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feat(pvforecast): add adaptive per-plane PV learning and diagnostics (#1422)
PV arrays with different orientations and curtailment need separate plant calibration and weather correction. This opt-in provider publishes normal EOS AC/DC forecast keys at 15-minute resolution. - Preserve daily per-plane energy/shape calibration and validated short-term local/trend selection. Curtailment-sensitive arrays require a fresh release flag or an explicitly configured learning guard. - Add switchable empirical solar-angle response relative to separate eligible reference arrays, removing their common weather error. This learns angular residuals, not physical angles or a measured geometric horizon. - Archive actually received weather model inputs, first local receipt and frozen per-member PV candidates. Returned past weather is excluded; unknown source issuance remains explicit. Learn model weights and forecast-regime bias separately at 2–6, 6–24 and 24–48 hours. - New long-horizon candidates remain in shadow until their genuinely issued outputs improve equal-day MAE by the configured margin, win on at least 60% of validation days and pass a matched-support energy-bias guard. Insufficient evidence retains calibration. Daily yields still require complete local days, including DST. - Expose fitted parameters, independent training/validation day counts, errors, selected methods and persistence in the existing status API, with additional normal prediction keys for Grafana. Retain physical DC through angular/weather corrections an enforce individual inverter AC limits. Co-authored-by: Normann <github@koldrack.com> Co-authored-by: Christin <chrissi@von-perbandt.de> Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com> Co-authored-by: YMT <yn276364@dal.ca> Co-authored-by: sarankumar1325 <120080287+sarankumar1325@users.noreply.github.com>
This commit is contained in:
Andreas
co-authored by
Normann
Christin
Claude Opus 5.5
YMT
sarankumar1325
Normann
Christin
Claude Opus 5.5
YMT
sarankumar1325
parent
298d46a527
commit
f804d48072
+770
-1
@@ -8,7 +8,7 @@
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"name": "Apache 2.0",
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"url": "https://www.apache.org/licenses/LICENSE-2.0.html"
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},
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"version": "v0.3.0.dev2610301534325811"
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"version": "v0.3.0.dev2611011668106370"
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},
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"paths": {
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"/v1/measurement/battery-capacity/{battery_id}": {
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@@ -330,6 +330,182 @@
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}
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}
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},
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"/v1/prediction/pv-adaptive/status": {
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"get": {
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"tags": [
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"prediction"
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],
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"summary": "Status",
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"description": "Status contains honest cold-start counts and matched per-lead error metrics.",
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"operationId": "status_v1_prediction_pv_adaptive_status_get",
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"additionalProperties": true,
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"type": "object",
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"title": "Response Status V1 Prediction Pv Adaptive Status Get"
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}
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}
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}
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}
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}
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}
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},
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"/v1/prediction/pv-adaptive/samples": {
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"put": {
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"tags": [
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"prediction"
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],
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"summary": "Samples",
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"description": "Store original power readings in the bounded adaptive archive, without zero filling.",
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"operationId": "samples_v1_prediction_pv_adaptive_samples_put",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"items": {
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"$ref": "#/components/schemas/MeasurementSample"
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},
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"type": "array",
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"maxItems": 10000,
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"title": "Values"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"additionalProperties": {
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"type": "integer"
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},
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"type": "object",
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"title": "Response Samples V1 Prediction Pv Adaptive Samples Put"
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}
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}
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}
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},
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"422": {
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"description": "Validation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/HTTPValidationError"
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}
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}
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}
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}
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}
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}
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},
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"/v1/prediction/pv-adaptive/comparisons": {
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"get": {
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"tags": [
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"prediction"
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],
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"summary": "Comparisons",
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"description": "Export genuinely issued forecasts with later measured truth, issuance and lead.",
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"operationId": "comparisons_v1_prediction_pv_adaptive_comparisons_get",
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"parameters": [
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{
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"name": "days",
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"in": "query",
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"required": false,
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"schema": {
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"type": "integer",
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"maximum": 30,
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"minimum": 1,
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"default": 2,
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"title": "Days"
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}
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},
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{
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"name": "limit",
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"in": "query",
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"required": false,
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"schema": {
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"type": "integer",
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"maximum": 20000,
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"minimum": 1,
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"default": 2000,
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"title": "Limit"
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}
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},
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{
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"name": "since_ms",
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"in": "query",
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"required": false,
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"schema": {
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"type": "integer",
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"minimum": 0,
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"default": 0,
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"title": "Since Ms"
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}
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}
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],
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"type": "array",
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"items": {
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"type": "object",
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"additionalProperties": true
