diff --git a/src/antares/tsgen/ts_generator.py b/src/antares/tsgen/ts_generator.py
index 379710a..36eb4ad 100644
--- a/src/antares/tsgen/ts_generator.py
+++ b/src/antares/tsgen/ts_generator.py
@@ -91,7 +91,7 @@ def _check_cluster(cluster: ThermalCluster) -> None:
     _check_array(cluster.fo_duration < 0, "Forced outage duration is negative on following days")
     _check_array(cluster.po_rate < 0, "Planned failure rate is negative on following days")
     _check_array(cluster.po_rate > 1, "Planned failure rate is greater than 1 on following days")
-    _check_array(cluster.po_duration < 0, "Planned outage duration is negative on following days")
+    _check_array(cluster.po_duration <= 0, "Planned outage duration is null or negative on following days")
     _check_array(cluster.modulation < 0, "Hourly modulation is negative on following hours")
 
     lengths = {
diff --git a/tests/test_unit.py b/tests/test_unit.py
index 6bee9a9..7b3c7b5 100644
--- a/tests/test_unit.py
+++ b/tests/test_unit.py
@@ -62,24 +62,22 @@ def base_cluster_365_days():
 
 def test_ts_gen_with_matrix_full_of_zeros(rng):
     days = 365
-    cluster = ThermalCluster(
-        unit_count=10,
-        nominal_power=100,
-        modulation=np.ones(dtype=float, shape=8760),
-        fo_law=ProbabilityLaw.UNIFORM,
-        fo_volatility=0,
-        po_law=ProbabilityLaw.UNIFORM,
-        po_volatility=0,
-        fo_duration=10 * np.zeros(dtype=int, shape=days),
-        fo_rate=0.2 * np.zeros(dtype=float, shape=days),
-        po_duration=10 * np.zeros(dtype=int, shape=days),
-        po_rate=np.zeros(dtype=float, shape=days),
-        npo_min=np.zeros(dtype=int, shape=days),
-        npo_max=10 * np.zeros(dtype=int, shape=days),
-    )
-    generator = ThermalDataGenerator(rng=rng, days=days)
-    # asserts the method _compute_failure_rates doesn't return NaN values which led to the generation failing.
-    generator.generate_time_series(cluster, 1)
+    with pytest.raises(ValueError, match="Planned outage duration is null or negative on following days"):
+        ThermalCluster(
+            unit_count=10,
+            nominal_power=100,
+            modulation=np.ones(dtype=float, shape=8760),
+            fo_law=ProbabilityLaw.UNIFORM,
+            fo_volatility=0,
+            po_law=ProbabilityLaw.UNIFORM,
+            po_volatility=0,
+            fo_duration=10 * np.zeros(dtype=int, shape=days),
+            fo_rate=0.2 * np.zeros(dtype=float, shape=days),
+            po_duration=10 * np.zeros(dtype=int, shape=days),
+            po_rate=np.zeros(dtype=float, shape=days),
+            npo_min=np.zeros(dtype=int, shape=days),
+            npo_max=10 * np.zeros(dtype=int, shape=days),
+        )
 
 
 def test_invalid_fo_rates(rng, base_cluster_365_days):