any]]]:
if to_ts <= from_ts:
raise HTTPException(status_code=422, detail="'to' must be after 'from'")
if to_ts - from_ts > timedelta(days=60):
raise HTTPException(
status_code=422,
detail="Span between 'from' and 'to' must be at most 60 days",
)
async with db.acquire() as conn:
site_ok = await conn.fetchval(
"SELECT EXISTS(SELECT 1 FROM ems.site WHERE id = $1)", site_id
)
if not site_ok:
raise HTTPException(status_code=404, detail="Site not found")
rows = await conn.fetch(
"""
select
slot_start,
site_id,
avg_pv_w,
avg_load_w,
avg_grid_w,
avg_battery_w,
last_soc_pct,
sample_count
from ems.telemetry_inverter_15m
where site_id = $1
and slot_start >= $2::timestamptz
and slot_start < $3::timestamptz
order by slot_start asc
""",
site_id,
from_ts,
to_ts,
)
return {"slots": [record_to_dict(r) for r in rows]}
@router.get("/{site_id}/forecast/load-baseline-slots")
async def get_site_load_baseline_slots_range(
site_id: int,
db: Annotated[asyncpg.Pool, Depends(get_pg_pool)],
from_ts: datetime = Query(..., alias="from", description="Začátek okna [from, to)"),
to_ts: datetime = Query(..., alias="to", description="Konec okna [from, to)"),
) -> dict[str, list[dict[str, Any]]]:
if to_ts <= from_ts:
raise HTTPException(status_code=422, detail="'to' must be after 'from'")
if to_ts - from_ts > timedelta(days=60):
raise HTTPException(
status_code=422,
detail="Span between 'from' and 'to' must be at most 60 days",
)
async with db.acquire() as conn:
site_ok = await conn.fetchval(
"SELECT EXISTS(SELECT 1 FROM ems.site WHERE id = $1)", site_id
)
if not site_ok:
raise HTTPException(status_code=404, detail="Site not found")
rows = await conn.fetch(
"""
select interval_start, forecast_w, confidence_w
from ems.fn_get_baseline_forecast($1::int, $2::timestamptz, $3::timestamptz)
""",
site_id,
from_ts,
to_ts,
)
return {"slots": [record_to_dict(r) for r in rows]}