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},
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"title": "Response Comparisons V1 Prediction Pv Adaptive Comparisons Get"
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}
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}
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}
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},
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"422": {
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"description": "Validation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/HTTPValidationError"
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}
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}
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}
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}
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}
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}
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},
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"/v1/prediction/pv-adaptive/latest": {
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"get": {
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"tags": [
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"prediction"
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],
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"summary": "Latest",
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"description": "Latest complete output curve; validation uses the separate immutable archive.",
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"operationId": "latest_v1_prediction_pv_adaptive_latest_get",
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"items": {
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"additionalProperties": true,
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"type": "object"
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},
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"type": "array",
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"title": "Response Latest V1 Prediction Pv Adaptive Latest Get"
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}
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}
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}
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}
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}
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}
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},
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"/v1/admin/cache/clear": {
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"post": {
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"tags": [
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@@ -14127,6 +14303,470 @@
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"title": "PPBCStartInterruptionInstruction",
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"description": "Represents an instruction to interrupt execution of a running power sequence.\n\nThis model defines a control instruction that interrupts the execution of an\nactive power sequence. It enables dynamic control over sequence execution,\nallowing temporary suspension of a sequence in response to changing system conditions\nor requirements, particularly for sequences marked as interruptible."
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},
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"PVForecastAdaptiveAkkudoktorCommonSettings": {
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"properties": {
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"backend": {
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"type": "string",
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"enum": [
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"remote",
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"local"
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],
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"title": "Backend",
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"default": "local"
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},
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"resolution_minutes": {
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"type": "integer",
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"title": "Resolution Minutes",
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"description": "Forecast resolution in minutes. 15 requests Open-Meteo's `minutely_15` block (natively resolved over Central Europe and North America, interpolated from hourly elsewhere); 60 requests the `hourly` block.",
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"default": 15,
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"examples": [
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15,
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60
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]
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},
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"forecast_days": {
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"anyOf": [
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{
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"type": "integer",
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"maximum": 16.0,
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"minimum": 1.0
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},
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{
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"type": "null"
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}
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],
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"title": "Forecast Days",
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"description": "Forecast horizon in days (1-16). Leave empty to derive it from `prediction.hours`, which is what keeps the optimizer's tail horizon fed.",
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"examples": [
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null,
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7
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]
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},
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"past_days": {
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"anyOf": [
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{
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"type": "integer",
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"maximum": 92.0,
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"minimum": 0.0
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},
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{
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"type": "null"
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}
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],
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"title": "Past Days",
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"description": "Days of past data to request (0-92). Leave empty to derive it from `prediction.historic_hours`.",
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"examples": [
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null,
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3
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]
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},
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"weather_models": {
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"items": {
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"type": "string"
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},
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"type": "array",
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"minItems": 1,
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"title": "Weather Models",
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"description": "Open-Meteo weather models to request. Listing more than one turns the input into a poor-man's ensemble: the members are averaged per variable, which is the cheapest reliable way to cut irradiance forecast error. Costs no extra API calls.",
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"default": [
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"best_match"
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],
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"examples": [
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[
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"best_match"
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],
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[
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"icon_seamless",
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"ecmwf_ifs025",
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"gfs_seamless"
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]
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]
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},
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"transposition_model": {
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"type": "string",
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"title": "Transposition Model",
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"description": "pvlib sky-diffuse transposition model: isotropic, klucher, haydavies, reindl, king or perez.",
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"default": "perez",
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"examples": [
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"perez",
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"haydavies"
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]
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},
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"albedo": {
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"type": "number",
