Battery timeline modal + switch to real 2025 data
Modal: - Click any battery row to open a modal with three uPlot charts: irradiance (W/m²), battery SoC (kWh), net meter flow (kWh/h). - Date picker + prev/next buttons + 1/3/7-day window selector. - 'Battery on' toggle flips the SoC and grid charts to the no-battery baseline; summary numbers update accordingly. - New /api/timeline endpoint returns the full per-hour series for any (battery, scenario, window). Data: - Re-exported prices + solar from data-vm for 2025-01-01 → 2025-09-01 (8 months — solar coverage limit). All three signals now share real 2025 timestamps; no more month/day alignment fudge. - Re-processed dad's CSV against the new window so power_w is real net consumption per actual hour. - Compute_leaderboard now applies an 8766/window-hours annualisation factor to year-1 savings, capt kWh, throughput, and total surplus so payback / 10-yr net stay correct on the shorter window. - Defaults: demand 1010 (= dad's net over 8 months, scale 1.0), start 2025-06-15. Tests pass. Local run: PORT=8765 uv run python -m pluginbattery.web, click any row.
This commit is contained in:
Michiel Berger
parent
10cc32ddc0
commit
b39501ca21
7 changed files with 17794 additions and 26343 deletions
14616
data/raw/p1_hourly.csv
14616
data/raw/p1_hourly.csv
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@ -255,3 +255,179 @@ captureInitialFromDOM();
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repaint(); // honour saved filter + sort on first paint
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repaint(); // honour saved filter + sort on first paint
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form.addEventListener("submit", (e) => { e.preventDefault(); recalc(); });
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form.addEventListener("submit", (e) => { e.preventDefault(); recalc(); });
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// ─── Battery timeline modal ────────────────────────────────────────────
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const modal = document.getElementById("timeline-modal");
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const tlTitle = document.getElementById("tl-title");
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const tlDate = document.getElementById("tl-date");
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const tlDays = document.getElementById("tl-days");
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const tlOnBox = document.getElementById("tl-battery-on");
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const tlPrev = document.getElementById("tl-prev");
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const tlNext = document.getElementById("tl-next");
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const tlStatus = document.getElementById("tl-status");
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const tlSummary = document.getElementById("tl-summary");
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let activeBattery = null; // the row clicked
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let tlData = null; // last fetched timeline payload
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let charts = { irr: null, soc: null, grid: null };
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function openModalForBattery(row) {
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activeBattery = row;
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tlTitle.textContent = `${row.title} — ${fmtNum(row.capacity_kwh)} kWh / ${fmtNum(row.power_kw, 1)} kW`;
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if (!tlDate.value) tlDate.value = "2025-06-15";
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modal.hidden = false;
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refreshTimeline();
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}
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function closeModal() {
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modal.hidden = true;
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for (const c of Object.values(charts)) c?.destroy?.();
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charts = { irr: null, soc: null, grid: null };
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}
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modal.querySelectorAll('[data-close="modal"]').forEach(
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(el) => el.addEventListener("click", closeModal),
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);
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document.addEventListener("keydown", (e) => {
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if (e.key === "Escape" && !modal.hidden) closeModal();
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});
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function shiftDate(days) {
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const d = new Date(tlDate.value || "2024-06-17");
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d.setUTCDate(d.getUTCDate() + days);
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tlDate.value = d.toISOString().slice(0, 10);
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}
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tlPrev.addEventListener("click", () => { shiftDate(-parseInt(tlDays.value, 10)); refreshTimeline(); });
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tlNext.addEventListener("click", () => { shiftDate(+parseInt(tlDays.value, 10)); refreshTimeline(); });
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tlDate.addEventListener("change", refreshTimeline);
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tlDays.addEventListener("change", refreshTimeline);
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tlOnBox.addEventListener("change", () => paintTimeline(tlData)); // local toggle, no refetch
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async function refreshTimeline() {
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if (!activeBattery) return;
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tlStatus.textContent = "Loading…";
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const sc = readScenario();
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const params = new URLSearchParams({
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cap: activeBattery.capacity_kwh,
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power: activeBattery.power_kw,
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allows_export: activeBattery.category === "hybrid",
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start: tlDate.value || "2024-06-17",
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days: tlDays.value,
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demand_kwh: sc.demand_kwh, retail: sc.retail,
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pv_kwp: sc.pv_kwp, fixed_rate: sc.fixed_rate,
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saldering: sc.saldering, eta: sc.eta,
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});
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if (sc.export_rate !== null) params.set("export_rate", sc.export_rate);
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try {
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const r = await fetch(`/api/timeline?${params}`);
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if (!r.ok) {
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const err = await r.json().catch(() => ({}));
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throw new Error(err.error || `HTTP ${r.status}`);
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}
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tlData = await r.json();
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paintTimeline(tlData);
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tlStatus.textContent = "";
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} catch (e) {
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tlStatus.textContent = `Error: ${e.message}`;
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}
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}
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function paintTimeline(d) {
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if (!d) return;
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const batteryOn = tlOnBox.checked;
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// Summary, switching when toggle flips.
