diff --git a/.gitignore b/.gitignore
index f63add8..54d8aa3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,3 +7,6 @@ __pycache__/
 /tests/_files/tabular_datapackage_hack_a_thon/data/
 /tests/_files/tabular_datapackage_hack_a_thon/datapackage.json
 /tests/_files/tabular_datapackage_mininmal_example/
+/tests/_files/tsam/*
+/examples/industry/collections/*
+/examples/industry/datapackage/*
diff --git a/data_adapter_oemof/adapters.py b/data_adapter_oemof/adapters.py
index 9f719a8..4c1e7b7 100644
--- a/data_adapter_oemof/adapters.py
+++ b/data_adapter_oemof/adapters.py
@@ -10,6 +10,7 @@
 from oemof.tabular import facades
 from oemof.tabular._facade import Facade
 from oemof_industry.mimo_converter import MIMO
+from oemof_industry.emission_constraint import CO2EmissionLimit
 
 from data_adapter_oemof import calculations
 
@@ -35,6 +36,7 @@ class Adapter:
         Field(name="name", type=str),
         Field(name="region", type=str),
         Field(name="year", type=int),
+        Field(name="full_load_time_max", type=float),
     )
     output_parameters = (Field(name="max", type=float), Field(name="min", type=float))
     input_parameters = ()
@@ -158,7 +160,10 @@ def get_data(self, key, field_type: Optional[Type] = None):
                     f"Using existing timeseries column '{timeseries_key}'."
                 )
                 return timeseries_key
-            logger.warning(f"Could not find timeseries entry for mapped key '{key}'")
+            logger.warning(
+                f"For Process {self.process_name}"
+                f"Could not find timeseries entry for mapped key '{key}'"
+            )
             return None
 
         # 2 Use defaults
@@ -213,11 +218,12 @@ def get_busses(self) -> dict:
         bus_dict = {}
         for bus in bus_occurrences_in_fields:  # emission_bus
             # 1. Check for existing mappings
-            try:
-                bus_dict[bus] = self.bus_map[self.__class__.__name__][bus]
-                continue
-            except KeyError:
-                pass
+            if self.bus_map:
+                try:
+                    bus_dict[bus] = self.bus_map[self.__class__.__name__][bus]
+                    continue
+                except KeyError:
+                    pass
 
             # TODO: Make use of Parameter [stuct.csv]?
             # Do we need parameter specific Bus structure? Maybe for multiple in/output?
@@ -236,6 +242,11 @@ def get_busses(self) -> dict:
                     busses = struct["inputs"]
                 if bus == "to_bus":
                     busses = struct["outputs"]
+                if (
+                    self.__class__.type == "storage"
+                    and struct["inputs"] == struct["outputs"]
+                ):
+                    busses = struct["outputs"]
                 if len(busses) != 1:
                     raise MappingError(
                         f"Could not map {bus} to default bus - too many options"
@@ -326,25 +337,68 @@ def default_pre_mapping_calculations(self):
 
         """
         calculations.normalize_activity_bonds(self)
+        calculations.process_availability_constant_to_full_load_time_max(self)
 
     def default_post_mapping_calculations(self, mapped_defaults):
         """
         Does default calculations#
 
-        I. Decommissioning of existing Capacities
-        II. Rounding lifetime down to integers
+        I. Decommissioning of existing Capacities (processes _0) and add
+            `expandable = True` if process is expandable (_1, _2, not _0)
+        II. Reformatting of amount in case amount is not a number
+            a) Multiply timeseries by the repeoctiv yearly amount
+            b) Analogous to decommissioning of capacities
+        III. Rounding lifetime down to integers
 
         Returns
         -------
 
         """
+        if mapped_defaults["type"] == "mimo":
+            parameter_name = f"flow_share_max_{mapped_defaults['primary']}"
+        elif len(self.structure["outputs"]) == 0:
+            parameter_name = "input_parameters"
+        else:
+            parameter_name = "output_parameters"
+
         # I:
         if self.process_name[-1] == "0":
             mapped_defaults = calculations.decommission(
-                process_name=self.process_name, adapter_dict=mapped_defaults
+                process_name=self.process_name,
+                adapter_dict=mapped_defaults,
+                column="capacity",
+                change_parameter=parameter_name,
             )
+        elif self.process_name[-1] == "1" or self.process_name[-1] == "2":
+            mapped_defaults["expandable"] = True
+        elif "x2x_other_biogas_treatment" in self.process_name:
+            mapped_defaults["expandable"] = True
+            logging.warning(
+                "Setting capacity cost of x2x_other_biogas_treatment to 0 and "
+                "life time to 20 as this is missing in the data.")
+            mapped_defaults["capacity_cost"] = 0
+            mapped_defaults["lifetime"] = 20
 
         # II:
+        if "amount" in mapped_defaults.keys():
+            # a)
+            if "profile" in mapped_defaults.keys():
+                self.timeseries = calculations.adapt_profile_with_yearly_value(
+                    profile=self.timeseries,
+                    value=mapped_defaults["amount"]
+                )
+                mapped_defaults["amount"] = 1
+
+            # b)
+            else:
+                mapped_defaults = calculations.decommission(
+                    process_name=self.process_name,
+                    adapter_dict=mapped_defaults,
+                    column="amount",
+                    change_parameter=parameter_name,
+                )
+
+        # III:
         if "lifetime" in mapped_defaults.keys():
             mapped_defaults = calculations.floor_lifetime(mapped_defaults)
 
@@ -420,6 +474,53 @@ def get_default_parameters(
         if self.get("carrier") == "carrier":
             defaults["carrier"] = self.get_busses()["bus"]
 
