diff --git a/docs/api.rst b/docs/api.rst
index 78d482fa..142d3734 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -7,6 +7,27 @@ API Reference
 Quality
 =======
 
+Energy
+-----------
+
+Functions for checking if an energy data stream is cumulative
+or not.
+
+.. autosummary::
+   :toctree: generated/
+
+   quality.energy.cumulative_energy_simple_diff_check
+   quality.energy.cumulative_energy_avg_diff_check
+
+If the energy data stream passes the checks, then 
+it is converted to non-cumulative energy data stream via simple or
+average differencing
+
+.. autosummary::
+   :toctree: generated/
+
+   quality.energy.convert_cumulative_energy
+
 Data Shifts
 -----------
 
diff --git a/docs/examples/energy/README.rst b/docs/examples/energy/README.rst
new file mode 100644
index 00000000..9ff7b975
--- /dev/null
+++ b/docs/examples/energy/README.rst
@@ -0,0 +1,4 @@
+Energy
+----------------
+
+This includes examples for identifying and correcting cumulative energy time series.
\ No newline at end of file
diff --git a/docs/examples/energy/cumulative-energy-simple-avg-check.py b/docs/examples/energy/cumulative-energy-simple-avg-check.py
new file mode 100644
index 00000000..8ae1ae93
--- /dev/null
+++ b/docs/examples/energy/cumulative-energy-simple-avg-check.py
@@ -0,0 +1,72 @@
+"""
+Cumulative Energy via Average Difference
+=======================================
+
+Check and correct energy series for cumulative energy via average differencing.
+"""
+
+# %%
+# AC energy data streams are often cumulative, meaning they increase
+# over time. These energy streams need to be corrected into a form
+# that resembles regular, non-cumulative data. This process involves
+# applying a percent threshold to the average difference in subsequent values
+# to check if the data is always increasing. If it passes,
+# that check, then the data stream is cumulative and it can be corrected
+# via average differencing.
+
+import pandas as pd
+import matplotlib.pyplot as plt
+from pvanalytics.quality import energy
+import pathlib
+import pvanalytics
+
+# %%
+# First, read in the ac energy data. This data set contains one week of
+# 10-minute ac energy data.
+
+pvanalytics_dir = pathlib.Path(pvanalytics.__file__).parent
+energy_file = pvanalytics_dir / 'data' / 'system_10004_ac_energy.csv'
+data = pd.read_csv(energy_file)
+energy_series = data['ac_energy_inv_16425']
+
+# %%
+# Now check if the energy time series is cumulative via average differencing.
+# This is done using the
+# :py:func:`pvanalytics.quality.energy.cumulative_energy_avg_diff_check`
+# function.
+
+is_cumulative = energy.cumulative_energy_avg_diff_check(energy_series)
+
+# %%
+# If the energy series is cumulative,, then it can be converted to
+# non-cumulative energy series via average differencing.
+corrected_energy_series = 0.5 * \
+    (energy_series.diff().shift(-1) + energy_series.diff())
+
+# %%
+# Plot the original, cumulative energy series.
+
+data.plot(x="local_measured_on", y='ac_energy_inv_16425')
+plt.title("Cumulative Energy Series")
+plt.xticks(rotation=45)
+plt.xlabel("Datetime")
+plt.ylabel("AC Energy (kWh)")
+plt.tight_layout()
+plt.show()
+
+# %%
+# Plot the corrected, non-cumulative energy series.
+
+corrected_energy_df = pd.DataFrame({
+    "local_measured_on": data["local_measured_on"],
+    "corrected_ac_energy_inv_16425": corrected_energy_series})
+corrected_energy_df = corrected_energy_df[
+    corrected_energy_df["corrected_ac_energy_inv_16425"] >= 0]
+corrected_energy_df.plot(x="local_measured_on",
+                         y="corrected_ac_energy_inv_16425")
+plt.title("Corrected, Non-cumulative Energy Series")
+plt.xticks(rotation=45)
+plt.xlabel("Datetime")
+plt.ylabel("AC Energy (kWh)")
+plt.tight_layout()
+plt.show()
diff --git a/docs/examples/energy/cumulative-energy-simple-diff-check.py b/docs/examples/energy/cumulative-energy-simple-diff-check.py
new file mode 100644
index 00000000..6f4eb463
--- /dev/null
+++ b/docs/examples/energy/cumulative-energy-simple-diff-check.py
@@ -0,0 +1,72 @@
+"""
+Cumulative Energy via Simple Difference
+=======================================
+
+Check and correct energy series for cumulative energy with simple differencing.
