feat(application): integrate measured-load ingestion training and planner source

services/netplan-v4/netplan_v4/forecast_quality.py

@@ -0,0 +1,21 @@
+"""Minimal validity gates, not a claim of forecast accuracy or model ranking."""
+from math import isfinite
+
+
+def assess_family(family, *, minimum_steps=3):
+    points=family.get('points',[])
+    if len(points)<minimum_steps:
+        return {'valid':False,'reason':'Forecast has too few intervals'}
+    loads=[]
+    for point in points:
+        for key in ('loadW','pvW'):
+            value=point.get(key)
+            if isinstance(value,bool) or not isinstance(value,(int,float)) or not isfinite(value) or value<0:
+                return {'valid':False,'reason':'Forecast contains missing or invalid power'}
+        loads.append(point['loadW'])
+    # A PV-only plant or confirmed shutdown may legitimately forecast zero load.
+    # It must be explicit; missing observations filled with zero are not savings.
+    if max(loads)==0 and family.get('zeroLoadConfirmed') is not True:
+        return {'valid':False,'reason':'Unconfirmed all-zero load forecast; likely missing data, not zero electricity costs'}
+    return {'valid':True,'reason':None,'loadMaximumW':max(loads),
+        'loadZeroFraction':sum(v==0 for v in loads)/len(loads)}