diff --git a/openstef/validation/validation.py b/openstef/validation/validation.py
index a4c126ab0..867d06802 100644
--- a/openstef/validation/validation.py
+++ b/openstef/validation/validation.py
@@ -36,7 +36,6 @@ def validate(
     """
     logger = structlog.get_logger(__name__)
 
-    # Check if DataFrame has datetime index
     if not isinstance(data.index, pd.DatetimeIndex):
         raise ValueError("Input dataframe does not have a datetime index.")
 
@@ -261,6 +260,26 @@ def find_nonzero_flatliner(
     return interval_df
 
 
+def detect_ongoing_zero_flatliner(
+    load: pd.Series,
+    duration_threshold_hours: int,
+) -> bool:
+    """Detects if the latest measurements follow a zero flatliner pattern.
+
+    Args:
+        load (pd.Series): A timeseries of measured load with a datetime index.
+        duration_threshold_hours (int): A zero flatliner is only detected if it exceeds the threshold duration.
+
+    Returns:
+        bool: Indicating wether or not there is a zero flatliner ongoing for the given load.
+    """
+
+    latest_measurement_time = load.index.max()
+    latest_measurements = load[latest_measurement_time - timedelta(minutes=duration_threshold_hours * 60):].dropna()
+    
+    return ((latest_measurements == 0).all() & (not latest_measurements.empty))
+
+
 def find_zero_flatliner(
     df: pd.DataFrame,
     threshold: float,
diff --git a/test/unit/validation/test_validation_detect_ongoing_zero_flatliner.py b/test/unit/validation/test_validation_detect_ongoing_zero_flatliner.py
new file mode 100644
index 000000000..7b461ef7c
--- /dev/null
+++ b/test/unit/validation/test_validation_detect_ongoing_zero_flatliner.py
@@ -0,0 +1,92 @@
+from datetime import datetime, timedelta
+from test.unit.utils.base import BaseTestCase
+import numpy as np
+import pandas as pd
+
+from openstef.validation.validation import detect_ongoing_zero_flatliner
+
+now = datetime.utcnow()
+three_hour_range = pd.date_range(
+    start=now - timedelta(minutes=180), end=now, freq="0.25H"
+)
+
+
+class TestDetectOngoingZeroFlatliners(BaseTestCase):
+    def test_all_zero(self):
+        # Arrange
+        load = pd.Series(index=three_hour_range, data=[0 for i in range(13)])
+        duration_threshold = 2
+
+        # Act
+        zero_flatliner_ongoing = detect_ongoing_zero_flatliner(load, duration_threshold)
+
+        # Assert
+        assert zero_flatliner_ongoing == True
+
+    def test_all_nonzero(self):
+        # Arrange
+        load = pd.Series(index=three_hour_range, data=[i for i in range(1, 14)])
+        duration_threshold = 2
+
+        # Act
+        zero_flatliner_ongoing = detect_ongoing_zero_flatliner(load, duration_threshold)
+
+        # Assert
+        assert zero_flatliner_ongoing == False
+
+    def test_only_last_nonzero(self):
+        # Arrange
+        load = pd.Series(index=three_hour_range, data=[0 for i in range(1, 13)] + [1])
+        duration_threshold = 2
+
+        # Act
+        zero_flatliner_ongoing = detect_ongoing_zero_flatliner(load, duration_threshold)
+
+        # Assert
+        assert zero_flatliner_ongoing == False
+
+    def test_zero_flatliner_pattern_below_threshold(self):
+        # Arrange
+        load = pd.Series(
+            index=three_hour_range, data=[i for i in range(1, 10)] + [0, 0, 0, 0]
+        )
+        duration_threshold = 2
+
+        # Act
+        zero_flatliner_ongoing = detect_ongoing_zero_flatliner(load, duration_threshold)
+
+        # Assert
+        assert zero_flatliner_ongoing == False
+
+    def test_zero_flatliner_pattern_just_above_threshold(self):
+        # Arrange
+        load = pd.Series(index=three_hour_range, data=[1, 2, 3, 4] + [0 for i in range(9)])
+        duration_threshold = 2
+
+        # Act
+        zero_flatliner_ongoing = detect_ongoing_zero_flatliner(load, duration_threshold)
+
+        # Assert
+        assert zero_flatliner_ongoing == True
+
+    def test_zero_flatliner_and_missing_values(self):
+        # Arrange
+        load = pd.Series(index=three_hour_range, data=[1, 2, 3, 4] + [0, 0, 0, 0, np.nan, np.nan, np.nan, np.nan, 0])
+        duration_threshold = 2
+
+        # Act
+        zero_flatliner_ongoing = detect_ongoing_zero_flatliner(load, duration_threshold)
+
+        # Assert
+        assert zero_flatliner_ongoing == True
+
+    def test_all_missing_values(self):
+        # Arrange
+        load = pd.Series(index=three_hour_range, data=[np.nan for i in range(13)])
+        duration_threshold = 2
+
+        # Act
+        zero_flatliner_ongoing = detect_ongoing_zero_flatliner(load, duration_threshold)
+
+        # Assert
+        assert zero_flatliner_ongoing == False