+        if self.get("amount") == None:
+            amount = 9999999999999
+            logger.warning(
+                f"Adding parameter 'amount' with value {amount} to commodity "
+                f"{self.process_name}. \n         "
+                f"This is beneficial if your commodity is functioning as "
+                f"shortage or unlimited import/source. "
+                f"Otherwise please add 'amount' to your commodity!"
+            )
+            defaults["amount"] = amount
+
+        return defaults
+
+
+class CommodityGHGAdapter(CommodityAdapter):
+    """
+    CommodityGHGAdapter
+    """
+
+    type = "commodity_ghg"
+    facade = facades.CommodityGHG
+
+    def get_busses(self) -> dict:
+        bus_list = self.structure["outputs"]
+        bus_dict = {}
+        counter = 0
+        for bus in bus_list:
+            if not bus.startswith("emi"):
+                bus_dict["bus"] = bus
+            elif bus.startswith("emi"):
+                bus_dict[f"emission_bus_{counter}"] = bus
+                counter += 1
+        return bus_dict
+
+    def get_default_parameters(self) -> dict:
+        defaults = super().get_default_parameters()
+        for key, value in self.data.items():
+            if key.startswith("ef"):
+                # adapt to the naming convention in oemof.tabular commodityGHG facade: emission_factor_<emission_bus_label>
+                target_label = None
+                emission_bus_labels = [key for item, key in defaults.items() if item.startswith("emission_bus")]
+                for label in emission_bus_labels:
+                    if label in key:
+                        target_label = label
+                if target_label == None:
+                    raise ValueError(f"Emission factor of {self.process_name} is named {key} but None of the emission buses matches: {emission_bus_labels}.")
+                defaults[f"emission_factor_{target_label}"] = value
         return defaults
 
 
@@ -433,6 +534,44 @@ class ConversionAdapter(Adapter):
     facade = facades.Conversion
 
 
+class ConversionGHGAdapter(Adapter):
+    """
+    ConversionGHGAdapter
+    """
+
+    type = "conversion_ghg"
+    facade = facades.ConversionGHG
+
+    def get_busses(self) -> dict:
+        def get_bus_from_struct(bus_list: list, bus_key: str) -> dict:
+            bus_dict = {}
+            counter = 0
+            for bus in bus_list:
+                if not bus.startswith("emi"):
+                    bus_dict[f"{bus_key}"] = bus
+                elif bus.startswith("emi"):
+                    bus_dict[f"emission_bus_{counter}"] = bus
+                    counter += 1
+            return bus_dict
+
+        return_bus_dict = get_bus_from_struct(
+            self.structure["inputs"], bus_key="from_bus"
+        ) | get_bus_from_struct(self.structure["outputs"], bus_key="to_bus")
+
+        # check that from_bus and to_bus is defined
+        for key in ["from_bus", "to_bus"]:
+            if return_bus_dict.get(key) is None:
+                raise KeyError(f"{self.process_name} is missing {key}.")
+        return return_bus_dict
+
+    def get_default_parameters(self) -> dict:
+        defaults = super().get_default_parameters()
+        for key, value in self.data.items():
+            if key.startswith("ef"):
+                defaults[key.replace("ef", "emission_factor")] = value
+        return defaults
+
+
 class LoadAdapter(Adapter):
     """
     LoadAdapter
@@ -474,6 +613,44 @@ class VolatileAdapter(Adapter):
     facade = facades.Volatile
 
 
+class EmissionConstraintAdapter(Adapter):
+    """
+    EmissionConstraintAdapter
+    """
+
+    type = "co2_emission_limit"
+    facade = CO2EmissionLimit  # oemof.industry facade - might be moved to oemof.tabular
+    extra_fields = Adapter.extra_fields + (
+        Field(name="commodities", type=float),
+    )
+
+    def get_default_parameters(self) -> dict:
+        defaults = super().get_default_parameters()
+        del defaults["region"]
+        del defaults["name"]
+        del defaults["year"]
+        # reduce co2 limit by share of steel industry
+        defaults["co2_limit"] = [limit * self.data["steel_emission_share"] for
+                                 limit in defaults["co2_limit"]]
+
+        # categorize commodities
+        commodities = {"co2_commodities": [], "ch4_commodities": [],
+                       "n2o_commodities": [], "negative_co2_commodities": []}
+        inputs = self.structure["inputs"]
+        for i in inputs:
+            if "neg" in i and "co2" in i:
+                commodities["negative_co2_commodities"].append(i)
+            elif "co2" in i:
+                commodities["co2_commodities"].append(i)
+            elif "ch4" in i:
+                commodities["ch4_commodities"].append(i)
+            elif "n2o" in i:
+                commodities["n2o_commodities"].append(i)
+        # replace quotes with # to make a json.loads easier later
+        defaults["commodities"] = json.dumps(commodities).replace('"', "#")
+        return defaults
+
+
 class MIMOAdapter(Adapter):
     """
     MIMOAdapter
@@ -485,25 +662,19 @@ class MIMOAdapter(Adapter):
         Field(name="name", type=str),
         Field(name="region", type=str),
         Field(name="year", type=int),
+        Field(name="full_load_time_max", type=float),
         Field(name="groups", type=dict),
+        Field(name="lifetime", type=float),
         Field(name="capacity_cost", type=float),
         Field(name="capacity", 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),
+        Field(name="primary", type=str),
     )
     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()
         defaults["groups"] = self.get_groups()
@@ -512,10 +683,13 @@ def get_default_parameters(self) -> dict:
             "emissions_factor_",
             "conversion_factor_",
             "flow_share_",
+            "ef_",
         )
         for key, value in self.data.items():
             for keyword in keywords:
                 if key.startswith(keyword):
+                    if key.startswith("ef"):
+                        key = key.replace("ef", "emission_factor")
                     defaults[key] = value
         return defaults
 