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const s = d.summary;
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const cost = batteryOn ? s.cost_with_battery_eur : s.cost_no_battery_eur;
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const imports = batteryOn ? s.imports_with_bat : s.imports_no_bat;
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const exports_ = batteryOn ? s.exports_with_bat : s.exports_no_bat;
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const savings = batteryOn ? s.savings_eur : 0;
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tlSummary.replaceChildren();
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for (const [k, v] of [
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["window cost", `€${cost.toFixed(2)}`],
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["imports", `${imports.toFixed(1)} kWh`],
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["exports", `${exports_.toFixed(1)} kWh`],
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["battery throughput", batteryOn
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? `${s.battery_charge_kwh.toFixed(1)} in / ${s.battery_discharge_kwh.toFixed(1)} out kWh`
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: `— (battery off)`],
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["window saving", `€${savings.toFixed(2)}`],
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]) {
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const row = document.createElement("div");
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const lbl = document.createElement("span"); lbl.textContent = k;
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const val = document.createElement("strong"); val.textContent = v;
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row.append(lbl, val); tlSummary.appendChild(row);
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}
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// X axis: unix seconds (uPlot wants epoch seconds)
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const xs = d.hours.map(h => Date.parse(h.ts) / 1000);
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const irr = d.hours.map(h => h.irradiance);
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const soc = batteryOn ? d.hours.map(h => h.soc) : d.hours.map(() => 0);
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const grid = batteryOn ? d.hours.map(h => h.grid_with_bat)
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: d.hours.map(h => h.grid_no_bat);
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drawChart("irr", ["Time", "W/m²"], xs, irr, "tl-chart-irradiance",
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{ stroke: "#fbbf24", fill: "rgba(251, 191, 36, 0.2)" });
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drawChart("soc", ["Time", "kWh"], xs, soc, "tl-chart-soc",
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{ stroke: "#4ade80", fill: "rgba(74, 222, 128, 0.2)" });
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drawChart("grid", ["Time", "kWh/h"], xs, grid, "tl-chart-grid",
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{ stroke: batteryOn ? "#93c5fd" : "#fb7185",
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fill: batteryOn ? "rgba(147, 197, 253, 0.18)" : "rgba(251, 113, 133, 0.18)",
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zeroline: true });
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}
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function drawChart(key, axes, xs, ys, containerId, opts = {}) {
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const el = document.getElementById(containerId);
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if (charts[key]) charts[key].destroy();
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el.innerHTML = "";
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const data = [xs, ys];
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const u = new uPlot({
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width: el.clientWidth, height: el.clientHeight,
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cursor: { y: false, lock: false },
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legend: { show: false },
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series: [
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{},
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{
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stroke: opts.stroke || "#93c5fd",
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fill: opts.fill,
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width: 1.5,
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points: { show: false },
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},
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],
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axes: [
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{ stroke: "#9aa6b2",
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grid: { stroke: "#2a323b", width: 1 },
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ticks: { stroke: "#2a323b" } },
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{ stroke: "#9aa6b2",
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grid: { stroke: "#2a323b", width: 1 },
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ticks: { stroke: "#2a323b" },
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size: 45 },
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],
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hooks: opts.zeroline ? {
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drawAxes: [(u) => {
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const ctx = u.ctx;
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const y0 = u.valToPos(0, "y", true);
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ctx.save();
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ctx.strokeStyle = "#9aa6b2"; ctx.lineWidth = 1;
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ctx.beginPath();
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ctx.moveTo(u.bbox.left, y0);
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ctx.lineTo(u.bbox.left + u.bbox.width, y0);
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ctx.stroke();
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ctx.restore();
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}],
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} : {},
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}, data, el);
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charts[key] = u;
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}
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// Hook up battery row clicks.
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tbody.addEventListener("click", (e) => {
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// Ignore link clicks — let those go to the shop page if user explicitly wants it.
