diff --git a/dao/prog/da_base.py b/dao/prog/da_base.py
index 5b8ee363..70ac02cd 100644
--- a/dao/prog/da_base.py
+++ b/dao/prog/da_base.py
@@ -649,7 +649,7 @@ def calc_solar_predictions(
             solar_prog["tijd"] = pd.to_datetime(solar_prog["date_time"])
             if interval == "15min":
                 solar_prog = interpolate(solar_prog, "prediction", quantity=True)
-            while solar_prog["tijd"].iloc[0].tz_localize(None) < vanaf:
+            while len(solar_prog)>0 and solar_prog["tijd"].iloc[0].tz_localize(None) < vanaf:
                 solar_prog = solar_prog.iloc[1:]
         else:
             solar_prog = pd.DataFrame(columns=["tijd", "prediction"])
diff --git a/dao/prog/da_report.py b/dao/prog/da_report.py
index b760a014..f7af995b 100644
--- a/dao/prog/da_report.py
+++ b/dao/prog/da_report.py
@@ -1326,7 +1326,7 @@ def get_datasoort(ds):
             if not isinstance(row.tijd, datetime.datetime):
                 print(row)
             if interval == "uur":
-                tijd_str = str(row.tijd)[10:14] + "00"
+                tijd_str = str(row.tijd)[0:14] + "00"
             elif interval == "dag":
                 tijd_str = str(row.tijd)[0:10]
             else:
diff --git a/dao/prog/day_ahead.py b/dao/prog/day_ahead.py
index 6c849118..4c840e57 100644
--- a/dao/prog/day_ahead.py
+++ b/dao/prog/day_ahead.py
@@ -577,7 +577,7 @@ def calc_optimum(
                 solar_series = prog_data[solar_name]
                 for u in range(U):
                     # pv_prod productie van batterij b van solar s in uur u, in kWh
-                    prod_dc = solar_series[u] * interval_fraction[u]
+                    prod_dc = max(0.0, solar_series[u]) * interval_fraction[u]
                     eff = 1
                     for ds in range(DS[b]):
                         if discharge_stages[b][ds]["power"] / 1000 > prod_dc:
@@ -1057,9 +1057,10 @@ def calc_optimum(
             )
             # 0.5 K/uur afkoeling per uur, omrekenen naar afkoeling per interval
             logging.info(f"Boiler hysterese {boiler_hysterese} K")
-            boiler_cooling = (
-                self.boiler_options["cooling rate"] * self.interval_s / 3600
+            cooling_rate = self.get_setting_state(
+                "cooling rate", self.boiler_options, "number", 0.5
             )
+            boiler_cooling = cooling_rate * self.interval_s / 3600
             # 45 oC grens daaronder kan worden verwarmd
             # boiler_bovengrens = self.boiler_options["heating allowed below"]
             boiler_bovengrens = float(
diff --git a/release-testing/CHANGELOG.md b/release-testing/CHANGELOG.md
index 0256b69d..ff8317af 100644
--- a/release-testing/CHANGELOG.md
+++ b/release-testing/CHANGELOG.md
@@ -1,5 +1,10 @@
 # Changelog 刀 DAO
 # Day Ahead Optimizer
+# 2026.02.2.rc3
+- Fixed error in reports and api with interval "vandaag en morgen"
+- Made boiler cooling_rate flex setting (feature request by @tomvandepoel3)
+- Fixed negative predictions pv_dc (reported by @Dogooder)
+
 # 2026.02.2.rc2
 No changes
 
diff --git a/release-testing/config.yaml b/release-testing/config.yaml
index 305b2580..b9279ebb 100644
--- a/release-testing/config.yaml
+++ b/release-testing/config.yaml
@@ -1,6 +1,6 @@
 ---
 name: 刀 Day Ahead Optimizer (TESTING)
-version: 2026.02.2.rc2
+version: 2026.02.2.rc3
 stage: experimental
 slug: day_ahead_opt-testing
 description: Beta version of DAO. Use only for testing!