Account for remaining values in multi-period models

docs/usage.rst

@@ -1270,6 +1270,11 @@ Besides the `invest` variable, new variables are introduced as well. These are:
       has not yet been tested.
     * For now, both, the `timeindex` as well as the `timeincrement` of an energy system have to be defined since they
       have to be of the same length for a multi-period model.
+    * You can choose whether to re-evaluate assets at the end of the optimization horizon. If you set attribute
+      `use_remaining_value` of the energy system to True (defaults to False), this leads to the model evaluating the
+      difference in the asset value at the end of the optimization horizon vs. at the time the investment was made.
+      The difference in value is added to or subtracted from the respective investment costs increment,
+      assuming assets are to be liquidated / re-evaluated at the end of the optimization horizon.
     * Also please be aware, that periods correspond to years by default. You could also choose
       monthly periods, but you would need to be very careful in parameterizing your energy system and your model and also,
       this would mean monthly discounting (if applicable) as well as specifying your plants lifetimes in months.

docs/whatsnew/v0-5-2.rst

@@ -4,15 +4,25 @@ v0.5.2 (????)
 API changes
 ###########
 
+* New bool attribute `use_remaining_value` of `oemof.solph.EnergySystem`
+
 New features
 ############
 
+* Allow for evaluating differences in the remaining vs. the original value
+  for multi-period investments.
+
 Documentation
 #############
 
 Bug fixes
 #########
 
+* Fix handling of investment annuities and fixed costs for multi-period models:
+  Limit to costs that occur within the optimization horizon to prevent a
+  bias towards investments happening earlier in the optimization horizon.
+* Fix bugs in multi-period documentation.
+
 Testing
 #######
 
@@ -25,3 +35,7 @@ Contributors
 ############
 
 * Patrik Schönfeldt
+* Johannes Kochems
+* Julian Endres
+* Hendrik Huyskens
+* Raul Ciria Aylagas

src/oemof/solph/_energy_system.py

@@ -62,6 +62,10 @@ class EnergySystem(es.EnergySystem):
         For a standard model, periods are not (to be) declared, i.e. None.
         A list with one entry is derived, i.e. [0].
 
+    use_remaining_value : bool
+        If True, compare the remaining value of an investment to the
+        original value (only applicable for multi-period models)
+
     kwargs
     """
 
@@ -71,6 +75,7 @@ def __init__(
         timeincrement=None,
         infer_last_interval=None,
         periods=None,
+        use_remaining_value=False,
         **kwargs,
     ):
         # Doing imports at runtime is generally frowned upon, but should work
@@ -160,7 +165,8 @@ def __init__(
             timeindex=timeindex, timeincrement=timeincrement, **kwargs
         )
 
-        if periods is not None:
+        self.periods = periods
+        if self.periods is not None:
             msg = (
                 "CAUTION! You specified the 'periods' attribute for your "
                 "energy system.\n This will lead to creating "
@@ -171,9 +177,10 @@ def __init__(
                 "please report them."
             )
             warnings.warn(msg, debugging.SuspiciousUsageWarning)
-        self.periods = periods
-        self._extract_periods_years()
-        self._extract_periods_matrix()
+            self._extract_periods_years()
+            self._extract_periods_matrix()
+            self._extract_end_year_of_optimization()
+            self.use_remaining_value = use_remaining_value
 
     def _extract_periods_years(self):
         """Map years in optimization to respective period based on time indices
@@ -183,13 +190,12 @@ def _extract_periods_years(self):
         start of the optimization run and starting with 0.
         """
         periods_years = [0]
-        if self.periods is not None:
-            start_year = self.periods[0].min().year
-            for k, v in enumerate(self.periods):
-                if k >= 1:
-                    periods_years.append(v.min().year - start_year)
+        start_year = self.periods[0].min().year
+        for k, v in enumerate(self.periods):
+            if k >= 1:
+                periods_years.append(v.min().year - start_year)
 
-            self.periods_years = periods_years
+        self.periods_years = periods_years
 
     def _extract_periods_matrix(self):
         """Determines a matrix describing the temporal distance to each period.
@@ -200,13 +206,41 @@ def _extract_periods_matrix(self):
         between each investment period to each decommissioning period.
         """
         periods_matrix = []
-        if self.periods is not None:
-            period_years = np.array(self.periods_years)
-            for v in period_years:
-                row = period_years - v
-                row = np.where(row < 0, 0, row)
-                periods_matrix.append(row)
-            self.periods_matrix = np.array(periods_matrix)
+        period_years = np.array(self.periods_years)
+        for v in period_years:
+            row = period_years - v
+            row = np.where(row < 0, 0, row)
+            periods_matrix.append(row)
+        self.periods_matrix = np.array(periods_matrix)
+
+    def _extract_end_year_of_optimization(self):
+        """Extract the end of the optimization in years
+
+        Attribute `end_year_of_optimization` of int is set.
+        """
+        duration_last_period = self.get_period_duration(-1)
+        self.end_year_of_optimization = (
+            self.periods_years[-1] + duration_last_period
+        )
+
+    def get_period_duration(self, period):
+        """Get duration of a period in full years
+
+        Parameters
+        ----------
+        period : int
+            Period for which the duration in years shall be obtained
+
+        Returns
+        -------
+        int
+            Duration of the period
+        """
+        return (
+            self.periods[period].max().year
+            - self.periods[period].min().year
+            + 1
+        )
 
 
 def create_time_index(