@@ -524,6 +698,8 @@ def get_bus_from_struct(bus_list: list, prefix: str) -> dict:
             buses = {}
             counter = 0
             for bus_group in bus_list:
+                if prefix == "to_bus_" and counter == 0:
+                    buses["primary"] = bus_group
                 if isinstance(bus_group, str):
                     buses[f"{prefix}{counter}"] = bus_group
                     counter += 1
diff --git a/data_adapter_oemof/build_datapackage.py b/data_adapter_oemof/build_datapackage.py
index 28c65bf..4d7d0e3 100644
--- a/data_adapter_oemof/build_datapackage.py
+++ b/data_adapter_oemof/build_datapackage.py
@@ -1,4 +1,5 @@
 import dataclasses
+import logging
 import os
 import warnings
 from typing import Optional, Type
@@ -11,10 +12,12 @@
 
 from data_adapter_oemof.adapters import FACADE_ADAPTERS
 from data_adapter_oemof.adapters import Adapter as FacadeAdapter
-from data_adapter_oemof.calculations import handle_nans
+from data_adapter_oemof.calculations import handle_nans, reduce_data_frame
 from data_adapter_oemof.settings import BUS_MAP, PARAMETER_MAP, PROCESS_ADAPTER_MAP
 from data_adapter_oemof.utils import convert_mixed_types_to_same_length
 
+logger = logging.getLogger()
+
 
 # Define a function to aggregate differing values into a list
 def _listify_to_periodic(group_df) -> pd.Series:
@@ -77,7 +80,6 @@ def _listify_to_periodic(group_df) -> pd.Series:
                 unique_values[col] = group_df[col].iat[0][0]
             else:
                 unique_values[col] = group_df[col].iat[0]
-    unique_values["name"] = "_".join(group_df.name)
     unique_values.drop("year")
     return unique_values
 
@@ -95,6 +97,7 @@ class DataPackage:
     periods: pd.DataFrame()
     location_to_save_to: str = None
     tsa_parameters: pd.DataFrame = None
+    constraint_parameters: pd.DataFrame = None
 
     @staticmethod
     def __split_timeseries_into_years(parametrized_sequences):
@@ -247,12 +250,22 @@ def save_datapackage_to_csv(
         sequences_path = os.path.join(location_to_save_to, "data", "sequences")
         periods_path = os.path.join(location_to_save_to, "data", "periods")
         tsam_path = os.path.join(location_to_save_to, "data", "tsam")
+        constraint_path = os.path.join(location_to_save_to, "data", "constraints")
 
         os.makedirs(elements_path, exist_ok=True)
         os.makedirs(sequences_path, exist_ok=True)
         os.makedirs(periods_path, exist_ok=True)
         os.makedirs(tsam_path, exist_ok=True)
 
+
+        if self.constraint_parameters is not None:
+            os.makedirs(constraint_path, exist_ok=True)
+            self.constraint_parameters.to_csv(
+                os.path.join(constraint_path, "emission_constraint.csv"),
+                index=False,
+                sep=";",
+            )
+
         if not self.periods.empty:
             self.periods.to_csv(
                 os.path.join(
@@ -295,6 +308,12 @@ def save_datapackage_to_csv(
             field_names = [field["name"] for field in resource["schema"]["fields"]]
             resource["dialect"] = {"delimiter": ";"}
             if resource["name"] in self.foreign_keys.keys():
+                # drop "primary", see mimo converter of oemof.industry for more information
+                self.foreign_keys[resource["name"]] = [
+                    item for item in self.foreign_keys[resource["name"]] if
+                    item["fields"] != "primary"
+                ]
+                # update schema
                 resource["schema"].update(
                     {"foreignKeys": self.foreign_keys[resource["name"]]}
                 )
@@ -450,6 +469,7 @@ def build_datapackage(
         parameter_map: Optional[dict] = PARAMETER_MAP,
         bus_map: Optional[dict] = BUS_MAP,
         location_to_save_to: str = None,
+        debug=False,
     ):
         """
         Creating a Datapackage from the oemof_data_adapter that fits oemof.tabular Datapackages.
@@ -473,6 +493,9 @@ def build_datapackage(
         -------
         DataPackage
 
+        units : dict
+            keys: process names, values: dict containing parameters for
+            optimization as keys and units as values.
         """
 
         def _reduce_lists(x):
@@ -484,9 +507,12 @@ def _reduce_lists(x):
         parametrized_elements = {"bus": []}
         parametrized_sequences = {}
         foreign_keys = {}
+        constraint_parameters = None
+        units = {}
         # Iterate Elements
         for process_name, struct in adapter.structure.processes.items():
             process_data = adapter.get_process(process_name)
+            units[process_name] = process_data.units
             timeseries = process_data.timeseries
             if isinstance(timeseries.columns, pd.MultiIndex):
                 timeseries.columns = (
@@ -495,6 +521,9 @@ def _reduce_lists(x):
                     + _reduce_lists(timeseries.columns.get_level_values(1))
                 )
             facade_adapter_name: str = process_adapter_map[process_name]
+            logger.info(
+                f"Adaptering process {process_name} into adapter {facade_adapter_name}"
+            )
             facade_adapter: Type[FacadeAdapter] = FACADE_ADAPTERS[facade_adapter_name]
             component_adapter: Optional[FacadeAdapter] = None
             components = []
@@ -527,9 +556,12 @@ def _reduce_lists(x):
                 component_adapter, components
             )
 
-            parametrized_elements[process_name] = pd.DataFrame(components)
-            if not timeseries.empty:
-                parametrized_sequences.update({process_name: timeseries})
+            if "constraint" in process_name:
+                constraint_parameters = pd.DataFrame(components)
+            else:
+                parametrized_elements[process_name] = pd.DataFrame(components)
+                if not timeseries.empty:
+                    parametrized_sequences.update({process_name: timeseries})
         # Create Bus Element from all unique `busses` found in elements
         parametrized_elements["bus"] = pd.DataFrame(
             {
@@ -540,6 +572,12 @@ def _reduce_lists(x):
         )
         periods = cls.get_periods_from_parametrized_sequences(parametrized_sequences)
 
