diff --git a/opengrid/library/analysis.py b/opengrid/library/analysis.py
index daea53a..ff2dadb 100644
--- a/opengrid/library/analysis.py
+++ b/opengrid/library/analysis.py
@@ -105,3 +105,33 @@ def count_peaks(ts):
     result = on_toggles & shifted
     count = result.sum()
     return count
+
+
+def load_factor(ts, resolution=None, norm=None):
+    """
+    Calculate the ratio of input vs. norm over a given interval.
+
+    Parameters
+    ----------
+    ts : pandas.Series
+        timeseries
+    resolution : str, optional
+        interval over which to calculate the ratio
+        default: resolution of the input timeseries
+    norm : int | float, optional
+        denominator of the ratio
+        default: the maximum of the input timeseries
+
+    Returns
+    -------
+    pandas.Series
+    """
+    if norm is None:
+        norm = ts.max()
+
+    if resolution is not None:
+        ts = ts.resample(rule=resolution).mean()
+
+    lf = ts / norm
+
+    return lf
diff --git a/opengrid/tests/test_analyses.py b/opengrid/tests/test_analyses.py
index 4fc903e..e5568ba 100644
--- a/opengrid/tests/test_analyses.py
+++ b/opengrid/tests/test_analyses.py
@@ -28,6 +28,17 @@ def test_count_peaks(self):
         count = og.analysis.count_peaks(ts)
         self.assertEqual(count, 13)
 
+    def test_load_factor(self):
+        ts = og.datasets.get('electricity_2016_hour')
+        ts = ts['e1de'].truncate(after=pd.Timestamp('20160107'))
+        lf1 = og.analysis.load_factor(ts)
+        self.assertIsInstance(ts, pd.Series)
+        self.assertAlmostEqual(ts.iloc[0], (lf1 * ts.max()).iloc[0])
+
+        lf2 = og.analysis.load_factor(ts, resolution='3h', norm=800)
+        self.assertIsInstance(ts, pd.Series)
+        self.assertAlmostEqual(175.0345212009457, (lf2 * 800).iloc[0])
+
 
 if __name__ == '__main__':
     unittest.main()