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"maximum": 1.0,
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"minimum": 0.0,
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"title": "Albedo",
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"description": "Ground albedo used for planes that do not set their own.",
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"default": 0.25,
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"examples": [
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0.25,
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0.2
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]
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},
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"inverter_efficiency": {
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"type": "number",
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"maximum": 1.0,
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"exclusiveMinimum": 0.0,
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"title": "Inverter Efficiency",
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"description": "Nominal inverter efficiency (PVWatts eta_inv_nom).",
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"default": 0.96,
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"examples": [
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0.96,
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0.94
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]
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},
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"temperature_coefficient": {
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"type": "number",
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"title": "Temperature Coefficient",
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"description": "Module power temperature coefficient in %/degC (negative). Matches the `cellCoEff` the akkudoktor.net forecast uses.",
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"default": -0.36,
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"examples": [
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-0.36,
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-0.29
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]
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},
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"apply_iam": {
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"type": "boolean",
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"title": "Apply Iam",
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"description": "Apply the ASHRAE incidence-angle modifier to the beam component.",
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"default": true,
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"examples": [
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true
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]
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},
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"shift_to_interval_start": {
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"type": "boolean",
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"title": "Shift To Interval Start",
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"description": "Open-Meteo stamps an interval mean with the interval END. EOS labels an interval by its START, so records are shifted back by one interval. Disable only to compare like-for-like against a provider that does not.",
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"default": true,
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"examples": [
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true
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]
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},
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"calibration_enabled": {
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"type": "boolean",
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"title": "Calibration Enabled",
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"default": false
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},
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"calibration_days": {
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"type": "integer",
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"maximum": 92.0,
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"minimum": 1.0,
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"title": "Calibration Days",
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"description": "Length of the measurement window used to fit the correction.",
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"default": 30,
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"examples": [
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30,
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14
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]
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},
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"calibration_reference_days": {
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"type": "integer",
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"maximum": 92.0,
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"minimum": 3.0,
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"title": "Calibration Reference Days",
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"description": "Lookback used to distinguish healthy production from outages or curtailment. If the calibration window contains too few healthy days, the most recent healthy days from this reference window are used.",
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"default": 30,
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"examples": [
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30,
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14
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]
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},
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"calibration_outage_filter_enabled": {
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"type": "boolean",
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"title": "Calibration Outage Filter Enabled",
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"description": "Exclude days whose measured production is far below the recent healthy plant level. This prevents inverter, battery and curtailment events from being learned as permanent PV model losses.",
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"default": true,
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"examples": [
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true
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]
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},
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"calibration_outage_threshold": {
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"type": "number",
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"exclusiveMaximum": 1.0,
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"exclusiveMinimum": 0.0,
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"title": "Calibration Outage Threshold",
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"description": "A day is treated as unavailable when its measured/modelled energy ratio is below this fraction of the robust healthy reference ratio.",
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"default": 0.55,
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"examples": [
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0.55,
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0.5
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]
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},
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"calibration_min_healthy_days": {
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"type": "integer",
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"maximum": 31.0,
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"minimum": 1.0,
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"title": "Calibration Min Healthy Days",
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"description": "Minimum number of healthy days used for a fit. Older healthy days from the reference window are added when the recent window contains fewer.",
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"default": 3,
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"examples": [
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3
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]
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},
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"calibration_azimuth_bin_degrees": {
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"type": "integer",
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"maximum": 180.0,
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"minimum": 0.0,
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"title": "Calibration Azimuth Bin Degrees",
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"description": "Width of the solar-azimuth bins for the correction. 0 fits a single global factor only.",
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"default": 45,
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"examples": [
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45,
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30,
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15,
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0
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]
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},
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"calibration_prior_kwh": {
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"type": "number",
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"minimum": 0.0,