+        if debug:
+            periods = reduce_data_frame(data_frame=periods)
+            for key, value in parametrized_sequences.items():
+                df_short = reduce_data_frame(data_frame=value)
+                parametrized_sequences.update({key: df_short})
+
         return cls(
             parametrized_elements=parametrized_elements,
             parametrized_sequences=parametrized_sequences,
@@ -547,4 +585,5 @@ def _reduce_lists(x):
             foreign_keys=foreign_keys,
             periods=periods,
             location_to_save_to=location_to_save_to,
-        )
+            constraint_parameters=constraint_parameters,
+        ), units
diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py
index c190b60..3b3e7d3 100644
--- a/data_adapter_oemof/calculations.py
+++ b/data_adapter_oemof/calculations.py
@@ -1,6 +1,7 @@
 import collections
 import logging
 import warnings
+import json
 
 import numpy as np
 import pandas as pd
@@ -44,7 +45,9 @@ 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:
+def decommission(
+    process_name, adapter_dict: dict, column: str = "capacity", max_column: str = "max", change_parameter: str = "output_parameters",
+) -> dict:
     """
 
     Takes adapter dictionary from adapters.py with mapped values.
@@ -74,38 +77,86 @@ def decommission(process_name, adapter_dict: dict) -> dict:
     -------
 
     """
-    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():
+    if column not in adapter_dict.keys():
         logging.info(
-            f"Capacity missing for decommissioning " f"of Process `{process_name}`"
+            f"{column} missing for decommissioning " f"of Process `{process_name}`"
         )
         return adapter_dict
 
-    if not isinstance(adapter_dict[capacity_column], list):
+    if not isinstance(adapter_dict[column], list):
         logging.info(
-            f"No capacity fading out that can be decommissioned"
+            f"No {column} 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:
+    if change_parameter not in ["input_parameters", "output_parameters"]:
+        # this occurs e.g. for flow_share_max of mimo
+        # still max might be set in parameters
+        parameter = "output_parameters"
     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])
+        parameter = change_parameter
+    if max_column not in adapter_dict[parameter].keys():
+        max = list(adapter_dict[column] / np.nanmax(adapter_dict[column]))
 
-    adapter_dict[capacity_column] = np.max(adapter_dict[capacity_column])
+    # II:
+    else:
+        max = list(multiply_two_lists(
+                adapter_dict[parameter][max_column],
+                adapter_dict[column]
+            ) / np.nanmax(adapter_dict[column]))
+        if change_parameter != parameter:
+            # drop max output_parameters, as max_column is saved in `change_parameter`
+            del adapter_dict[parameter][max_column]
+
+    if change_parameter != parameter:
+        # e.g. flow_share_max_<bus_name>
+        adapter_dict[change_parameter] = max
+    else:
+        # max must be extended to time series over all time steps of each
+        # period as output_parameters are not extended in oemof.tabular
+        column_name = [f"max_timeseries_{process_name}"]
+        timeseries = pd.DataFrame(columns=column_name)
+        for y in adapter_dict["year"]:
+            ts = pd.DataFrame(data=[1 for i in range(8760)],
+                              columns=column_name,
+                              index=pd.date_range(f"1/1/{y}", periods=8760,
+                                                  freq="h"),
+                              dtype="float64")
+            timeseries = ts.copy() if timeseries.empty else pd.concat(
+                [timeseries, ts])
+        max_time_series = adapt_profile_with_yearly_value(profile=timeseries,
+                                                          value=max)
+
+        max_time_series = reduce_data_frame(max_time_series)
+
+        adapter_dict[change_parameter][max_column] = list(max_time_series[column_name[0]].values)
+        adapter_dict[change_parameter] = json.dumps(adapter_dict[change_parameter])
+
+    # set `column` value to maximum value
+    adapter_dict[column] = np.nanmax(adapter_dict[column])
     return adapter_dict
 
 
+def adapt_profile_with_yearly_value(profile, value):
+
+    # Map amount to years
+    years = sorted(profile.index.year.unique())
+    values_mapped_to_years = dict(zip(years, value))
+
+    profile["value"] = profile.index.year.map(values_mapped_to_years)
+
+    # Multiply profile with value
+    col_name = profile.columns[0]
+    profile["adjusted_ts"] = (profile[col_name] * profile["value"])
+    profile.drop(columns=[col_name, "value"], inplace=True)
+    profile.rename(columns={"adjusted_ts": col_name}, inplace=True)
+
+    return profile
+
 def normalize_activity_bonds(adapter):
     """
     Normalizes activity bonds in order to be used as min/max values
@@ -137,6 +188,15 @@ def normalize_activity_bonds(adapter):
         return adapter
 
 
+def process_availability_constant_to_full_load_time_max(adapter):
+    """ Calculate full load time max from availability constant."""
+    if "availability_constant" in adapter.data.keys():
+        availability_constant = adapter.data["availability_constant"]
+        if availability_constant > 1:  # assumption: then the unit is %
+            availability_constant = availability_constant / 100
+        adapter.data["full_load_time_max"] = 8760 * availability_constant
+
+
 def floor_lifetime(mapped_defaults):
     """
 
@@ -317,3 +377,15 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame:
 