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if (e.target.closest("a")) return;
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const tr = e.target.closest("tr");
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if (!tr) return;
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const idx = Array.from(tbody.children).indexOf(tr);
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const visible = applySort(applyFilter(lastBatteries));
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if (visible[idx]) openModalForBattery(visible[idx]);
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});
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@ -200,6 +200,53 @@ dl.legend {
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}
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}
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dl.legend dt { font-weight: 600; color: var(--text); }
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dl.legend dt { font-weight: 600; color: var(--text); }
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dl.legend dd { margin: 0; }
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dl.legend dd { margin: 0; }
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/* Make leaderboard rows look clickable */
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table#leaderboard tbody tr { cursor: pointer; }
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table#leaderboard tbody tr a { color: inherit; text-decoration: underline dotted; text-underline-offset: 2px; }
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/* Modal */
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.modal { position: fixed; inset: 0; z-index: 100; display: flex;
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align-items: stretch; justify-content: center; }
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.modal[hidden] { display: none; }
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.modal-backdrop { position: absolute; inset: 0; background: rgba(0,0,0,0.7); }
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.modal-card {
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position: relative; background: var(--bg); border: 1px solid var(--border);
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border-radius: 10px; max-width: 1200px; width: calc(100% - 2rem);
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margin: 1rem auto; padding: 1.25rem; overflow-y: auto; max-height: calc(100vh - 2rem);
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}
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.modal-card header { display: flex; justify-content: space-between;
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align-items: baseline; margin-bottom: 0.75rem; }
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.modal-card h2 { margin: 0; font-size: 1.1rem; }
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.modal-close { background: none; border: 0; font-size: 1.6rem; line-height: 1;
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color: var(--muted); cursor: pointer; padding: 0 0.5rem; }
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.modal-close:hover { color: var(--text); }
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.modal-controls { display: flex; gap: 0.6rem; align-items: center;
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flex-wrap: wrap; margin-bottom: 0.75rem; font-size: 0.85rem; }
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.modal-controls button, .modal-controls input, .modal-controls select {
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background: var(--panel2); color: var(--text); border: 1px solid var(--border);
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border-radius: 6px; padding: 0.35rem 0.6rem; font-size: 0.85rem;
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}
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.modal-controls button { cursor: pointer; }
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.modal-summary {
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display: grid; grid-template-columns: repeat(auto-fit, minmax(180px, 1fr));
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gap: 0.5rem 1.25rem; padding: 0.6rem 0.75rem; background: var(--panel2);
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border: 1px solid var(--border); border-radius: 8px; margin-bottom: 0.75rem;
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font-size: 0.85rem;
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}
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.modal-summary div { display: flex; justify-content: space-between; gap: 0.5rem; }
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.modal-summary div strong { color: var(--accent); }
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.modal-charts { display: flex; flex-direction: column; gap: 0.6rem; }
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.modal-charts figure { margin: 0; background: var(--panel); border: 1px solid var(--border);
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border-radius: 8px; padding: 0.6rem 0.75rem 0.4rem; }