+"""
+
+# %%
+# AC energy data streams are often cumulative, meaning they increase
+# over time. These energy streams need to be corrected into a form
+# that resembles regular, non-cumulative data. This process involves
+# applying a percent threshold to the difference in subsequent values
+# to check if the data is always increasing. If it passes,
+# that check, then the data stream is cumulative and it can be corrected
+# via simple differencing.
+
+import pandas as pd
+import matplotlib.pyplot as plt
+from pvanalytics.quality import energy
+import pathlib
+import pvanalytics
+
+# %%
+# First, read in the ac energy data. This data set contains one week of
+# 10-minute ac energy data.
+
+pvanalytics_dir = pathlib.Path(pvanalytics.__file__).parent
+energy_file = pvanalytics_dir / 'data' / 'system_10004_ac_energy.csv'
+data = pd.read_csv(energy_file)
+energy_series = data['ac_energy_inv_16425']
+
+# %%
+# Now check if the energy time series is cumulative via simple differencing.
+# This is done using the
+# :py:func:`pvanalytics.quality.energy.cumulative_energy_simple_diff_check`
+# function.
+
+is_cumulative = energy.cumulative_energy_simple_diff_check(energy_series)
+
+# %%
+# If the energy series is cumulative, then it can be converted
+# to the non-cumulative energy series. This is done using the
+# :py:func:`pvanalytics.quality.energy.convert_cumulative_energy` function.
+corrected_energy_series = energy.convert_cumulative_energy(energy_series)
+
+# %%
+# Plot the original, cumulative energy series.
+
+data.plot(x="local_measured_on", y='ac_energy_inv_16425')
+plt.title("Cumulative Energy Series")
+plt.xticks(rotation=45)
+plt.xlabel("Datetime")
+plt.ylabel("AC Energy (kWh)")
+plt.tight_layout()
+plt.show()
+
+# %%
+# Plot the corrected, non-cumulative energy series.
+
+corrected_energy_df = pd.DataFrame({
+    "local_measured_on": data["local_measured_on"],
+    "corrected_ac_energy_inv_16425": corrected_energy_series})
+corrected_energy_df = corrected_energy_df[
+    corrected_energy_df["corrected_ac_energy_inv_16425"] >= 0]
+corrected_energy_df.plot(x="local_measured_on",
+                         y="corrected_ac_energy_inv_16425")
+plt.title("Corrected, Non-cumulative Energy Series")
+plt.xticks(rotation=45)
+plt.xlabel("Datetime")
+plt.ylabel("AC Energy (kWh)")
+plt.tight_layout()
+plt.show()
diff --git a/docs/whatsnew/0.2.1.rst b/docs/whatsnew/0.2.1.rst
index b54d3aef..462eddce 100644
--- a/docs/whatsnew/0.2.1.rst
+++ b/docs/whatsnew/0.2.1.rst
@@ -7,6 +7,17 @@
 Enhancements
 ~~~~~~~~~~~~
 * Compatibility with numpy 2.0. (:pull:`211`)
+* Added function :py:func:`~pvanalytics.quality.energy.cumulative_energy_simple_diff_check` to
+  check if an energy time series is cumulative via simple differencing.
+  (:issue:`165`, :pull:`212`)
+* Added function :py:func:`~pvanalytics.quality.energy.cumulative_energy_avg_diff_check` to
+  check if an energy time series is cumulative via average differencing.