     group_df = handle_min_max(group_df)
     return find_and_replace_irrelevant_data(group_df)
+
+
+def reduce_data_frame(data_frame, steps=23):
+    """reduces `df` to less time steps per period"""
+    df = data_frame.copy()
+    df["ind"] = df.index
+    df["ind"] = df["ind"].apply(
+        lambda
+            x: True if x.month == 1 and x.day == 1 and x.hour <= steps else False
+    )
+    df_reduced = df.loc[df["ind"] == 1].drop(columns=["ind"])
+    return df_reduced
diff --git a/data_adapter_oemof/settings.py b/data_adapter_oemof/settings.py
index aea3add..3f93fa2 100644
--- a/data_adapter_oemof/settings.py
+++ b/data_adapter_oemof/settings.py
@@ -1,3 +1,4 @@
+import logging
 import os
 import pathlib
 from pathlib import Path
@@ -36,3 +37,45 @@
     Path(__file__).parent / "mappings" / "PROCESS_ADAPTER_MAP.yaml"
 )
 BUS_MAP = load_yaml(Path(__file__).parent / "mappings" / "BUS_MAP.yaml")
+
+
+class CustomFormatter(logging.Formatter):
+    """Logging colored formatter, adapted from https://stackoverflow.com/a/56944256/3638629"""
+
+    grey = "\x1b[38;21m"
+    blue = "\x1b[38;5;39m"
+    yellow = "\x1b[38;5;226m"
+    red = "\x1b[38;5;196m"
+    bold_red = "\x1b[31;1m"
+    reset = "\x1b[0m"
+    green = "'\x1b[38;5;82m'"
+
+    def __init__(self, fmt):
+        super().__init__()
+        self.fmt = fmt
+        self.FORMATS = {
+            logging.DEBUG: self.grey + self.fmt + self.reset,
+            logging.INFO: self.green + self.fmt + self.reset,
+            logging.WARNING: self.yellow + self.fmt + self.reset,
+            logging.ERROR: self.red + self.fmt + self.reset,
+            logging.CRITICAL: self.bold_red + self.fmt + self.reset,
+        }
+
+    def format(self, record):
+        log_fmt = self.FORMATS.get(record.levelno)
+        formatter = logging.Formatter(log_fmt)
+        return formatter.format(record)
+
+
+logger = logging.getLogger()
+logger.setLevel(logging.INFO)
+
+console_handler = logging.StreamHandler()
+console_handler.setLevel(logging.INFO)
+
+formatter = CustomFormatter("%(levelname)s: %(message)s")
+console_handler.setFormatter(formatter)
+
+logger.addHandler(console_handler)
+
+# Initialize logging configuration
diff --git a/examples/industry/collections/.gitkeep b/examples/industry/collections/.gitkeep
new file mode 100644
index 0000000..e69de29
diff --git a/examples/industry/data_adapter_industry.py b/examples/industry/data_adapter_industry.py
index 356c3f6..39b3f9d 100644
--- a/examples/industry/data_adapter_industry.py
+++ b/examples/industry/data_adapter_industry.py
@@ -1,10 +1,11 @@
+import logging
 import pathlib
 
 import pandas as pd
 from data_adapter.databus import download_collection  # noqa
 from data_adapter.preprocessing import Adapter  # noqa: E402
 from data_adapter.structure import Structure  # noqa: E402
-from oemof.solph import Model
+from oemof.solph import Model, processing
 from oemof.solph._energy_system import EnergySystem
 from oemof.solph.buses import Bus
 from oemof.tabular.datapackage import building  # noqa F401
@@ -12,23 +13,51 @@
     deserialize_constraints,
     deserialize_energy_system,
 )
-from oemof.tabular.facades import Commodity, Conversion, Excess, Load, Volatile
+from oemof.tabular.facades import (
+    Commodity,
+    Conversion,
+    Excess,
+    Load,
+    Volatile,
+    Storage,
+    ConversionGHG,
+    CommodityGHG,
+)
 from oemof_industry.mimo_converter import MIMO
 
 from data_adapter_oemof.build_datapackage import DataPackage  # noqa: E402
 
+logger = logging.getLogger()
+
 EnergySystem.from_datapackage = classmethod(deserialize_energy_system)
 
 Model.add_constraints_from_datapackage = deserialize_constraints
-#
-# Download Collection
-# Due to Nan values in "ind_scalar" type column datapackage.json must be adjusted after download
+
+DEBUG = True  # set to False for full run. DEBUG reduces to 5 time steps per period
+
+"""
+Download Collection
+
+Some datasets must be adjusted due to wrong formatting in comments
+    - x2x_import_hydrogen_renewable
+    - x2x_p2gas_aec_1
+    - x2x_p2gas_pemec_1
+    - x2x_x2gas_mpyr_1
+
+
+Also adjust Modelstructure:
+    Delete lines:
+        - helper sinks in HelperO1
+        - red marked lines in ProcessO1 (not yet uploaded or deleted data)
+"""
 
 # from data_adapter.databus import download_collection
+#
 # download_collection(
-#          "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/"
-#      )
+#     "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/"
+# )
 
+logger.info("Reading Structure")
 structure = Structure(
     "SEDOS_Modellstruktur",
     process_sheet="Processes_O1",
@@ -41,7 +70,9 @@
     structure=structure,
 )
 
-# create dicitonary with all found in and outputs
+logger.info("Building Adapter Map")
+
+# create dictionary with all found in- and outputs
 process_adapter_map = pd.concat(
     [
         pd.read_excel(
@@ -59,9 +90,8 @@
     ]
 ).to_dict(orient="dict")["facade adapter (oemof)"]
 
