Make varying period lenghts possible

examples/cellular/cellular.py

@@ -30,14 +30,14 @@
 """
 
 
+from oemof.solph import EnergySystem
 from oemof.solph import Model
 from oemof.solph import buses
 from oemof.solph import components as cmp
-from oemof.solph import EnergySystem
-
 from oemof.solph import create_time_index
 from oemof.solph import flows
-from oemof.solph import processing, views
+from oemof.solph import processing
+from oemof.solph import views
 
 
 def main():

examples/electrical/lopf.py

@@ -31,11 +31,17 @@
 import pandas as pd
 from matplotlib import pyplot as plt
 from oemof.network.graph import create_nx_graph
-from oemof.solph import EnergySystem, Investment, Model, processing, views
-from oemof.solph.components import Sink, Source
+
+from oemof.solph import EnergySystem
+from oemof.solph import Investment
+from oemof.solph import Model
+from oemof.solph import processing
+from oemof.solph import views
 from oemof.solph.buses.experimental import ElectricalBus
-from oemof.solph.flows.experimental import ElectricalLine
+from oemof.solph.components import Sink
+from oemof.solph.components import Source
 from oemof.solph.flows import Flow
+from oemof.solph.flows.experimental import ElectricalLine
 
 try:
     import pygraphviz as pygz

examples/excel_reader/dispatch.py

@@ -41,16 +41,16 @@
 
 """
 
-import os
 import logging
-import pandas as pd
+import os
 
+import networkx as nx
+import pandas as pd
+from matplotlib import pyplot as plt
+from oemof.network.graph import create_nx_graph
 from oemof.tools import logger
-from oemof import solph
 
-from oemof.network.graph import create_nx_graph
-from matplotlib import pyplot as plt
-import networkx as nx
+from oemof import solph
 
 
 def nodes_from_excel(filename):

examples/invest_nonconvex_flow_examples/diesel_genset_nonconvex_investment.py

@@ -31,13 +31,16 @@
 __copyright__ = "oemof developer group"
 __license__ = "MIT"
 
-import numpy as np
 import os
-import pandas as pd
 import time
-from datetime import datetime, timedelta
-from oemof import solph
 import warnings
+from datetime import datetime
+from datetime import timedelta
+
+import numpy as np
+import pandas as pd
+
+from oemof import solph
 
 try:
     import matplotlib.pyplot as plt

examples/invest_nonconvex_flow_examples/house_with_nonconvex_investment.py

@@ -30,9 +30,10 @@
 
 import numpy as np
 import pandas as pd
-from oemof import solph
 from oemof.tools import economics
 
+from oemof import solph
+
 try:
     import matplotlib.pyplot as plt
 except ImportError:

examples/invest_nonconvex_flow_examples/house_without_nonconvex_investment.py

@@ -36,9 +36,10 @@
 
 import numpy as np
 import pandas as pd
-from oemof import solph
 from oemof.tools import economics
 
+from oemof import solph
+
 try:
     import matplotlib.pyplot as plt
 except ImportError:

examples/start_and_shutdown_costs/startup_shutdown.py

@@ -17,9 +17,10 @@
 `MIT license <https://github.com/oemof/oemof-solph/blob/dev/LICENSE>`_
 
 """
+import matplotlib.pyplot as plt
 import pandas as pd
+
 from oemof import solph
-import matplotlib.pyplot as plt
 
 
 def main():

examples/storage_investment/v1_invest_optimize_all_technologies.py

@@ -68,7 +68,6 @@
 import warnings
 
 import pandas as pd
-
 # Default logger of oemof
 from oemof.tools import economics
 from oemof.tools import logger

examples/storage_investment/v2_invest_optimize_only_gas_and_storage.py

@@ -68,7 +68,6 @@
 import warnings
 
 import pandas as pd
-
 # Default logger of oemof
 from oemof.tools import economics
 from oemof.tools import logger

examples/storage_investment/v3_invest_optimize_only_storage_with_fossil_share.py

@@ -67,7 +67,6 @@
 import warnings
 
 import pandas as pd
-
 # Default logger of oemof
 from oemof.tools import economics
 from oemof.tools import logger

examples/storage_investment/v4_invest_optimize_all_technologies_with_fossil_share.py