+  (:issue:`165`, :pull:`212`)
+* Added function :py:func:`~pvanalytics.quality.energy.convert_cumulative_energy` to correct
+  the cumulative energy to interval-based, non-cumulative energy series, if the energy series
+  passes the simple difference :py:func:`~pvanalytics.quality.energy.cumulative_energy_simple_diff_check`
+  or average difference :py:func:`~pvanalytics.quality.energy.cumulative_energy_avg_diff_check`
+  checks. (:issue:`165`, :pull:`212`)
 
 
 Bug Fixes
@@ -20,12 +31,13 @@ Requirements
 
 Documentation
 ~~~~~~~~~~~~~
-
+* Added examples for checking cumulative energy time series. (:issue:`165`, :pull:`212`)
 
 Testing
 ~~~~~~~
-
+* Added testing for ``pvanalytics.quality.energy``. (:issue:`165`, :pull:`212`)
 
 
 Contributors
 ~~~~~~~~~~~~
+* Quyen Nguyen (:ghuser:`qnguyen345`)
\ No newline at end of file
diff --git a/pvanalytics/data/system_10004_ac_energy.csv b/pvanalytics/data/system_10004_ac_energy.csv
new file mode 100644
index 00000000..7f53709a
--- /dev/null
+++ b/pvanalytics/data/system_10004_ac_energy.csv
@@ -0,0 +1,1151 @@
+utc_measured_on,ac_energy_inv_16425,local_measured_on
+2011-06-23 10:00:00,6.0,2011-06-23 06:00:00
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+2011-06-29 13:55:00,9881.0,2011-06-29 09:55:00
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+2011-06-29 14:05:00,10794.0,2011-06-29 10:05:00
+2011-06-29 14:10:00,11258.0,2011-06-29 10:10:00
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+2011-06-30 09:45:00,0.0,2011-06-30 05:45:00
+2011-06-30 09:50:00,1.0,2011-06-30 05:50:00
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+2011-06-30 10:00:00,9.0,2011-06-30 06:00:00
diff --git a/pvanalytics/quality/energy.py b/pvanalytics/quality/energy.py
new file mode 100644
index 00000000..73678885
--- /dev/null
+++ b/pvanalytics/quality/energy.py
@@ -0,0 +1,147 @@
+"""Quality control functions for energy data."""
+import warnings
+
+
+def cumulative_energy_simple_diff_check(energy_series,
+                                        pct_increase_threshold=95,
+                                        system_self_consumption=-0.5):
+    """Check if an energy time series is cumulative via simple differencing.
+
+    To determine if an energy data stream is cumulative, subsequent values in
+    the series are differenced to determine if the data stream is consistently
+    increasing. If the percentage of increasing values in the data set exceeds
+    the pct_increase_threshold parameter, the energy series is determined as
+    cumulative and a True boolean is returned. Otherwise, False is returned.
+
+    Parameters
+    ----------
+    energy_series: Series
+        Time series of energy data stream with datetime index.
+    pct_increase_threshold: Int, default 95
+        The percentage threshold to consider the energy series as cumulative.
+    system_self_consumption: Float, default -0.5
+        The difference threshold to account for the effect of nighttime system
+        self-consumption on the energy data stream.
+
+    Returns
+    -------
+    Boolean
+        True if energy_series is cumulative, False otherwise.
+    """
+    # Simple diff function
+    differenced_series = energy_series.diff().dropna()
+    if len(differenced_series) == 0:
+        warnings.warn(
+            "The energy time series has a length of zero and cannot be run.")
+        return False
+    else:
+        # If over X percent of the data is increasing (set via the
+        # pct_increase_threshold), then assume that the column is cumulative
+        differenced_series_positive_mask = (
+            differenced_series >= system_self_consumption)
+        pct_over_zero = differenced_series_positive_mask.value_counts(
+            normalize=True) * 100
+        if pct_over_zero[True] >= pct_increase_threshold:
+            return True
+        else:
+            return False
+
+
+def cumulative_energy_avg_diff_check(energy_series,
+                                     pct_increase_threshold=95,
+                                     system_self_consumption=-0.5):
+    """Check if an energy time series is cumulative via average differencing.
+
+    To determine if an energy data stream is cumulative, subsequent values in
+    the series are average differenced to determine if the data stream is
+    consistently increasing. If the percentage of increasing values in the
+    data set exceeds the pct_increase_threshold parameter, the energy series
+    is determined as cumulative and a True boolean is returned.
+    Otherwise, False is returned.
+
+    Parameters
+    ----------
+    energy_series: Series
+        Time series of energy data stream with datetime index.
+    pct_increase_threshold: int, default 95
+        The percentage threshold to consider the energy series as cumulative.
+    system_self_consumption: Float, default -0.5
+        The difference threshold to account for the effect of nighttime system
+        self-consumption on the energy data stream.
+
+    Returns
+    -------
+    Boolean
+        True if energy_series is cumulative, False otherwise.