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"title": "Calibration Prior Kwh",
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"description": "Shrinkage strength: a bin needs this much modelled energy before its own factor outweighs the global one. Higher is more conservative.",
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"default": 5.0,
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"examples": [
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5.0,
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20.0
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]
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},
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"calibration_min_factor": {
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"type": "number",
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"exclusiveMinimum": 0.0,
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"title": "Calibration Min Factor",
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"description": "Lower clamp on any fitted correction factor.",
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"default": 0.5,
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"examples": [
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0.5
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]
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},
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"calibration_max_factor": {
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"type": "number",
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"exclusiveMinimum": 0.0,
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"title": "Calibration Max Factor",
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"description": "Upper clamp on any fitted correction factor.",
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"default": 1.5,
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"examples": [
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1.5
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]
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},
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"regional_weather_model": {
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"anyOf": [
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{
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"type": "string"
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},
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{
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"type": "null"
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}
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],
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"title": "Regional Weather Model",
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"default": "icon_d2"
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},
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"regional_horizon_hours": {
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"type": "number",
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"maximum": 48.0,
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"exclusiveMinimum": 0.0,
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"title": "Regional Horizon Hours",
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"default": 6
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},
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"learning_days": {
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"type": "integer",
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"maximum": 30.0,
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"minimum": 7.0,
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"title": "Learning Days",
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"default": 21
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},
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"min_training_days": {
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"type": "integer",
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"maximum": 14.0,
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"minimum": 2.0,
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"title": "Min Training Days",
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"default": 5
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},
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"max_ac_power_w": {
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"type": "number",
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"minimum": 0.0,
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"title": "Max Ac Power W",
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"default": 0
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},
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"nominal_total_peakpower_kw": {
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"anyOf": [
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{
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"type": "number",
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"exclusiveMinimum": 0.0
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},
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{
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"type": "null"
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}
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],
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"title": "Nominal Total Peakpower Kw",
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"description": "Known installed nameplate total; fitted plane powers may be effective estimates.",
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"examples": [
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null
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]
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},
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"diagnostics_days": {
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"type": "integer",
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"maximum": 30.0,
|
||||
"minimum": 1.0,
|
||||
"title": "Diagnostics Days",
|
||||
"default": 7
|
||||
},
|
||||
"archive_retention_days": {
|
||||
"type": "integer",
|
||||
"maximum": 365.0,
|
||||
"minimum": 31.0,
|
||||
"title": "Archive Retention Days",
|
||||
"default": 60
|
||||
},
|
||||
"nowcast_enabled": {
|
||||
"type": "boolean",
|
||||
"title": "Nowcast Enabled",
|
||||
"default": true
|
||||
},
|
||||
"trend_enabled": {
|
||||
"type": "boolean",
|
||||
"title": "Trend Enabled",
|
||||
"default": true
|
||||
},
|
||||
"solar_response_enabled": {
|
||||
"type": "boolean",
|
||||
"title": "Solar Response Enabled",
|
||||
"description": "Learn empirical angular response relative to separate, eligible reference arrays; activate only after issued-candidate validation.",
|
||||
"default": true
|
||||
},
|
||||
"weather_response_enabled": {
|
||||
"type": "boolean",
|
||||
"title": "Weather Response Enabled",
|
||||
"description": "Archive received model weather and learn horizon/regime corrections; activate only after issued-candidate validation.",
|
||||
"default": true
|
||||
},
|
||||
"correction_mode": {
|
||||
"type": "string",
|
||||
"enum": [
|
||||
"auto",
|
||||
"calibrated",
|
||||
"local",
|
||||
"trend"
|
||||
],
|
||||
"title": "Correction Mode",
|
||||
"description": "Choose validated short-term candidates per group/lead, or explicitly fix a correction stage.",
|
||||
"default": "auto"
|
||||
},
|
||||
"validation_days": {
|
||||
"type": "integer",
|
||||
"maximum": 30.0,
|
||||
"minimum": 3.0,
|
||||
"title": "Validation Days",
|
||||
"default": 7
|
||||
},
|
||||
"min_validation_days": {
|
||||
"type": "integer",
|
||||
"maximum": 14.0,
|
||||
"minimum": 2.0,
|
||||
"title": "Min Validation Days",
|
||||
"default": 3
|
||||
},
|
||||
"min_validation_samples": {
|
||||
"type": "integer",
|
||||
"minimum": 8.0,
|
||||
"title": "Min Validation Samples",
|
||||
"default": 32
|
||||
},
|
||||
"min_validation_improvement": {
|
||||
"type": "number",
|
||||
"maximum": 0.5,
|
||||
"minimum": 0.0,
|
||||
"title": "Min Validation Improvement",
|
||||
"default": 0.02
|
||||
},
|
||||
"training_delay_minutes": {
|
||||
"type": "integer",
|
||||
"maximum": 120.0,
|
||||
"minimum": 0.0,
|
||||
"title": "Training Delay Minutes",
|
||||
"default": 15
|
||||
},
|
||||
"total_measurement_key": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"maxLength": 128,
|
||||
"minLength": 1
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Total Measurement Key",
|
||||
"description": "Optional whole-plant power channel when individual plane measurements are unavailable.",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"total_curtailment_sensitive": {
|
||||
"type": "boolean",
|
||||
"title": "Total Curtailment Sensitive",
|
||||
"default": false
|
||||
},
|
||||
"total_curtailment_key": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"maxLength": 128,
|
||||
"minLength": 1
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Total Curtailment Key",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"total_learning_guard_key": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"maxLength": 128,
|
||||
"minLength": 1
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Total Learning Guard Key",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"total_learning_guard_max": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "number"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Total Learning Guard Max",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"total_learning_guard_max_gap_seconds": {
|
||||
"type": "integer",
|
||||
"maximum": 3600.0,
|
||||
"minimum": 1.0,
|
||||
"title": "Total Learning Guard Max Gap Seconds",
|
||||
"default": 600
|
||||
}
|
||||
},
|
||||
"type": "object",
|
||||
"title": "PVForecastAdaptiveAkkudoktorCommonSettings",
|
||||
"description": "Automatic defaults; configure measurements and reference flags on each plane."
