Fix/resample to instantaneous for scheduling

documentation/changelog.rst

@@ -23,6 +23,7 @@ v0.31.1 | March 6, 2026
 
 Bugfixes
 -----------
+* Fix bug with resampling time series of e.g. SoC minima with different belief times for adjacent time slots [see `PR #2012 <https://www.github.com/FlexMeasures/flexmeasures/pull/2012>`_]
 * Fix CLI command ``flexmeasures add forecasts`` [see `PR #2007 <https://www.github.com/FlexMeasures/flexmeasures/pull/2007>`_]
 * Add missing field documentation for ``aggregate-power`` and ``state-of-charge`` fields, which can be used to reference a sensor on which to record extra scheduling results [see `PR #2003 <https://www.github.com/FlexMeasures/flexmeasures/pull/2003>`_ and `PR #2006 <https://www.github.com/FlexMeasures/flexmeasures/pull/2006>`_]
 

flexmeasures/data/models/planning/utils.py

@@ -344,7 +344,11 @@ def get_series_from_quantity_or_sensor(
             one_deterministic_belief_per_event=True,
         )
         if as_instantaneous_events:
-            bdf = bdf.resample_events(timedelta(0), boundary_policy=resolve_overlaps)
+            bdf = bdf.resample_events(
+                timedelta(0),
+                boundary_policy=resolve_overlaps,
+                keep_only_most_recent_belief=True,
+            )
         time_series = simplify_index(bdf).reindex(index).squeeze(axis=1)
         time_series = convert_units(
             time_series, variable_quantity.unit, unit, resolution

requirements/3.10/app.txt

@@ -442,7 +442,7 @@ tabulate==0.9.0
     # via -r requirements/app.in
 threadpoolctl==3.6.0
     # via scikit-learn
-timely-beliefs[forecast]==3.5.1
+timely-beliefs[forecast]==3.5.2
     # via -r requirements/app.in
 timetomodel==0.7.3
     # via -r requirements/app.in

requirements/3.11/app.txt

@@ -439,7 +439,7 @@ tabulate==0.9.0
     # via -r requirements/app.in
 threadpoolctl==3.6.0
     # via scikit-learn
-timely-beliefs[forecast]==3.5.1
+timely-beliefs[forecast]==3.5.2
     # via -r requirements/app.in
 timetomodel==0.7.3
     # via -r requirements/app.in

requirements/3.12/app.txt

@@ -439,7 +439,7 @@ tabulate==0.9.0
     # via -r requirements/app.in
 threadpoolctl==3.6.0
     # via scikit-learn
-timely-beliefs[forecast]==3.5.1
+timely-beliefs[forecast]==3.5.2
     # via -r requirements/app.in
 timetomodel==0.7.3
     # via -r requirements/app.in

requirements/app.in

@@ -31,8 +31,8 @@ tldextract
 pyomo>=5.6,<6.9
 tabulate
 timetomodel>=0.7.3
-# 3.5.1: fixed issue with downsampling against non-midnight origins
-timely-beliefs[forecast]>=3.5.1
+# 3.5.2: fixed issue with resampling to instantaneous
+timely-beliefs[forecast]>=3.5.2
 python-dotenv
 # a backport, not needed in Python3.8
 importlib_metadata