+    """
+    differenced_series = energy_series.diff().dropna()
+    # Get the averaged difference
+    avg_diff_series = 0.5 * \
+        (differenced_series.shift(-1) + differenced_series).dropna()
+    if len(differenced_series) == 0:
+        warnings.warn(
+            "The energy time series has a length of zero and cannot be run.")
+        return False
+    else:
+        # If over X percent of the data is increasing (set via the
+        # pct_increase_threshold), then assume that the column is cumulative
+        avg_series_positive_mask = (avg_diff_series >= system_self_consumption)
+        pct_over_zero = avg_series_positive_mask.value_counts(
+            normalize=True) * 100
+        if pct_over_zero[True] >= pct_increase_threshold:
+            return True
+        else:
+            return False
+
+
+def convert_cumulative_energy(energy_series, pct_increase_threshold=95,
+                              system_self_consumption=-0.5):
+    """Convert cumulative to interval-based, non-cumulative energy, if needed.
+
+    Two main test are run to determine if the associated energy
+    data stream is cumulative or not: a simple differencing function is run
+    on the series via cumulative_energy_simple_diff_check, and an
+    average differencing function is run on the series via
+    cumulative_energy_avg_diff_check.
+
+    Parameters
+    ----------
+    energy_series: Series
+        Time series of energy data stream with datetime index.
+    pct_increase_threshold: int, default 95
+        The percentage threshold to consider the energy series as cumulative.
+    system_self_consumption: Float, default -0.5
+        The difference threshold to account for the effect of nighttime system
+        self-consumption on the energy data stream.
+
+    Returns
+    -------
+    Series
+        corrected_energy_series is retuned if the energy series is cumulative.
+        If the energy series passes the simple difference check, then the
+        the series is corrected via the simple differencing. Else, if
+        energy series passes the average difference check, then the series is
+        corrected via average differencing.
+        If neither checks are passes, then the original non-cumulative
+        energy_series is returned.
+    """
+    # Check if energy series is cumulative with simple difference and average
+    # difference
+    simple_diff_check = cumulative_energy_simple_diff_check(
+        energy_series, pct_increase_threshold, system_self_consumption)
+    avg_diff_check = cumulative_energy_avg_diff_check(energy_series,
+                                                      pct_increase_threshold,
+                                                      system_self_consumption)
+    if simple_diff_check:
+        # Return simple difference of energy series if it passes the simple
+        # difference check
+        corrected_energy_series = energy_series.diff()
+        return corrected_energy_series
+    elif avg_diff_check:
+        # Return average differnce of energy series if it passes the
+        # average difference check
+        corrected_energy_series = 0.5 * \
+            (energy_series.diff().shift(-1) + energy_series.diff())
+        return corrected_energy_series
+    else:
+        return energy_series
diff --git a/pvanalytics/tests/quality/test_energy.py b/pvanalytics/tests/quality/test_energy.py
new file mode 100644
index 00000000..a4b88121
--- /dev/null
+++ b/pvanalytics/tests/quality/test_energy.py
@@ -0,0 +1,164 @@
+"""Tests for energy functions."""
+import pytest
+import os
+import pandas as pd
+from pandas.testing import assert_series_equal
+from pvanalytics.quality import energy
+
+script_directory = os.path.dirname(__file__)
+energy_filepath = os.path.join(script_directory,
+                               "../../data/system_10004_ac_energy.csv")
+energy_df = pd.read_csv(energy_filepath)
+
+
+@pytest.fixture
+def cumulative_series():
+    """
+    A pandas energy time series with cumulative data.
+    """
+    data = energy_df["ac_energy_inv_16425"]
+    return pd.Series(data=data)
+
+
+@pytest.fixture
+def noncumulative_series():
+    """
+    A pandas energy time series with noncumulative data.
+    """
+    # Perform .diff() to turn cumulative data into noncumulative
+    diff_data = energy_df["ac_energy_inv_16425"].diff().dropna()
+    return pd.Series(data=diff_data)
+
+
+@pytest.fixture
+def zero_length_series():
+    """
+    A pandas energy time series that has zero length.
+    """
+    data = []
+    return pd.Series(data=data, dtype="float64")
+
+
+@pytest.fixture
+def simple_diff_energy_series():
+    """
+    The differenced pandas energy series using the simple .diff() function.
