Merge pull request #78 from sedos-project/feature/routine-for-decomis…

…sioning-of-exisitng-capacity

Feature/routine for decomissioning of exisiting capacity

data_adapter_oemof/adapters.py

@@ -7,7 +7,6 @@
 import warnings
 from typing import Optional, Type, Union
 
-import numpy as np
 import pandas as pd
 from oemof.tabular import facades
 from oemof.tabular._facade import Facade
@@ -38,6 +37,8 @@ class Adapter:
         Field(name="region", type=str),
         Field(name="year", type=int),
     )
+    output_parameters = (Field(name="max", type=float), Field(name="min", type=float))
+    input_parameters = ()
     counter: int = itertools.count()
 
     def __init__(
@@ -75,16 +76,12 @@ def get_default_parameters(self) -> dict:
                     )
                 }
             )
-        if "lifetime" in defaults.keys():
-            # want to move this section including if statements together with decommissioning
-            # section to a calculations as "default calculations
-            if not isinstance(defaults["lifetime"], collections.abc.Iterable):
-                defaults["lifetime"] = int(np.floor(defaults["lifetime"]))
-            elif all(x == defaults["lifetime"][0] for x in defaults["lifetime"]):
-                defaults["lifetime"] = int(np.floor(defaults["lifetime"][0]))
-            else:
-                warnings.warn("Lifetime cannot change in Multi-period modeling")
-                defaults["lifetime"] = int(np.floor(defaults["lifetime"][0]))
+
+        defaults = self.default_post_mapping_calculations(defaults)
+        if not defaults["input_parameters"]:
+            defaults.pop("input_parameters")
+        if not defaults["output_parameters"]:
+            defaults.pop("output_parameters")
 
         return defaults
 
@@ -271,24 +268,94 @@ def get_busses(self) -> dict:
 
         return bus_dict
 
+    def get_output_input_parameter_fields(self):
+        """
+        Getting output and input parameters from data
+        Parameters must be applicable to respective flows
+
+        Parameters to be defined in Adapter
+        Returns
+        {"output_parameters": {"min": [10, 20], "max": [20, 30]},
+        "input_parameters": {"min": [10, 20], "max": [20, 30]}}
+        -------
+
+        """
+
+        def get_io_parameter_dict(parameters):
+            io_dict = {}
+            for param in parameters:
+                if input_parameter_value := self.get(param.name):
+                    io_dict.update({param.name: input_parameter_value})
+            return io_dict
+
+        input_output_parameters = {"output_parameters": {}, "input_parameters": {}}
+
+        input_output_parameters["input_parameters"].update(
+            get_io_parameter_dict(parameters=self.input_parameters)
+        )
+        input_output_parameters["output_parameters"].update(
+            get_io_parameter_dict(parameters=self.output_parameters)
+        )
+
+        return input_output_parameters
+
     def get_default_mappings(self):
         """
         :return: Dictionary for all fields that the facade can take and matching data
         """
 
+        self.default_pre_mapping_calculations()
+
         mapped_all_class_fields = {
             field.name: value
             for field in self.get_fields()
             if (value := self.get(field.name, field.type)) is not None
         }
         mapped_all_class_fields.update(self.get_busses())
+        mapped_all_class_fields.update(self.get_output_input_parameter_fields())
         return mapped_all_class_fields
 
     @staticmethod
     def is_sequence(field_type: Type):
         # TODO: Implement it using typing hints
         return "Sequence" in str(field_type)
 
+    def default_pre_mapping_calculations(self):
+        """
+        Takes activity bonds and calculates min/max values
+        Parameters
+        ----------
+        adapter_dict
+
+        Returns
+        -------
+
+        """
+        calculations.normalize_activity_bonds(self)
+
+    def default_post_mapping_calculations(self, mapped_defaults):
+        """
+        Does default calculations#
+
+        I. Decommissioning of existing Capacities
+        II. Rounding lifetime down to integers
+
+        Returns
+        -------
+
+        """
+        # I:
+        if self.process_name[-1] == "0":
+            mapped_defaults = calculations.decommission(
+                process_name=self.process_name, adapter_dict=mapped_defaults
+            )
+
+        # II:
+        if "lifetime" in mapped_defaults.keys():
+            mapped_defaults = calculations.floor_lifetime(mapped_defaults)
+
+        return mapped_defaults
+
 
 class DispatchableAdapter(Adapter):
     """
@@ -427,9 +494,21 @@ class MIMOAdapter(Adapter):
         Field(name="groups", type=dict),
         Field(name="capacity_cost", type=float),
         Field(name="capacity", type=float),
-        Field(name="max", type=float),
         Field(name="expandable", type=bool),
+        Field(name="activity_bound_min", type=float),
+        Field(name="activity_bound_max", type=float),
+        Field(name="activity_bound_fix", type=float),
     )
+    output_parameters = ()
+
+    def default_pre_mapping_calculations(self):
+        """
+        Mimo adapter specific pre calculations
+        Returns
+        -------
+
+        """
+        pass
 
     def get_default_parameters(self) -> dict:
         defaults = super().get_default_parameters()

data_adapter_oemof/calculations.py

@@ -1,3 +1,8 @@
+import collections
+import logging
+import warnings
+
+import numpy as np
 from oemof.tools.economics import annuity
 