@@ -64,7 +64,6 @@
 import warnings
 
 import pandas as pd
-
 # Default logger of oemof
 from oemof.tools import economics
 from oemof.tools import logger

examples/storage_level_constraint/storage_level_constraint.py

@@ -1,12 +1,15 @@
-import pandas as pd
-from oemof.solph import Bus, EnergySystem, Flow, Model
-from oemof.solph.components import GenericStorage, Source, Sink
-from oemof.solph.processing import results
-
 import matplotlib.pyplot as plt
+import pandas as pd
 
+from oemof.solph import Bus
+from oemof.solph import EnergySystem
+from oemof.solph import Flow
+from oemof.solph import Model
+from oemof.solph.components import GenericStorage
+from oemof.solph.components import Sink
+from oemof.solph.components import Source
 from oemof.solph.constraints import storage_level_constraint
-
+from oemof.solph.processing import results
 
 es = EnergySystem(
     timeindex=pd.date_range("2022-01-01", freq="1H", periods=24),

examples/time_index_example/non_equidistant_time_step_example.py

@@ -26,6 +26,7 @@
     pip install oemof.solph
 """
 import pandas as pd
+
 from oemof import solph
 
 try:

src/oemof/solph/_energy_system.py

@@ -173,6 +173,7 @@ def __init__(
             warnings.warn(msg, debugging.SuspiciousUsageWarning)
         self.periods = periods
         self._extract_periods_years()
+        self._extract_periods_matrix()
 
     def _extract_periods_years(self):
         """Map simulation years to the respective period based on time indices
@@ -192,6 +193,26 @@ def _extract_periods_years(self):
 
             self.periods_years = periods_years
 
+    def _extract_periods_matrix(self):
+        """Determines a matrix describing the temporal distance to each period.
+        Rows represent investment/commissioning periods, columns represent
+        decommissioning periods. The values describe the temporal distance
+        between each investment period to each decommissioning period.
+
+        Returns
+        -------
+        period_distance_matrix: np.array
+
+        """
+        periods_matrix = []
+        if self.periods is not None:
+            period_years = np.array(self.periods_years)
+            for k, v in enumerate(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 create_time_index(
     year: int = None,

src/oemof/solph/_groupings.py

@@ -24,9 +24,8 @@
 
 from oemof.network import groupings as groupings
 
-from oemof.solph.flows._invest_non_convex_flow_block import (
-    InvestNonConvexFlowBlock,
-)
+from oemof.solph.flows._invest_non_convex_flow_block import \
+    InvestNonConvexFlowBlock
 from oemof.solph.flows._investment_flow_block import InvestmentFlowBlock
 from oemof.solph.flows._non_convex_flow_block import NonConvexFlowBlock
 from oemof.solph.flows._simple_flow_block import SimpleFlowBlock

src/oemof/solph/_models.py

@@ -26,9 +26,8 @@
 from oemof.solph import processing
 from oemof.solph.buses._bus import BusBlock
 from oemof.solph.components._transformer import TransformerBlock
-from oemof.solph.flows._invest_non_convex_flow_block import (
-    InvestNonConvexFlowBlock,
-)
+from oemof.solph.flows._invest_non_convex_flow_block import \
+    InvestNonConvexFlowBlock
 from oemof.solph.flows._investment_flow_block import InvestmentFlowBlock
 from oemof.solph.flows._non_convex_flow_block import NonConvexFlowBlock
 from oemof.solph.flows._simple_flow_block import SimpleFlowBlock