-
 parameter_map = {
-    "DEFAULT": {},
+    "DEFAULT": {"interest_rate": "wacc"},
     "StorageAdapter": {
         "capacity_potential": "expansion_limit",
         "capacity": "installed_capacity",
@@ -69,23 +99,213 @@
         "inflow_conversion_factor": "input_ratio",
         "outflow_conversion_factor": "output_ratio",
     },
-    "MIMOAdapter": {
-        "capacity_cost": "cost_fix_capacity_w",
-        "capacity": "capacity_w_resid",
-        "expandable": "capacity_w_abs_new_max",
+    "CommodityAdapter": {},
+    "x2x_import_biogas": {"amount": "capacity_w_inst_0", "marginal_cost": "cost_var_e"},
+    "x2x_import_coal": {"amount": "capacity_w_inst_0", "marginal_cost": "cost_var_e"},
+    "x2x_import_hydrogen_renewable": {
+        "amount": "capacity_w_inst_0",
+        "marginal_cost": "cost_var_e",
+    },
+    "x2x_other_biogas_treatment": {"marginal_cost": "cost_var_e"},
+    "ind_source_steel_scrap_iron": {"amount": "capacity_w_inst_0"},
+    "ind_steel_sinter_0": {"capacity": "capacity_w_inst_0"},
+    "ind_steel_coke_plant_0": {"capacity": "capacity_e_inst_0"},
+    "ind_steel_blafu_0": {"capacity": "capacity_w_inst_0"},
+    "ind_steel_oxyfu_0": {"capacity": "capacity_w_inst_0"},
+    "ind_steel_casting_0": {"capacity": "capacity_w_inst_0"},
+    "ind_steel_elefu_0": {"capacity": "capacity_w_inst_0"},
+    "x2x_delivery_methane_pipeline_0": {
+        "capacity": "capacity_p_max",
+        "marginal_cost": "cost_var_p",
+    },
+    "x2x_x2gas_sr_syngas_0": {
+        "capacity": "capacity_p_inst",
+        "capacity_cost": "cost_inv_p",
+        "fixed_costs": "cost_fix_p",
+    },
+    "ind_steel_coke_plant_1": {
+        "capacity_potential": "capacity_e_abs_new_max",
+        "capacity_cost": "cost_inv_e",
+        "fixed_costs": "cost_fix_e",
+        "marginal_cost": "cost_var_e",
+    },
+    "ind_steel_sinter_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+    },
+    "ind_steel_blafu_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+    },
+    "ind_steel_blafu_cc_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+    },
+    "ind_steel_oxyfu_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+        # "max":"availability_constant"
+    },
+    "ind_steel_casting_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+        # "max":"availability_constant"
+    },
+    "ind_steel_elefu_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+        # "max":"availability_constant"
+    },
+    "ind_steel_dirred_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+        # "max":"availability_constant"
+    },
+    "ind_steel_sponge_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+        # "max":"availability_constant"
+    },
+    "ind_steel_pellet_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+        # "max":"availability_constant"
+    },
+    "ind_steel_hyddri_1": {
+        "capacity_potential": "capacity_w_abs_new_max",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+        "marginal_cost": "cost_var_w",
+        # "max":"availability_constant"
+    },
+    "x2x_delivery_hydrogen_pipeline_retrofit_1": {
+        "capacity_potential": "capacity_p_max",
+        "capacity_cost": "cost_inv_p",
+        "fixed_costs": "cost_fix_p",
+        "marginal_cost": "cost_var_p",
+    },
+    "x2x_delivery_hydrogen_pipeline_new_1": {
+        "capacity_cost": "cost_inv_p",
+        "fixed_costs": "cost_fix_p",
+    },
+    "x2x_g2p_pemfc_ls_1": {
+        "capacity_cost": "cost_inv_p",
+        "fixed_costs": "cost_fix_p",
+    },
+    "x2x_g2p_sofc_ls_1": {
+        "capacity_cost": "cost_inv_p",
+        "fixed_costs": "cost_fix_p",
+    },
+    "x2x_other_dac_ht_1": {
+        "marginal_cost": "cost_var_w",
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+    },
+    "x2x_other_dac_lt_1": {
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+    },
+    "x2x_p2gas_aec_1": {
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+    },
+    "x2x_p2gas_pemec_1": {
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+    },
+    "x2x_p2gas_biom_1": {
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+    },
+    "x2x_p2gas_sabm_1": {
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+    },
+    "x2x_p2gas_soec_1": {
+        "capacity_cost": "cost_inv_w",
+        "fixed_costs": "cost_fix_w",
+    },
+    "x2x_x2gas_mpyr_1": {
+        "capacity_cost": "cost_inv_p",
+        "fixed_costs": "cost_fix_p",
+        "marginal_cost": "cost_var_e",
+    },
+    "x2x_x2gas_sr_syngas_1": {
+        "capacity_cost": "cost_inv_p",
+        "fixed_costs": "cost_fix_p",
+    },
+    "x2x_storage_hydrogen_lohc_1": {
+        "efficiency": "efficiency_sto_in",
+        "fixed_costs": "cost_fix_w",
+        "loss_rate": "sto_self_discharge",
+        "storage_capacity_cost": "cost_inv_e",
+        "fixed_costs": "cost_fix_p",
+        "marginal_cost": "cost_var_e",
+    },
+    "x2x_storage_hydrogen_new_1": {
+        "efficiency": "efficiency_sto_in",
+        "loss_rate": "sto_self_discharge",
+        "storage_capacity_cost": "cost_inv_e",
+        "fixed_costs": "cost_fix_w",
+        "fixed_costs": "cost_fix_p",
+        "marginal_cost": "cost_var_e",
+        "capacity_capacity_potential": "capacity_e_max",
+    },
+    "x2x_storage_hydrogen_retrofit_1": {
+        "efficiency": "efficiency_sto_in",
+        "fixed_costs": "cost_fix_p",
+        "loss_rate": "sto_self_discharge",
+        "storage_capacity_cost": "cost_inv_e",
+        "fixed_costs": "cost_fix_p",
+        "marginal_cost": "cost_var_e",
+        "capacity_capacity_potential": "capacity_e_max",
+        "storage_capacity": "capacity_e_inst",
+    },
+    "x2x_storage_methane_0": {
+        "efficiency": "efficiency_sto_in",
+        "fixed_costs": "cost_fix_p",
+        "loss_rate": "sto_self_discharge",
+        "storage_capacity_cost": "cost_inv_e",
+        "fixed_costs": "cost_fix_p",
+        "marginal_cost": "cost_var_e",
+        "capacity_capacity_potential": "capacity_e_max",
+        "storage_capacity": "capacity_e_inst",
+    },
+    "helper_sink_exo_steel": {
+        "profile": "demand_timeseries_fixed",
+        "amount": "demand_annual",
     },
-    "modex_tech_wind_turbine_onshore": {"profile": "onshore"},
 }
-
+logger.info("Building datapackage...")
 dp = DataPackage.build_datapackage(
     adapter=adapter,
     process_adapter_map=process_adapter_map,
     parameter_map=parameter_map,
+    debug=DEBUG,  # set DEBUG to False for full run. DEBUG reduces to 5 time steps per period
 )
 datapackage_path = pathlib.Path(__file__).parent / "datapackage"
 dp.save_datapackage_to_csv(str(datapackage_path))
 
 
+logger.info("Building EnergySystem")
 es = EnergySystem.from_datapackage(
     path="datapackage/datapackage.json",
     typemap={
@@ -96,8 +316,18 @@
         "load": Load,
         "volatile": Volatile,
         "mimo": MIMO,
+        "storage": Storage,
+        "conversion_ghg": ConversionGHG,
+        "commodity_ghg": CommodityGHG,
     },
 )
 