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.modal-charts figcaption { font-size: 0.78rem; color: var(--muted); margin-bottom: 0.3rem; }
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.modal-charts .chart { width: 100%; height: 110px; }
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.modal-charts figure:nth-child(3) .chart { height: 200px; } /* taller grid panel */
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/* uPlot dark-theme tweaks */
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.uplot { color: var(--text); }
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.uplot .u-legend { color: var(--text); font-size: 0.75rem; }
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.uplot .u-axis { color: var(--muted); }
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table#leaderboard tbody tr:hover { background: var(--panel2); }
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table#leaderboard tbody tr:hover { background: var(--panel2); }
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table#leaderboard tbody tr:first-child { background: rgba(74, 222, 128, 0.08); }
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table#leaderboard tbody tr:first-child { background: rgba(74, 222, 128, 0.08); }
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@ -4,7 +4,8 @@
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<meta charset="utf-8">
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>Honest battery payback — vs thuisbatterijgids.nl</title>
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<title>Honest battery payback — vs thuisbatterijgids.nl</title>
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<link rel="stylesheet" href="{{ url_for('static', filename='style.css') }}?v=14">
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/uplot@1.6.31/dist/uPlot.min.css">
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<link rel="stylesheet" href="{{ url_for('static', filename='style.css') }}?v=16">
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</head>
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</head>
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<body>
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<body>
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@ -155,6 +156,44 @@
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</p>
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</p>
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</footer>
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</footer>
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<script src="{{ url_for('static', filename='app.js') }}?v=14"></script>
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<script src="https://cdn.jsdelivr.net/npm/uplot@1.6.31/dist/uPlot.iife.min.js"></script>
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<script src="{{ url_for('static', filename='app.js') }}?v=16"></script>
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<div id="timeline-modal" class="modal" hidden>
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<div class="modal-backdrop" data-close="modal"></div>
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<div class="modal-card">
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<header>
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<h2 id="tl-title">Battery timeline</h2>
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<button class="modal-close" data-close="modal" aria-label="close">×</button>
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</header>
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<div class="modal-controls">
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<button id="tl-prev">◀ prev day</button>
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<input type="date" id="tl-date">
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<button id="tl-next">next day ▶</button>
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<select id="tl-days">
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<option value="1">1 day</option>
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<option value="3">3 days</option>
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<option value="7" selected>7 days</option>
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</select>
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<label class="filter-toggle"><input type="checkbox" id="tl-battery-on" checked> battery on</label>
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<span id="tl-status" class="status"></span>
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||||||
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</div>
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<div id="tl-summary" class="modal-summary"></div>
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<div class="modal-charts">
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<figure>
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<figcaption>Solar irradiance — proxy for sun (W/m², from our weather station, season-aligned)</figcaption>
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<div id="tl-chart-irradiance" class="chart"></div>
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</figure>
