diff --git a/cymetric/metrics.py b/cymetric/metrics.py
index 36692ba6..18d5b034 100644
--- a/cymetric/metrics.py
+++ b/cymetric/metrics.py
@@ -537,3 +537,80 @@ def timelist(info):
 
 
 del _tldeps, _tlschema
+
+
+# Quantity per GigaWattElectric in Inventory [kg/GWe]
+_invdeps = ['ExplicitInventory','TimeSeriesPower']
+
+_invschema = [
+    ('SimId', ts.UUID),
+    ('AgentId', ts.INT), 
+    ('Time', ts.INT),
+    ('InventoryName', ts.STRING),
+    ('NucId', ts.INT),
+    ('Quantity', ts.DOUBLE)
+    ]
+
+@metric(name='InventoryQuantityPerGWe', depends=_invdeps, schema=_invschema)
+def inventory_quantity_per_gwe(expinv,power):
+    """Inventory Quantity per GWe metric returns the explicit inventory table with quantity
+    in units of kg/GWe, calculated by dividing the original quantity by the electricity generated
+    at the corresponding simulation and the specific time in TimeSeriesPower metric.
+    """
+    power = pd.DataFrame(data={'SimId': power.SimId,
+			      'AgentId': power.AgentId,
+                              'Time': power.Time,
+                              'Value': power.Value},
+			columns=['SimId','AgentID','Time', 'Value'])
+    power_index = ['SimId','Time']
+    power = power.groupby(power_index).sum()
+    df1 = power.reset_index()
+    inv = pd.DataFrame(data={'SimId': expinv.SimId,
+			     'AgentId': expinv.AgentId,
+			     'Time': expinv.Time, 
+		             'InventoryName': expinv.InventoryName,
+	 		     'NucId': expinv.NucId,
+                             'Quantity': expinv.Quantity},
+	             columns=['SimId','AgentId','Time','InventoryName','NucId','Quantity'])    
+    inv=pd.merge(inv,df1, on=['SimId','Time'],how='left')
+    inv.Quantity = inv.Quantity/inv.Value
+    inv=inv.drop(['Value'],axis=1)
+    return inv
+
+
+# Quantity per GigaWattElectric in TransactionQuantity [kg/GWe]
+_tranactsdeps = ['TransactionQuantity','TimeSeriesPower']
+
+_tranactsschema = [
+    ('SimId', ts.UUID),
+    ('TransactionId', ts.INT),
+    ('ResourceId', ts.INT),
+    ('ObjId', ts.INT),
+    ('Time', ts.INT),
+    ('SenderId', ts.INT),
+    ('ReceiverId', ts.INT),
+    ('Commodity', ts.STRING),
+    ('Units', ts.STRING),
+    ('Quantity', ts.DOUBLE)
+    ]
+
+
+@metric(name='TransactionQuantityPerGWe', 
+        depends=_tranactsdeps, schema=_tranactsschema)
+def transaction_quantity_per_gwe(tranacts, power):
+    """Transaction Quantity per GWe metric returns the transaction quantity 
+    table with quantity in units of kg/GWe, calculated by dividing the 
+    original quantity by the electricity generated at the corresponding 
+    simulation and the specific time in TimeSeriesPower metric.
+    """
+    power = power.groupby(['SimId', 'Time']).sum()
+    df1 = power.reset_index()
+    tranacts_index = ['SimId', 'TransactionId', 'ResourceId', 
+                      'ObjId', 'Time','SenderId', 'ReceiverId', 
+                      'Commodity', 'Units', 'Quantity']
+    tranacts = tranacts.rename(columns = {'TimeCreated' : 'Time'})
+    tranacts['Units'] = tranacts['Units'] + "/MWe" 
+    tranacts=pd.merge(tranacts,df1, on=['SimId', 'Time'],how='left')
+    tranacts.Quantity = tranacts.Quantity/tranacts.Value
+    return tranacts[tranacts_index]
+
diff --git a/tests/test_metrics.py b/tests/test_metrics.py
index 48712010..458e3e9b 100644
--- a/tests/test_metrics.py
+++ b/tests/test_metrics.py
@@ -549,53 +549,101 @@ def test_timelist():
 def test_inventory_quantity_per_gwe():
     # exp is the expected output metrics
     exp = pd.DataFrame(np.array([
-        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'core',
-            922350000, 1.0),
-        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'usedfuel',
-            922350000, 2.0),
-        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 1, 'core',
-            922350000, 2.0),
-    ], dtype=ensure_dt_bytes([
-        ('SimId', 'O'),
-        ('AgentId', '<i8'),
-        ('Time', '<i8'),
-        ('InventoryName', 'O'),
-        ('NucId', '<i8'),
-        ('Quantity', '<f8')
-    ]))
-    )
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 
+         1, 0, 'core', 922350000, 1.0),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 
+         1, 0, 'usedfuel', 922350000, 2.0),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 
+         2, 1, 'core', 922350000, 2.0),
+        ], dtype=ensure_dt_bytes([