+logger.info("Building Model...")
 m = Model(es)
-m.solve()
+logger.info("Solving Model...")
+m.solve(solver="cbc")
+logger.warning(m.solver_results["Solver"][0]["Termination condition"])
+print(m.solver_results["Solver"][0]["Termination condition"])
+logger.info("Reding Results")
+results = processing.results(m)
+logger.info("Writing Results and Goodbye :)")
diff --git a/examples/industry/datapackage/.gitkeep b/examples/industry/datapackage/.gitkeep
new file mode 100644
index 0000000..e69de29
diff --git a/examples/industry/structures/SEDOS_Modellstruktur_sh_test.xlsx b/examples/industry/structures/SEDOS_Modellstruktur_sh_test.xlsx
new file mode 100755
index 0000000..c3d8367
Binary files /dev/null and b/examples/industry/structures/SEDOS_Modellstruktur_sh_test.xlsx differ
diff --git a/poetry.lock b/poetry.lock
index e201d35..6529c9f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -32,38 +32,38 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p
 
 [[package]]
 name = "bcrypt"
-version = "4.1.3"
+version = "4.2.0"
 description = "Modern password hashing for your software and your servers"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
@@ -183,13 +183,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2024.6.2"
+version = "2024.7.4"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [[package]]
@@ -463,43 +463,38 @@ toml = ["tomli"]
 
 [[package]]
 name = "cryptography"
-version = "42.0.8"
+version = "43.0.0"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -512,12 +507,12 @@ nox = ["nox"]
 pep8test = ["check-sdist", "click", "mypy", "ruff"]
 sdist = ["build"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
+test = ["certifi", "cryptography-vectors (==43.0.0)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
 test-randomorder = ["pytest-randomly"]
 
 [[package]]
 name = "data-adapter"
-version = "0.22.0"
+version = "0.21.0"
 description = "Provides general functionality for other data adapters"
 optional = false
 python-versions = ">=3.8.1,<4.0.0"
@@ -536,8 +531,8 @@ units = "^0.7"
 [package.source]
 type = "git"
 url = "https://git@github.com/sedos-project/data_adapter"
-reference = "main"
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+    {file = "highspy-1.7.2-cp39-cp39-win32.whl", hash = "sha256:b496a5d337508847737836ada6d930b404d921a119132cd1d14df47a4b488db7"},
+    {file = "highspy-1.7.2-cp39-cp39-win_amd64.whl", hash = "sha256:e7d3883c697103c8c39d808976a00b85d68f869b97bae6d48b7b03811dfbb925"},
+    {file = "highspy-1.7.2.tar.gz", hash = "sha256:7987b2a3f013254a1845bceb4597087da4070f7887c0084024649486321ae213"},
 ]
 
 [package.dependencies]
@@ -820,13 +825,13 @@ test = ["numpy", "pytest"]
 
 [[package]]
 name = "identify"
-version = "2.5.36"
+version = "2.6.0"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "identify-2.5.36-py2.py3-none-any.whl", hash = "sha256:37d93f380f4de590500d9dba7db359d0d3da95ffe7f9de1753faa159e71e7dfa"},
-    {file = "identify-2.5.36.tar.gz", hash = "sha256:e5e00f54165f9047fbebeb4a560f9acfb8af4c88232be60a488e9b68d122745d"},
+    {file = "identify-2.6.0-py2.py3-none-any.whl", hash = "sha256:e79ae4406387a9d300332b5fd366d8994f1525e8414984e1a59e058b2eda2dd0"},
+    {file = "identify-2.6.0.tar.gz", hash = "sha256:cb171c685bdc31bcc4c1734698736a7d5b6c8bf2e0c15117f4d469c8640ae5cf"},
 ]
 
 [package.extras]
@@ -1403,13 +1408,13 @@ dev = ["pytest", "sphinx", "sphinx-rtd-theme"]
 
 [[package]]
 name = "openpyxl"
-version = "3.1.4"
+version = "3.1.5"
 description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "openpyxl-3.1.4-py2.py3-none-any.whl", hash = "sha256:ec17f6483f2b8f7c88c57e5e5d3b0de0e3fb9ac70edc084d28e864f5b33bbefd"},
-    {file = "openpyxl-3.1.4.tar.gz", hash = "sha256:8d2c8adf5d20d6ce8f9bca381df86b534835e974ed0156dacefa76f68c1d69fb"},
+    {file = "openpyxl-3.1.5-py2.py3-none-any.whl", hash = "sha256:5282c12b107bffeef825f4617dc029afaf41d0ea60823bbb665ef3079dc79de2"},
+    {file = "openpyxl-3.1.5.tar.gz", hash = "sha256:cf0e3cf56142039133628b5acffe8ef0c12bc902d2aadd3e0fe5878dc08d1050"},
 ]
 
 [package.dependencies]
@@ -2026,32 +2031,32 @@ crt = ["botocore[crt] (>=1.20.29,<2.0a.0)"]
 