 
@@ -34,3 +39,152 @@ def get_name(*args, counter=None):
 @calculation
 def get_capacity_cost(overnight_cost, fixed_cost, lifetime, wacc):
     return annuity(overnight_cost, lifetime, wacc) + fixed_cost
+
+
+def decommission(process_name, adapter_dict: dict) -> dict:
+    """
+
+    Takes adapter dictionary from adapters.py with mapped values.
+
+    I:
+    Takes largest found capacity and sets this capacity for all years
+    Each yearly changing capacity value is divided by max capacity and
+    quotient from `max capacity`/`yearly capacity` is set as max value.
+
+    II:
+    If Max value is already set by another parameter function will issue info
+    Recalculating max value to
+
+    .. math::
+        max_{new} = \frac{(max_{column} * capacity_{column})}{capacity_{max}}
+
+    Overwriting max value in `output_parameters`
+    Then is setting capacity to the largest found capacity
+
+
+    Supposed to be called when getting default parameters
+    Non investment objects must be decommissioned in multi period to take end of lifetime
+    for said objet into account.
+
+    Returns
+    adapter_dictionary with max values in output parameters and a single capacity
+    -------
+
+    """
+
+    def multiply_two_lists(l1, l2):
+        """
+        Multiplies two lists
+
+        Lists must be same length
+
+        Parameters
+        ----------
+        l1
+        l2
+
+        Returns divided list
+        -------
+
+        """
+        return [i * j for i, j in zip(l1, l2)]
+
+    capacity_column = "capacity"
+    max_column = "max"
+
+    # check if capacity column is there and if it has to be decommissioned
+    if capacity_column not in adapter_dict.keys():
+        logging.info(
+            f"Capacity missing for decommissioning " f"of Process `{process_name}`"
+        )
+        return adapter_dict
+
+    if not isinstance(adapter_dict[capacity_column], list):
+        logging.info(
+            f"No capacity fading out that can be decommissioned"
+            f" for Process `{process_name}`."
+        )
+        return adapter_dict
+
+    # I:
+    if max_column not in adapter_dict["output_parameters"].keys():
+        adapter_dict["output_parameters"][max_column] = adapter_dict[
+            capacity_column
+        ] / np.max(adapter_dict[capacity_column])
+    # II:
+    else:
+        adapter_dict["output_parameters"][max_column] = multiply_two_lists(
+            adapter_dict["output_parameters"][max_column], adapter_dict[capacity_column]
+        ) / np.max(adapter_dict[capacity_column])
+
+    adapter_dict[capacity_column] = np.max(adapter_dict[capacity_column])
+    return adapter_dict
+
+
+def normalize_activity_bonds(adapter):
+    """
+    Normalizes activity bonds in order to be used as min/max values
+    Parameters
+    ----------
+    adapter
+
+    Returns
+    -------
+
+    """
+
+    def divide_two_lists(dividend, divisor):
+        """
+        Divides two lists returns quotient, returns 0 if divisor is 0
+
+        Lists must be same length
+
+        Parameters
+        ----------
+        dividend
+        divisor
+
+        Returns divided list
+        -------
+
+        """
+        return [i / j if j != 0 else 0 for i, j in zip(dividend, divisor)]
+
+    if "activity_bound_fix" in adapter.data.keys():
+        adapter.data["activity_bound_fix"] = divide_two_lists(
+            adapter.data["activity_bound_fix"], adapter.get("capacity")
+        )
+        return adapter
+
+    if "activity_bound_min" in adapter.data.keys():
+        adapter.data["activity_bound_min"] = divide_two_lists(
+            adapter.data["activity_bound_min"], adapter.get("capacity")
+        )
+        return adapter
+
+    if "activity_bound_max" in adapter.data.keys():
+        adapter.data["activity_bound_max"] = divide_two_lists(
+            adapter.data["activity_bound_max"], adapter.get("capacity")
+        )
+        return adapter
+
+
+def floor_lifetime(mapped_defaults):
+    """
+
+    Parameters
+    ----------
+    adapter
+
+    Returns
+    -------
+
+    """
+    if not isinstance(mapped_defaults["lifetime"], collections.abc.Iterable):
+        mapped_defaults["lifetime"] = int(np.floor(mapped_defaults["lifetime"]))
+    elif all(x == mapped_defaults["lifetime"][0] for x in mapped_defaults["lifetime"]):
+        mapped_defaults["lifetime"] = int(np.floor(mapped_defaults["lifetime"][0]))
+    else:
+        warnings.warn("Lifetime cannot change in Multi-period modeling")
+        mapped_defaults["lifetime"] = int(np.floor(mapped_defaults["lifetime"][0]))
+    return mapped_defaults

examples/industry/data_adapter_industry.py

@@ -66,7 +66,6 @@
     "MIMOAdapter": {
         "capacity_cost": "cost_fix_capacity_w",
         "capacity": "capacity_w_resid",
-        "max": "activity_bound_fix",
         "expandable": "capacity_w_abs_new_max",
     },
     "modex_tech_wind_turbine_onshore": {"profile": "onshore"},