+                ('SimId', 'O'),
+                ('AgentId', '<i8'),
+                ('Time', '<i8'),
+                ('InventoryName', 'O'),
+                ('NucId', '<i8'),
+                ('Quantity', '<f8')]))
+        )
+
     # tsp is the TimeSeriesPower metrics
     tsp = pd.DataFrame(np.array([
         (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 100),
         (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 0, 200),
         (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 1, 100),
-    ], dtype=ensure_dt_bytes([
-        ('SimId', 'O'),
-        ('AgentId', '<i8'),
-        ('Time', '<i8'),
-        ('Value', '<f8')
-    ]))
-    )
+        ], dtype=ensure_dt_bytes([
+                ('SimId', 'O'),
+                ('AgentId', '<i8'),
+                ('Time', '<i8'),
+                ('Value', '<f8')]))
+        )
     # inv is the ExplicitInventory metrics
     inv = pd.DataFrame(np.array([
-        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'core',
-            922350000, 300),
-        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'usedfuel',
-            922350000, 600),
-        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 1, 'core',
-            922350000, 200),
-    ], dtype=ensure_dt_bytes([
-        ('SimId', 'O'),
-        ('AgentId', '<i8'),
-        ('Time', '<i8'),
-        ('InventoryName', 'O'),
-        ('NucId', '<i8'),
-        ('Quantity', '<f8')
-    ]))
-    )
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'core', 922350000, 300),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 0, 'usedfuel', 922350000, 600),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 1, 'core', 922350000, 200),
+        ], dtype=ensure_dt_bytes([
+                ('SimId', 'O'),
+                ('AgentId', '<i8'),
+                ('Time', '<i8'),
+                ('InventoryName', 'O'),
+                ('NucId', '<i8'),
+                ('Quantity', '<f8')]))
+        )
     obs = metrics.inventory_quantity_per_gwe.func(inv, tsp)
     assert_frame_equal(exp, obs)
 
 
+def test_transaction_quantity_per_gwe():
+    # exp is the expected output metrics
+    exp = pd.DataFrame(np.array([
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'),
+         1, 7, 3, 3,  10, 20, 'LWR Fuel', 'kg/MWe', 0.82),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'),
+         2, 8, 4, 3,  20, 30, 'FR Fuel', 'kg/MWe', 0.61),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'),
+         3, 9, 5, 12, 30, 40, 'Spent Fuel', 'kg/MWe', 0.09),
+        ], dtype=ensure_dt_bytes([
+                ('SimId', 'O'),
+                ('TransactionId', '<i8'),
+                ('ResourceId', '<i8'),
+                ('ObjId', '<i8'),
+                ('Time', '<i8'),
+                ('SenderId', '<i8'),
+                ('ReceiverId', '<i8'), 
+                ('Commodity', 'O'),
+                ('Units', 'O'),
+                ('Quantity', '<f8')]))
+        )
+    # tsp is the TimeSeriesPower metrics
+    tsp = pd.DataFrame(np.array([
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 3, 225),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 3, 275),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 12, 100),
+        ], dtype=ensure_dt_bytes([
+                ('SimId', 'O'),
+                ('AgentId', '<i8'),
+                ('Time', '<i8'),
+                ('Value', '<f8')]))
+        )
+    # tranacts is the TransactionQuantity metrics
+    tranacts = pd.DataFrame(np.array([
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 1, 7, 3, 3,  10, 20, 'LWR Fuel', 'kg', 410),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 2, 8, 4, 3,  20, 30, 'FR Fuel', 'kg', 305),
+        (UUID('f22f2281-2464-420a-8325-37320fd418f8'), 3, 9, 5, 12, 30, 40, 'Spent Fuel', 'kg', 9),
+        ], dtype=ensure_dt_bytes([
+                ('SimId', 'O'),
+                ('TransactionId', '<i8'),
+                ('ResourceId', '<i8'),
+                ('ObjId', '<i8'),
+                ('TimeCreated', '<i8'),
+                ('SenderId', '<i8'),
+                ('ReceiverId', '<i8'),
+                ('Commodity', 'O'),
+                ('Units', 'O'),
+                ('Quantity', '<f8')]))
+        )
+    obs = metrics.transaction_quantity_per_gwe.func(tranacts, tsp)
+    assert_frame_equal(exp, obs)
+
+
 if __name__ == "__main__":
     nose.runmodule()