 [[package]]
 name = "scikit-learn"
-version = "1.5.0"
+version = "1.5.1"
 description = "A set of python modules for machine learning and data mining"
 optional = false
 python-versions = ">=3.9"
 files = [
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+    {file = "scikit_learn-1.5.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:909144d50f367a513cee6090873ae582dba019cb3fca063b38054fa42704c3a4"},
+    {file = "scikit_learn-1.5.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:689b6f74b2c880276e365fe84fe4f1befd6a774f016339c65655eaff12e10cbf"},
+    {file = "scikit_learn-1.5.1-cp311-cp311-win_amd64.whl", hash = "sha256:9a07f90846313a7639af6a019d849ff72baadfa4c74c778821ae0fad07b7275b"},
+    {file = "scikit_learn-1.5.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:5944ce1faada31c55fb2ba20a5346b88e36811aab504ccafb9f0339e9f780395"},
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+    {file = "scikit_learn-1.5.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:97625f217c5c0c5d0505fa2af28ae424bd37949bb2f16ace3ff5f2f81fb4498b"},
+    {file = "scikit_learn-1.5.1-cp312-cp312-win_amd64.whl", hash = "sha256:da3f404e9e284d2b0a157e1b56b6566a34eb2798205cba35a211df3296ab7a74"},
+    {file = "scikit_learn-1.5.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:88e0672c7ac21eb149d409c74cc29f1d611d5158175846e7a9c2427bd12b3956"},
+    {file = "scikit_learn-1.5.1-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:7b073a27797a283187a4ef4ee149959defc350b46cbf63a84d8514fe16b69855"},
+    {file = "scikit_learn-1.5.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b59e3e62d2be870e5c74af4e793293753565c7383ae82943b83383fdcf5cc5c1"},
+    {file = "scikit_learn-1.5.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1bd8d3a19d4bd6dc5a7d4f358c8c3a60934dc058f363c34c0ac1e9e12a31421d"},
+    {file = "scikit_learn-1.5.1-cp39-cp39-win_amd64.whl", hash = "sha256:5f57428de0c900a98389c4a433d4a3cf89de979b3aa24d1c1d251802aa15e44d"},
+    {file = "scikit_learn-1.5.1.tar.gz", hash = "sha256:0ea5d40c0e3951df445721927448755d3fe1d80833b0b7308ebff5d2a45e6414"},
 ]
 
 [package.dependencies]
@@ -2062,8 +2067,8 @@ threadpoolctl = ">=3.1.0"
 
 [package.extras]
 benchmark = ["matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "pandas (>=1.1.5)"]
-build = ["cython (>=3.0.10)", "meson-python (>=0.15.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)"]
-docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "polars (>=0.20.23)", "pooch (>=1.6.0)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)", "sphinx (>=6.0.0)", "sphinx-copybutton (>=0.5.2)", "sphinx-gallery (>=0.15.0)", "sphinx-prompt (>=1.3.0)", "sphinxext-opengraph (>=0.4.2)"]
+build = ["cython (>=3.0.10)", "meson-python (>=0.16.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)"]
+docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.3.4)", "memory_profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "polars (>=0.20.23)", "pooch (>=1.6.0)", "pydata-sphinx-theme (>=0.15.3)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)", "sphinx (>=7.3.7)", "sphinx-copybutton (>=0.5.2)", "sphinx-design (>=0.5.0)", "sphinx-gallery (>=0.16.0)", "sphinx-prompt (>=1.4.0)", "sphinx-remove-toctrees (>=1.0.0.post1)", "sphinxcontrib-sass (>=0.3.4)", "sphinxext-opengraph (>=0.9.1)"]
 examples = ["matplotlib (>=3.3.4)", "pandas (>=1.1.5)", "plotly (>=5.14.0)", "pooch (>=1.6.0)", "scikit-image (>=0.17.2)", "seaborn (>=0.9.0)"]
 install = ["joblib (>=1.2.0)", "numpy (>=1.19.5)", "scipy (>=1.6.0)", "threadpoolctl (>=3.1.0)"]
 maintenance = ["conda-lock (==2.5.6)"]
@@ -2521,15 +2526,18 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "validators"
-version = "0.28.3"
+version = "0.33.0"
 description = "Python Data Validation for Humans™"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "validators-0.28.3-py3-none-any.whl", hash = "sha256:53cafa854f13850156259d9cc479b864ee901f6a96e6b109e6fc33f98f37d99f"},
-    {file = "validators-0.28.3.tar.gz", hash = "sha256:c6c79840bcde9ba77b19f6218f7738188115e27830cbaff43264bc4ed24c429d"},
+    {file = "validators-0.33.0-py3-none-any.whl", hash = "sha256:134b586a98894f8139865953899fc2daeb3d0c35569552c5518f089ae43ed075"},
+    {file = "validators-0.33.0.tar.gz", hash = "sha256:535867e9617f0100e676a1257ba1e206b9bfd847ddc171e4d44811f07ff0bfbf"},
 ]
 
+[package.extras]
+crypto-eth-addresses = ["eth-hash[pycryptodome] (>=0.7.0)"]
+
 [[package]]
 name = "virtualenv"
 version = "20.26.3"
@@ -2572,4 +2580,4 @@ docs = []
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.11"
-content-hash = "c20e8c1b158f2417d6e37b7708a4fea2a222fa1f3545062c651d0e9b685dd27c"
+content-hash = "fb6e2ecd10b63c067be3d7d8b63bfc062be95479af3f6f4ebf515f710fd1627e"
diff --git a/pyproject.toml b/pyproject.toml
index fdf574a..ccdd083 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,7 +7,8 @@ authors = [
   "Sarah Berendes <Sarah.Berendes@rl-institut.de>",
   "Julian Endres <Julian.Endres@rl-institut.de>",
   "Felix Maurer <Felix.Maurer@rl-institut.de>",
-  "Hendrik Huyskens <Hendrik.Huyskens@rl-institut.de>"
+  "Hendrik Huyskens <Hendrik.Huyskens@rl-institut.de>",
+  "Sabine Haas <Sabine.Haas@rl-institut.de>"
 ]
 
 [tool.poetry.group.dev.dependencies]
@@ -20,8 +21,8 @@ build-backend = "poetry.core.masonry.api"
 [tool.poetry.dependencies]
 python = ">=3.10,<3.11"
 data_adapter = { git = "https://git@github.com/sedos-project/data_adapter", branch = "main"}
-oemof-tabular = { git = "https://git@github.com/oemof/oemof-tabular", branch = "dev"}
-oemof-industry = { git = "https://github.com/sedos-project/oemof.industry.git", branch = "main"}
+oemof-tabular = { git = "https://git@github.com/oemof/oemof-tabular", branch = "feature/multi-period-results"}
+oemof-industry = { git = "https://github.com/sedos-project/oemof.industry.git", branch = "feature/multi_period_emi_constraint"}
 boto3 = "1.26.125"  # fix boto3 to fasten up dependency resolution
 python-dotenv = "^0.21.0"
 tsam = "^2.3.1"