src/oemof/solph/components/_generic_storage.py

@@ -22,6 +22,7 @@
 import numbers
 from warnings import warn
 
+import numpy as np
 from oemof.network import network
 from oemof.tools import debugging
 from oemof.tools import economics
@@ -1232,24 +1233,75 @@ def _old_storage_capacity_rule_end(block):
                             " Value for {} is missing.".format(n)
                         )
                         raise ValueError(msg)
+                    # get the period matrix describing the temporal distance
+                    # between all period combinations. Row indexes indicating
+                    # the investment period, column indexes the decommissioning
+                    # period.
+                    periods_matrix = m.es.periods_matrix
+                    # matrix = np.where(matrix == 0, np.nan, matrix)
+
+                    # get the index of the minimum value in each row greater
+                    # equal than the lifetime. This value equals the
+                    # decommissioning period if not zero. The index of this
+                    # value represents the investment period.
+                    decomm_periods = np.argmin(
+                        np.where(
+                            (periods_matrix >= lifetime),
+                            periods_matrix,
+                            np.inf,
+                        ),
+                        axis=1,
+                    )
+
+                    # first period doesn't have any decommissioning
+                    expr = self.old_end[n, 0] == 0
+                    self.old_rule_end.add((n, 0), expr)
+
+                    # all periods not in decomm_periods have no decommissioning
                     for p in m.PERIODS:
-                        # No shutdown in first period
-                        if p == 0:
+                        if p not in decomm_periods and p != 0:
                             expr = self.old_end[n, p] == 0
                             self.old_rule_end.add((n, p), expr)
-                        elif lifetime <= m.es.periods_years[p]:
-                            # Obtain commissioning period
-                            comm_p = 0
-                            for k, v in enumerate(m.es.periods_years):
-                                if m.es.periods_years[p] - lifetime - v < 0:
-                                    # change of sign is detected
-                                    comm_p = k - 1
-                                    break
-                            expr = self.old_end[n, p] == self.invest[n, comm_p]
-                            self.old_rule_end.add((n, p), expr)
+
+                    # multiple invests can decommission in the same period
+                    # but only sequential ones, thus a memory is introduced and
+                    # constraints are added to equation one iteration later.
+                    last_decomm_p = np.nan
+                    # loop over invest periods (values are decomm_periods)
+                    for invest_p, decomm_p in enumerate(decomm_periods):
+                        # Add constraint of iteration before
+                        # (skipped in first iteration)
+                        if (decomm_p != last_decomm_p) and (
+                            last_decomm_p is not np.nan
+                        ):
+                            #
+                            expr = self.old_end[n, last_decomm_p] == expr
+                            self.old_rule_end.add((n, last_decomm_p), expr)
+
+                        # no decommissioning if decomm_p is zero
+                        if decomm_p == 0:
+                            # overwrite decomm_p memory with nan to avoid
+                            # chaining invest periods in next iteration
+                            last_decomm_p = 0
+
+                        # if decomm_p is the same as the last one chain invest
+                        # period
+                        elif decomm_p == last_decomm_p:
+                            expr += self.invest[n, invest_p]
+                            # overwrite decomm_p memory
+                            last_decomm_p = decomm_p
+
+                        # if decomm_p is not zero, not the same as the last one,
+                        # and it's not the first period
                         else:
-                            expr = self.old_end[n, p] == 0
-                            self.old_rule_end.add((n, p), expr)
+                            expr = self.invest[n, invest_p]
+                            # overwrite decomm_p memory
+                            last_decomm_p = decomm_p
+
+                    if last_decomm_p != 0:
+                        # Add constraint of last iteration
+                        expr = self.old_end[n, last_decomm_p] == expr
+                        self.old_rule_end.add((n, last_decomm_p), expr)
 
             self.old_rule_end = Constraint(
                 self.INVESTSTORAGES, m.PERIODS, noruleinit=True

src/oemof/solph/flows/_flow.py

@@ -244,9 +244,9 @@ def __init__(
                     the_attr = eval(attr)
                 if the_attr is not None:
                     raise AttributeError(
-                        "If {} is set in a flow (except InvestmentFlow), "
+                        f"If {attr} is set in a flow (except InvestmentFlow), "
                         "nominal_value must be set as well.\n"
-                        "Otherwise, it won't have any effect.".format(attr)
+                        "Otherwise, it won't have any effect."
                     )
         # minimum will be set even without nominal limit