|
||||
},
|
||||
"PVForecastAkkudoktorLocalCommonSettings": {
|
||||
"properties": {
|
||||
"backend": {
|
||||
@@ -14409,6 +15049,10 @@
|
||||
"$ref": "#/components/schemas/PVForecastAkkudoktorLocalCommonSettings",
|
||||
"description": "Akkudoktor forecast backend and local calibration settings"
|
||||
},
|
||||
"adaptive": {
|
||||
"$ref": "#/components/schemas/PVForecastAdaptiveAkkudoktorCommonSettings",
|
||||
"description": "Adaptive Akkudoktor: configure string measurements and independent reference flags on the planes."
|
||||
},
|
||||
"pvforecastimport": {
|
||||
"$ref": "#/components/schemas/PVForecastImportCommonSettings",
|
||||
"description": "PV forecast import provider settings"
|
||||
@@ -14538,6 +15182,10 @@
|
||||
"$ref": "#/components/schemas/PVForecastAkkudoktorLocalCommonSettings",
|
||||
"description": "Akkudoktor forecast backend and local calibration settings"
|
||||
},
|
||||
"adaptive": {
|
||||
"$ref": "#/components/schemas/PVForecastAdaptiveAkkudoktorCommonSettings",
|
||||
"description": "Adaptive Akkudoktor: configure string measurements and independent reference flags on the planes."
|
||||
},
|
||||
"pvforecastimport": {
|
||||
"$ref": "#/components/schemas/PVForecastImportCommonSettings",
|
||||
"description": "PV forecast import provider settings"
|
||||
@@ -14902,6 +15550,127 @@
|
||||
},
|
||||
"PVForecastPlaneSetting": {
|
||||
"properties": {
|
||||
"name": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Name",
|
||||
"description": "Readable PV string name.",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"measurement_key": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Measurement Key",
|
||||
"description": "Matching EOS power measurement key for adaptive learning.",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"nowcast_reference": {
|
||||
"type": "boolean",
|
||||
"title": "Nowcast Reference",
|
||||
"description": "Use this independent array as a local weather reference.",
|
||||
"default": false
|
||||
},
|
||||
"curtailment_sensitive": {
|
||||
"type": "boolean",
|
||||
"title": "Curtailment Sensitive",
|
||||
"description": "Battery-full curtailment possible; exclude from unrestricted weather learning.",
|
||||
"default": false
|
||||
},
|
||||
"parameters_estimated": {
|
||||
"type": "boolean",
|
||||
"title": "Parameters Estimated",
|
||||
"description": "Geometry and peak power are effective fitted model estimates, not verified nameplate data.",
|
||||
"default": false
|
||||
},
|
||||
"correction_group": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"maxLength": 128,
|
||||
"minLength": 1
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Correction Group",
|
||||
"description": "Optional group of planes sharing short-term validation. Unset independent references share one group; other planes are separate.",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"curtailment_key": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"maxLength": 128,
|
||||
"minLength": 1
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Curtailment Key",
|
||||
"description": "Optional measured flag: 0 explicitly unrestricted, 1 curtailed. Missing or stale flags never authorize learning a curtailment-sensitive plane.",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"learning_guard_key": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "string",
|
||||
"maxLength": 128,
|
||||
"minLength": 1
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Learning Guard Key",
|
||||
"description": "Optional site-specific positive learning guard, e.g. battery SoC, as an alternative to a binary curtailment flag.",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"learning_guard_max": {
|
||||
"anyOf": [
|
||||
{
|
||||
"type": "number"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"title": "Learning Guard Max",
|
||||
"description": "Learn only while every supported guard value is below this bound. This is an explicit site assumption, not automatic curtailment detection.",
|
||||
"examples": [
|
||||
null
|
||||
]
|
||||
},
|
||||
"learning_guard_max_gap_seconds": {
|
||||
"type": "integer",
|
||||
"maximum": 3600.0,
|
||||
"minimum": 1.0,
|
||||
"title": "Learning Guard Max Gap Seconds",
|
||||
"default": 600
|
||||
},
|
||||
"surface_tilt": {
|
||||
"anyOf": [
|
||||
{
|
||||
|
||||
Reference in New Issue
Block a user