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<figure>
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<figcaption>Battery state of charge (kWh)</figcaption>
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<div id="tl-chart-soc" class="chart"></div>
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</figure>
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<figure>
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<figcaption>Net meter flow (kWh per hour). Positive = importing, negative = exporting.</figcaption>
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<div id="tl-chart-grid" class="chart"></div>
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||||||
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</figure>
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||||||
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</div>
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||||||
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</div>
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||||||
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</div>
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||||||
</body>
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</body>
|
||||||
</html>
|
</html>
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@ -180,9 +180,17 @@ def compute_leaderboard(
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avg_epex = float(df["epex_eur_per_kwh"].mean())
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avg_epex = float(df["epex_eur_per_kwh"].mean())
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store_params = StoreParams(avg_epex_eur_per_kwh=avg_epex)
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store_params = StoreParams(avg_epex_eur_per_kwh=avg_epex)
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||||||
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|
||||||
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# Annualisation factor: our data window may be shorter than a year (e.g.,
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||||||
|
# 8 months when solar coverage limits the overlap). Scale all per-window
|
||||||
|
# extensive quantities (savings, kWh shifted, captured, surplus) so they
|
||||||
|
# represent a full year. Intensive metrics like % full / % saturated stay
|
||||||
|
# as-is.
|
||||||
|
annualize = 8766.0 / len(df)
|
||||||
|
|
||||||
# Total PV / surplus available across the whole scenario (no battery).
|
# Total PV / surplus available across the whole scenario (no battery).
|
||||||
pv_col = df["pv_kwh"].to_numpy() if "pv_kwh" in df.columns else np.zeros(len(df))
|
pv_col = df["pv_kwh"].to_numpy() if "pv_kwh" in df.columns else np.zeros(len(df))
|
||||||
total_surplus_kwh = float(np.maximum(0.0, pv_col - df["demand_kwh"].to_numpy()).sum())
|
window_surplus = float(np.maximum(0.0, pv_col - df["demand_kwh"].to_numpy()).sum())
|
||||||
|
total_surplus_kwh = window_surplus * annualize
|
||||||
|
|
||||||
# Collect every distinct (capacity, power) the catalog asks for, then run
|
# Collect every distinct (capacity, power) the catalog asks for, then run
|
||||||
# the per-spec LPs in parallel. linprog/HiGHS release the GIL so threads
|
# the per-spec LPs in parallel. linprog/HiGHS release the GIL so threads
|
||||||
|
|
@ -238,11 +246,11 @@ def compute_leaderboard(
|
||||||
rows = []
|
rows = []
|
||||||
for b, cap, pw, price, allows_export in valid_rows:
|
for b, cap, pw, price, allows_export in valid_rows:
|
||||||
payload = lp_cache[(round(cap, 3), round(pw, 3), allows_export)]
|
payload = lp_cache[(round(cap, 3), round(pw, 3), allows_export)]
|
||||||
lp_year1 = payload["year1"]
|
lp_year1 = payload["year1"] * annualize
|
||||||
captured_kwh = payload["captured_kwh"]
|
captured_kwh = payload["captured_kwh"] * annualize
|
||||||
pct_full = payload["pct_full"]
|
pct_full = payload["pct_full"] # already a ratio
|
||||||
pct_saturated = payload["pct_saturated"]
|
pct_saturated = payload["pct_saturated"] # already a ratio
|
||||||
discharge_kwh = payload["discharge_kwh"]
|
discharge_kwh = payload["discharge_kwh"] * annualize
|
||||||
cycles_per_year = discharge_kwh / cap if cap > 0 else 0.0
|
cycles_per_year = discharge_kwh / cap if cap > 0 else 0.0
|
||||||
captured_pct = (captured_kwh / total_surplus_kwh * 100.0) if total_surplus_kwh > 0 else 0.0
|
captured_pct = (captured_kwh / total_surplus_kwh * 100.0) if total_surplus_kwh > 0 else 0.0
|
||||||
lp_payback = payback_years(lp_year1, price, inflation)
|
lp_payback = payback_years(lp_year1, price, inflation)
|
||||||
|
|
@ -313,10 +321,11 @@ def compute_leaderboard(
|
||||||
app = Flask(__name__)
|
app = Flask(__name__)
|
||||||
|
|
||||||
DEFAULTS = dict(
|
DEFAULTS = dict(
|
||||||
# Dad's actual: 2350 kWh/yr net (P1 data already nets his 3 kWp PV
|
# Window: 2025-01-01 → 2025-09-01 (8 months of dad's actual data with
|
||||||
# exports), retail €0.25, terugleveringskosten −€0.106/kWh.
|
# matching 2025 prices + solar). Net consumption over those 8 months
|
||||||
# Set pv_kwp = 0 because the 3 kWp solar is already inside the P1.
|
# is 1010 kWh; setting demand_kwh = 1010 gives scale factor 1.0 so the
|