+    """
+    diff_data = energy_df["ac_energy_inv_16425"].diff()
+    return pd.Series(data=diff_data)
+
+
+@pytest.fixture
+def alt_cumulative_series():
+    """
+    A cumulative energy series.
+    """
+    cumulative_series = pd.Series([1.5, 1, 2, 5, 8])
+    return cumulative_series
+
+
+@pytest.fixture
+def alt_avg_diff_series():
+    """
+    The average differene energy series.
+    """
+    cumulative_series = pd.Series([1.5, 1, 2, 5, 8])
+    avg_diff_series = 0.5 * \
+        (cumulative_series.diff().shift(-1) + cumulative_series.diff())
+    return pd.Series(avg_diff_series)
+
+
+def test_cumulative_energy_simple_diff_check_true(cumulative_series):
+    """
+    Tests if cumulative_energy_simple_diff_check for cumulative series is True.
+    """
+    assert energy.cumulative_energy_simple_diff_check(
+        energy_series=cumulative_series, system_self_consumption=0.0) is True
+
+
+def test_noncumulative_energy_simple_diff_check_false(noncumulative_series):
+    """
+    Tests if cumulative_energy_simple_diff_check for noncumulative series
+    is False.
+    """
+    assert energy.cumulative_energy_simple_diff_check(
+        energy_series=noncumulative_series,
+        system_self_consumption=0.0) is False
+
+
+def test_zero_length_energy_simple_diff_check_false(zero_length_series):
+    """
+    Tests if cumulative_energy_simple_diff_check for zero length series is
+    False.
+    """
+    assert energy.cumulative_energy_simple_diff_check(
+        energy_series=zero_length_series) is False
+
+
+def test_cumulative_energy_avg_diff_check_true(cumulative_series):
+    """
+    Tests if cumulative_energy_avg_diff_check for cumulative series is True.
+    """
+    assert energy.cumulative_energy_avg_diff_check(
+        energy_series=cumulative_series, system_self_consumption=0.0) is True
+
+
+def test_noncumulative_energy_avg_diff_check_false(noncumulative_series):
+    """
+    Tests if cumulative_energy_avg_diff_check for noncumulative series
+    is False.
+    """
+    assert energy.cumulative_energy_avg_diff_check(
+        energy_series=noncumulative_series,
+        system_self_consumption=0.0) is False
+
+
+def test_zero_length_energy_avg_diff_check_false(zero_length_series):
+    """
+    Tests if cumulative_energy_avg_diff_check for zero length series is
+    False.
+    """
+    assert energy.cumulative_energy_avg_diff_check(
+        energy_series=zero_length_series) is False
+
+
+def test_convert_cumulative_with_simple_diff(cumulative_series,
+                                             simple_diff_energy_series):
+    """
+    Tests convert_cumulative_energy for cumulative series.
+    Test returns the corrected differenced series via simple differencing.
+    """
+    simple_diff_result = energy.convert_cumulative_energy(
+        energy_series=cumulative_series, system_self_consumption=0.0)
+    assert_series_equal(simple_diff_result, simple_diff_energy_series)
+
+
+def test_convert_cumulative_with_avg_diff(alt_cumulative_series,
+                                          alt_avg_diff_series):
+    """
+    Tests convert_cumulative_energy for cumulative series.
+    Test returns the corrected differenced series via average differencing.
+    """
+    simple_diff_result = energy.convert_cumulative_energy(
+        energy_series=alt_cumulative_series, system_self_consumption=0.0)
+    assert_series_equal(simple_diff_result, alt_avg_diff_series)
+
+
+def test_convert_noncumulative(noncumulative_series):
+    """
+    Tests convert_cumulative_energy for non-cumulative series.
+    Test returns the original non-cumulative energy series.
+    """
+    energy_result = energy.convert_cumulative_energy(
+        energy_series=noncumulative_series, system_self_consumption=0.0)
+    assert_series_equal(energy_result, noncumulative_series)
+
+
+def test_check_zero_length(zero_length_series):
+    """
+    Tests convert_cumulative_energy for zero length series.
+    Test returns the original zero length energy series.
+    """
+    energy_result = energy.convert_cumulative_energy(
+        energy_series=zero_length_series, system_self_consumption=0.0)
+    assert_series_equal(energy_result, zero_length_series)