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@@ -0,0 +1,121 @@
-- ============================================================
-- Profil systematické chyby PV forecastu po 15min slotu dne
-- (aditivní korekce: corrected = max(0, forecast - delta[slot]))
-- ============================================================
create or replace function ems.fn_pv_forecast_delta_profile(
p_site_id int,
p_data_from timestamptz,
p_data_to timestamptz default now(),
p_half_life_days numeric default 14,
p_threshold_w int default 150
)
returns jsonb
language sql
stable
as $fn$
with tz as (
select coalesce(nullif(trim(s.timezone), ''), 'Europe/Prague') as tz_name
from ems.site s
where s.id = p_site_id
),
-- Cutoff z analýzy DB (EMS Postgres): u site_id=2 (`home-01`) začíná být
-- `forecast_accuracy.actual_power_w` spolehlivě vyplněné pro celé kalendářní dny
-- od 2026-04-06 (Europe/Prague). Dřívší dny mají výrazně nižší podíl slotů s actual
-- (částečný backfill / výpadky) a zkreslují delta profil.
cutoff as (
select timestamptz '2026-04-05T22:00:00Z' as min_ts
),
bounds as (
select
greatest(p_data_from, p_data_to - interval '120 days', (select min_ts from cutoff)) as ts_from,
p_data_to as ts_to,
greatest(p_half_life_days, 1) as half_life_days,
greatest(p_threshold_w, 0) as threshold_w
),
-- vezmeme jeden „reprezentativní“ forecast z historie: pro každý interval_start a pv_array_id
-- vybereme nejnovější forecast (forecast_created_at) který je <= interval_start (lead_time >= 0)
best as (
select
fa.interval_start,
fa.pv_array_id,
fa.forecast_power_w,
fa.actual_power_w,
fa.forecast_created_at,
row_number() over (
partition by fa.interval_start, fa.pv_array_id
order by fa.forecast_created_at desc
) as rn
from ems.forecast_accuracy fa
cross join bounds b
where fa.site_id = p_site_id
and fa.interval_start >= b.ts_from
and fa.interval_start < b.ts_to
and fa.actual_power_w is not null
and fa.forecast_created_at <= fa.interval_start
),
slots as (
select
b.interval_start,
sum(b.forecast_power_w)::numeric as forecast_total_w,
sum(b.actual_power_w)::numeric as actual_total_w,
(
(extract(hour from (b.interval_start at time zone tz.tz_name))::int * 60)
+ extract(minute from (b.interval_start at time zone tz.tz_name))::int
) / 15 as slot_of_day,
extract(epoch from (now() - b.interval_start)) / 86400.0 as age_days
from best b
cross join tz
where b.rn = 1
group by b.interval_start, slot_of_day, tz.tz_name
),
filtered as (
select
s.slot_of_day,
(s.forecast_total_w - s.actual_total_w) as error_w,
exp(-s.age_days / nullif((select half_life_days from bounds), 0)) as w
from slots s
cross join bounds b
where s.slot_of_day between 0 and 95
and (s.actual_total_w > b.threshold_w or s.forecast_total_w > b.threshold_w)
),
agg as (
select
slot_of_day,
count(*) as sample_count,
sum(w) as w_sum,
case
when sum(w) > 0 then sum(error_w * w) / sum(w)
else null
end as delta_w
from filtered
group by slot_of_day
),
spine as (
select generate_series(0, 95) as slot_of_day
)
select jsonb_build_object(
'site_id', p_site_id,
'data_from', (select ts_from from bounds),
'data_to', (select ts_to from bounds),
'half_life_days', (select half_life_days from bounds),
'threshold_w', (select threshold_w from bounds),
'deltas',
coalesce(
jsonb_agg(
jsonb_build_object(
'slot_of_day', sp.slot_of_day,
'delta_w', coalesce(round(a.delta_w)::int, 0),
'sample_count', coalesce(a.sample_count, 0)
)
order by sp.slot_of_day
),
'[]'::jsonb
)
)
from spine sp
left join agg a on a.slot_of_day = sp.slot_of_day;
$fn$;
comment on function ems.fn_pv_forecast_delta_profile(int, timestamptz, timestamptz, numeric, int) is
'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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@@ -0,0 +1,123 @@
-- ============================================================
-- PV forecast sloty (15min) + aditivně korigovaný forecast
-- corrected = max(0, forecast - delta_profile[slot_of_day])
-- ============================================================
create or replace function ems.fn_forecast_pv_slots_range_corrected(
p_site_id int,
p_from timestamptz,
p_to timestamptz,
p_delta_data_from timestamptz,
p_delta_data_to timestamptz default now(),
p_half_life_days numeric default 14,
p_threshold_w int default 150
)
returns jsonb
language sql
stable
as $fn$
with tz as (
select coalesce(nullif(trim(s.timezone), ''), 'Europe/Prague') as tz_name
from ems.site s
where s.id = p_site_id
),
bounds as (
select
p_from as ts_from,
case
when p_to <= p_from then p_from + interval '15 minutes'
when p_to > p_from + interval '120 hours' then p_from + interval '120 hours'
else p_to
end as ts_to
),
slot_spine as (
select gs as interval_start
from bounds b,
generate_series(
b.ts_from,
(b.ts_to - interval '15 minutes')::timestamptz,
interval '15 minutes'
) as gs
),
fc as (
select
u.interval_start,
coalesce(sum(u.power_w), 0)::bigint as pv_forecast_total_w
from (
select distinct on (fpi.interval_start, fpr.pv_array_id)
fpi.interval_start,
fpi.power_w
from ems.forecast_pv_interval fpi
join ems.forecast_pv_run fpr on fpr.id = fpi.run_id
join ems.asset_pv_array apa
on apa.id = fpr.pv_array_id
and apa.site_id = fpr.site_id
cross join bounds b
where fpr.site_id = p_site_id
and fpr.status = 'ok'
and fpi.interval_start >= b.ts_from
and fpi.interval_start < b.ts_to
order by fpi.interval_start, fpr.pv_array_id, fpr.created_at desc
) u
group by u.interval_start
),
profile as (
select ems.fn_pv_forecast_delta_profile(
p_site_id,
p_delta_data_from,
p_delta_data_to,
p_half_life_days,
p_threshold_w
) as j
),
deltas as (
select
(x->>'slot_of_day')::int as slot_of_day,
(x->>'delta_w')::int as delta_w,
(x->>'sample_count')::int as sample_count
from profile p
cross join lateral jsonb_array_elements(p.j->'deltas') as x
)
select coalesce(
jsonb_agg(
jsonb_build_object(
'interval_start', s.interval_start,
'pv_forecast_total_w', coalesce(fc.pv_forecast_total_w, 0),
'pv_forecast_corrected_w',
greatest(
0,
coalesce(fc.pv_forecast_total_w, 0)::int
- coalesce(
(
select d.delta_w
from deltas d
cross join tz
where d.slot_of_day = (
(
(extract(hour from (s.interval_start at time zone tz.tz_name))::int * 60)
+ extract(minute from (s.interval_start at time zone tz.tz_name))::int
) / 15
)
),
0
)
),
'slot_of_day',
(
(
(extract(hour from (s.interval_start at time zone tz.tz_name))::int * 60)
+ extract(minute from (s.interval_start at time zone tz.tz_name))::int
) / 15
)
)
order by s.interval_start
),
'[]'::jsonb
)
from slot_spine s
cross join tz
left join fc on fc.interval_start = s.interval_start;
$fn$;
comment on function ems.fn_forecast_pv_slots_range_corrected(int, timestamptz, timestamptz, timestamptz, timestamptz, numeric, int) is
'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
| **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`). |
---

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@@ -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 />} />

View File

@@ -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

View File

@@ -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}

View File

@@ -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)

View 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>
)
}

View File

@@ -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