||||||
demand_kwh=2350.0, retail=0.25, pv_kwp=0.0, pv_yield=875.0,
|
# P1 series passes through unscaled.
|
||||||
|
demand_kwh=1010.0, retail=0.25, pv_kwp=0.0, pv_yield=875.0,
|
||||||
fixed_rate=False, saldering=False, eta=0.88, inflation=0.03,
|
fixed_rate=False, saldering=False, eta=0.88, inflation=0.03,
|
||||||
export_rate=-0.106,
|
export_rate=-0.106,
|
||||||
)
|
)
|
||||||
|
|
@ -356,6 +365,99 @@ def calculate():
|
||||||
return jsonify(result)
|
return jsonify(result)
|
||||||
|
|
||||||
|
|
||||||
|
@app.route("/api/timeline")
|
||||||
|
def timeline():
|
||||||
|
"""Per-hour LP trajectory for a battery over a chosen window.
|
||||||
|
|
||||||
|
Returns both 'with battery' and 'without battery' series so the UI can
|
||||||
|
toggle between them without round-tripping. Defaults to a sunny mid-June
|
||||||
|
week.
|
||||||
|
"""
|
||||||
|
q = request.args
|
||||||
|
try:
|
||||||
|
cap = float(q.get("cap", "1.92"))
|
||||||
|
power = float(q.get("power", "0.8"))
|
||||||
|
allows_export = q.get("allows_export", "false").lower() == "true"
|
||||||
|
start_raw = q.get("start", "2025-06-15")
|
||||||
|
days = int(q.get("days", "7"))
|
||||||
|
|
||||||
|
demand_kwh = float(q.get("demand_kwh", DEFAULTS["demand_kwh"]))
|
||||||
|
retail = float(q.get("retail", DEFAULTS["retail"]))
|
||||||
|
pv_kwp = float(q.get("pv_kwp", DEFAULTS["pv_kwp"]))
|
||||||
|
pv_yield = float(q.get("pv_yield", DEFAULTS["pv_yield"]))
|
||||||
|
fixed_rate = q.get("fixed_rate", "false").lower() == "true"
|
||||||
|
saldering = q.get("saldering", "false").lower() == "true"
|
||||||
|
eta = float(q.get("eta", DEFAULTS["eta"]))
|
||||||
|
raw_export = q.get("export_rate")
|
||||||
|
if raw_export in (None, "", "null"):
|
||||||
|
export_rate = None
|
||||||
|
else:
|
||||||
|
export_rate = float(raw_export)
|
||||||
|
except (TypeError, ValueError) as e:
|
||||||
|
return jsonify({"error": f"bad query param: {e}"}), 400
|
||||||
|
|
||||||
|
df = _build_df(demand_kwh, retail, pv_kwp, pv_yield, fixed_rate, saldering, export_rate)
|
||||||
|
bat = Battery(
|
||||||
|
capacity_kwh=cap, max_charge_kw=power, max_discharge_kw=power,
|
||||||
|
round_trip_eff=eta, allows_export=allows_export,
|
||||||
|
)
|
||||||
|
out = simulate(df, bat, oracle_daily_schedule(df, bat))
|
||||||
|
|
||||||
|
import pandas as _pd
|
||||||
|
start_ts = _pd.Timestamp(start_raw, tz="UTC")
|
||||||
|
end_ts = start_ts + _pd.Timedelta(days=days)
|
||||||
|
win = out.loc[(out.index >= start_ts) & (out.index < end_ts)]
|
||||||
|
if win.empty:
|
||||||
|
return jsonify({"error": f"no data for {start_raw} + {days} days "
|
||||||
|
f"(window: {out.index[0].date()}..{out.index[-1].date()})"}), 400
|
||||||
|
|
||||||
|
g_no = (win["demand_kwh"] - win.get("pv_kwh", 0)).to_numpy()
|
||||||
|
g_yes = win["grid_kwh_with_battery"].to_numpy()
|
||||||
|
imp_p = win["eur_per_kwh"].to_numpy()
|
||||||
|
exp_p = win.get("export_eur_per_kwh", win["eur_per_kwh"]).to_numpy()
|
||||||
|
cost_no = np.where(g_no > 0, g_no * imp_p, g_no * exp_p)
|
||||||
|
cost_yes = np.where(g_yes > 0, g_yes * imp_p, g_yes * exp_p)
|
||||||
|
|
||||||
|
hours_payload = []
|
||||||
|
for i, (ts, r) in enumerate(win.iterrows()):
|
||||||
|
hours_payload.append({
|
||||||
|
"ts": ts.isoformat(),
|
||||||
|
"irradiance": float(r.get("irradiance_w_m2", 0.0)),
|
||||||
|
"price": float(r["eur_per_kwh"]),
|
||||||
|
"export_price": float(r.get("export_eur_per_kwh", r["eur_per_kwh"])),
|
||||||
|
"soc": float(r["soc_kwh"]),
|
||||||
|
"charge": float(r["charge_kwh"]),
|
||||||
|
"discharge": float(r["discharge_kwh"]),
|
||||||
|
"grid_no_bat": float(g_no[i]),
|
||||||
|
"grid_with_bat": float(g_yes[i]),
|
||||||
|
"cost_no_bat": float(cost_no[i]),
|
||||||
|
"cost_with_bat": float(cost_yes[i]),
|
||||||
|
})
|
||||||
|
|
||||||
|
return jsonify({
|
||||||
|
"battery": {"capacity_kwh": cap, "power_kw": power,
|
||||||
|
"allows_export": allows_export},
|
||||||
|
"scenario": {"demand_kwh": demand_kwh, "retail": retail,
|
||||||
|
"pv_kwp": pv_kwp, "saldering": saldering,
|
||||||
|
"fixed_rate": fixed_rate, "eta": eta,
|
||||||
|
"export_rate": export_rate},
|
||||||
|
"window": {"start": start_ts.isoformat(), "days": days,
|
||||||
|
"hours": len(hours_payload)},
|
||||||
|
"summary": {
|
||||||
|
"cost_no_battery_eur": float(cost_no.sum()),
|
||||||
|
"cost_with_battery_eur": float(cost_yes.sum()),
|
||||||
|
"savings_eur": float((cost_no - cost_yes).sum()),
|
||||||
|
"imports_no_bat": float(np.maximum(g_no, 0).sum()),
|
||||||
|
"imports_with_bat": float(np.maximum(g_yes, 0).sum()),
|
||||||
|
"exports_no_bat": float(-np.minimum(g_no, 0).sum()),
|
||||||
|
"exports_with_bat": float(-np.minimum(g_yes, 0).sum()),
|
||||||
|
"battery_charge_kwh": float(win["charge_kwh"].sum()),
|
||||||
|
"battery_discharge_kwh": float(win["discharge_kwh"].sum()),
|
||||||
|
},
|
||||||
|
"hours": hours_payload,
|
||||||
|
})
|
||||||
|
|
||||||
|
|
||||||
@app.route("/healthz")
|
@app.route("/healthz")
|
||||||
def healthz():
|
def healthz():
|
||||||
return {"ok": True, "rows": len(_BASE_DF), "catalog": len(_CATALOG)}
|
return {"ok": True, "rows": len(_BASE_DF), "catalog": len(_CATALOG)}
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue