Added fixed operating costs and total capacity calculations

scripts/prepare_cbc_short.sh

@@ -10,7 +10,7 @@ echo "end;" >> trimmed.txt
 # Omitting --check, which runs the solve using GLPK as well
 glpsol --wlp simplicity.lp -m ../osemosys/OSeMOSYS_GNU_MathProg/src/osemosys_short.txt -d trimmed.txt
 cbc simplicity.lp -dualpivot pesteep -psi 1.0 -pertv 52 -duals solve -solu simplicity.sol
-otoole -vvv results cbc csv simplicity.sol output
+otoole -vvv results cbc csv simplicity.sol output --input_data OSeMOSYS-simplicity-11a3a26/datapackage.json
 
 ls output > output_files
 ls results > result_file

src/otoole/results/calculate.py

@@ -41,18 +41,14 @@ def compute_annual_emissions(
 
 
 def compute_annual_fixed_operating_cost(
-    acc_new_capacity: pd.DataFrame,
-    residual_capacity: pd.DataFrame,
-    fixed_cost: pd.DataFrame,
+    total_capacity: pd.DataFrame, fixed_cost: pd.DataFrame,
 ) -> pd.DataFrame:
     """Compute AnnualFixedOperatingCost result
 
     Arguments
     ---------
-    acc_new_capacity: pd.DataFrame
-        Accumulated new capacity
-    residual_capacity: pd.DataFrame
-        Residual capacity
+    total_capacity: pd.DataFrame
+        Total annual capacity (new and residual)
     fixed_cost: pd.DataFrame
         Fixed cost
 
@@ -64,9 +60,29 @@ def compute_annual_fixed_operating_cost(
         NewCapacity[r,t,yy]) + ResidualCapacity[r,t,y]) ~VALUE;
 
     """
-    total_capacity = acc_new_capacity + residual_capacity
-    total_fixed_costs = fixed_cost * total_capacity
-    return total_fixed_costs[(total_fixed_costs != 0).all(1)]
+    total_fixed_costs = total_capacity.mul(fixed_cost, fill_value=0.0)
+    return total_fixed_costs[(total_fixed_costs != 0).all(1)].dropna()
+
+
+def compute_total_capacity_annual(residual_capacity, acc_new_capacity):
+    """Compute TotalCapacityAnnual result
+
+    Arguments
+    ---------
+    acc_new_capacity: pd.DataFrame
+        Accumulated new capacity
+    residual_capacity: pd.DataFrame
+        Residual capacity
+
+    Notes
+    -----
+    r~REGION, t~TECHNOLOGY, y~YEAR,
+    ResidualCapacity[r,t,y] +
+    (sum{yy in YEAR: y-yy < OperationalLife[r,t] && y-yy>=0}
+        NewCapacity[r,t,yy])~VALUE;
+    """
+    total_capacity = residual_capacity.add(acc_new_capacity, fill_value=0.0)
+    return total_capacity[(total_capacity != 0).all(1)]
 
 
 def compute_accumulated_new_capacity(
@@ -177,13 +193,26 @@ def calculate_result(
         new_capacity = results_data["NewCapacity"].copy()
         year = pd.Index(package["YEAR"]["VALUE"].to_list())
         return compute_accumulated_new_capacity(operational_life, new_capacity, year)
+
     elif parameter_name == "AnnualEmissions":
         emission_activity_ratio = package["EmissionActivityRatio"]
         yearsplit = package["YearSplit"]
         rate_of_activity = results_data["RateOfActivity"].copy()
         return compute_annual_emissions(
             emission_activity_ratio, yearsplit, rate_of_activity
         )
+    elif parameter_name == "TotalCapacityAnnual":
+        acc_new_capacity = calculate_result(
+            "AccumulatedNewCapacity", input_data, results_data
+        )
+        residual_capacity = package["ResidualCapacity"]
+        return compute_total_capacity_annual(residual_capacity, acc_new_capacity)
+    elif parameter_name == "AnnualFixedOperatingCost":
+        total_capacity = calculate_result(
+            "TotalCapacityAnnual", input_data, results_data
+        )
+        fixed_cost = package["FixedCost"]
+        return compute_annual_fixed_operating_cost(total_capacity, fixed_cost)
     elif parameter_name == "AnnualTechnologyEmission":
         emission_activity_ratio = package["EmissionActivityRatio"]
         yearsplit = package["YearSplit"]

src/otoole/results/convert.py

@@ -226,10 +226,16 @@ def convert_dataframe_to_csv(
 ) -> Dict[str, pd.DataFrame]:
     """Convert from dataframe to csv
 
+    Converts a pandas DataFrame containing all CBC results to reformatted
+    dictionary of pandas DataFrames in long format ready to write out as
+    csv files
+
     Arguments
     ---------
     data : pandas.DataFrame
-    input_data : str
+        CBC results stored in a dataframe
+    input_data : str, default=None
+        Path to the OSeMOSYS data file containing input data
 
     Example
     -------
@@ -285,14 +291,16 @@ def convert_dataframe_to_csv(
                 )
                 df = calculate_result(name, input_data, results)
                 if not df.empty:
-                    results[name] = df.set_index(indices)
+                    results[name] = df
                 else:
                     LOGGER.warning(
                         "Calculation returned empty dataframe for parameter '%s'", name
                     )
             else:
                 LOGGER.warning(
-                    "No input data provided, unable to calculate parameter '%s'", name
+                    "No OSeMOSYS data file provided, \
+                     unable to calculate parameter '%s'",
+                    name,
                 )
 
     return results

tests/results/test_calculate.py

@@ -9,6 +9,7 @@
     compute_annual_fixed_operating_cost,
     compute_annual_technology_emission_by_mode,
     compute_annual_technology_emissions,
+    compute_total_capacity_annual,
 )
 
 
@@ -193,33 +194,50 @@ def accumulated_new_capacity():
 
 
 @fixture
-def fixed_cost():
+def residual_capacity():
     data = pd.DataFrame(
         data=[
             ["SIMPLICITY", "GAS_EXTRACTION", 2014, 1],
             ["SIMPLICITY", "GAS_EXTRACTION", 2015, 1],
-            ["SIMPLICITY", "GAS_EXTRACTION", 2016, 1],
-            ["SIMPLICITY", "GAS_EXTRACTION", 2017, 1],
-            ["SIMPLICITY", "DUMMY", 2014, 0.5],
-            ["SIMPLICITY", "DUMMY", 2015, 0.5],
-            ["SIMPLICITY", "DUMMY", 2016, 0.5],
+            ["SIMPLICITY", "GAS_EXTRACTION", 2016, 0],
+            ["SIMPLICITY", "GAS_EXTRACTION", 2017, 0],
+            ["SIMPLICITY", "DUMMY", 2014, 0.1],
+            ["SIMPLICITY", "DUMMY", 2015, 0.2],
+            ["SIMPLICITY", "DUMMY", 2016, 0.3],
         ],
         columns=["REGION", "TECHNOLOGY", "YEAR", "VALUE"],
     ).set_index(["REGION", "TECHNOLOGY", "YEAR"])
     return data
 
 
 @fixture
-def residual_capacity():
+def total_capacity():
+    data = pd.DataFrame(
+        data=[
+            ["SIMPLICITY", "GAS_EXTRACTION", 2014, 2.3],
+            ["SIMPLICITY", "GAS_EXTRACTION", 2015, 2.3],
+            ["SIMPLICITY", "GAS_EXTRACTION", 2016, 1.6],
+            ["SIMPLICITY", "GAS_EXTRACTION", 2017, 1.6],
+            ["SIMPLICITY", "DUMMY", 2014, 1.0],
+            ["SIMPLICITY", "DUMMY", 2015, 1.1],
+            ["SIMPLICITY", "DUMMY", 2016, 1.2],
+        ],
+        columns=["REGION", "TECHNOLOGY", "YEAR", "VALUE"],
+    ).set_index(["REGION", "TECHNOLOGY", "YEAR"])
+    return data
+
+
+@fixture
+def fixed_cost():
     data = pd.DataFrame(
         data=[
             ["SIMPLICITY", "GAS_EXTRACTION", 2014, 1],
             ["SIMPLICITY", "GAS_EXTRACTION", 2015, 1],
-            ["SIMPLICITY", "GAS_EXTRACTION", 2016, 0],
-            ["SIMPLICITY", "GAS_EXTRACTION", 2017, 0],
-            ["SIMPLICITY", "DUMMY", 2014, 0.1],
-            ["SIMPLICITY", "DUMMY", 2015, 0.2],
-            ["SIMPLICITY", "DUMMY", 2016, 0.3],
+            ["SIMPLICITY", "GAS_EXTRACTION", 2016, 1],
+            ["SIMPLICITY", "GAS_EXTRACTION", 2017, 1],
+            ["SIMPLICITY", "DUMMY", 2014, 0.5],
+            ["SIMPLICITY", "DUMMY", 2015, 0.5],
+            ["SIMPLICITY", "DUMMY", 2016, 0.5],
         ],
         columns=["REGION", "TECHNOLOGY", "YEAR", "VALUE"],
     ).set_index(["REGION", "TECHNOLOGY", "YEAR"])
@@ -478,10 +496,8 @@ class TestComputeFixedOperatingCost:
     0.9 + 0.3 * 0.5 = 0.6
     """
 
-    def test_compute(self, accumulated_new_capacity, residual_capacity, fixed_cost):
-        actual = compute_annual_fixed_operating_cost(
-            accumulated_new_capacity, residual_capacity, fixed_cost
-        )
+    def test_compute(self, total_capacity, fixed_cost):
+        actual = compute_annual_fixed_operating_cost(total_capacity, fixed_cost)
         expected = pd.DataFrame(
             data=[
                 ["SIMPLICITY", "GAS_EXTRACTION", 2014, 2.3],
@@ -498,8 +514,45 @@ def test_compute(self, accumulated_new_capacity, residual_capacity, fixed_cost):
         assert_frame_equal(actual, expected)
 
     def test_compute_null(self):
-        actual = compute_annual_fixed_operating_cost(
-            pd.DataFrame(), pd.DataFrame(), pd.DataFrame()
+        actual = compute_annual_fixed_operating_cost(pd.DataFrame(), pd.DataFrame())
+        expected = pd.DataFrame()
+        assert_frame_equal(actual, expected)
+
+
+class TestComputeTotalAnnualCapacity:
+    """
+
+    Notes
+    -----
+    1.3 + 1.0
+    1.3 + 1.0
+    1.6 + 0.0
+    1.6 + 0.0
+    0.9 + 0.1
+    0.9 + 0.2
+    0.9 + 0.3
+    """
+
+    def test_compute(self, accumulated_new_capacity, residual_capacity):
+        actual = compute_total_capacity_annual(
+            residual_capacity, accumulated_new_capacity
         )
+        expected = pd.DataFrame(
+            data=[
+                ["SIMPLICITY", "GAS_EXTRACTION", 2014, 2.3],
+                ["SIMPLICITY", "GAS_EXTRACTION", 2015, 2.3],
+                ["SIMPLICITY", "GAS_EXTRACTION", 2016, 1.6],
+                ["SIMPLICITY", "GAS_EXTRACTION", 2017, 1.6],
+                ["SIMPLICITY", "DUMMY", 2014, 1.0],
+                ["SIMPLICITY", "DUMMY", 2015, 1.1],
+                ["SIMPLICITY", "DUMMY", 2016, 1.2],
+            ],
+            columns=["REGION", "TECHNOLOGY", "YEAR", "VALUE"],
+        ).set_index(["REGION", "TECHNOLOGY", "YEAR"])
+
+        assert_frame_equal(actual, expected)
+
+    def test_compute_null(self):
+        actual = compute_total_capacity_annual(pd.DataFrame(), pd.DataFrame())
         expected = pd.DataFrame()
         assert_frame_equal(actual, expected)