diff --git a/.gitignore b/.gitignore
index c71709af..51203af0 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,4 +2,8 @@
 /docs/_build/
 /docs/_build/doctrees/
 /docs/_build/html/
-/.idea/
\ No newline at end of file
+/.idea/
+cbc.exe
+coin-license.txt
+**/__pycache__/**
+micro_grid_design_logfile.log*
diff --git a/inputs/test_input_template.xlsx b/inputs/test_input_template.xlsx
index 86e2d6fc..22d5be5c 100644
Binary files a/inputs/test_input_template.xlsx and b/inputs/test_input_template.xlsx differ
diff --git a/inputs/timeseries/test_site.csv b/inputs/timeseries/test_site.csv
index d329b695..eb87210f 100644
--- a/inputs/timeseries/test_site.csv
+++ b/inputs/timeseries/test_site.csv
@@ -1,8761 +1,8761 @@
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+67.66119;67.66119;0;0.427
+45.31507;45.31507;0;0.445
+24.71021;24.71021;0;0.428
+13.05035;13.05035;0;0.439
+6.79898999999999;6.79898999999999;0;0.458999999999999
+6.0926;6.0926;0;0.482
+5.83372;5.83372;0;0.529
+5.39143;5.39143;0;0.529
+5.7385;5.7385;0;0.514
+11.84093;11.84093;0;0.482
+18.25696;18.25696;0;0.493
+24.80137;24.80137;0.099;0.445
+20.62038;20.62038;0.308;0.471
+21.19779;21.19779;0.488;0.389
+24.24526;24.24526;0.61;0.174
+29.14625;29.14625;0.675999999999999;0.038
+30.06301;30.06301;0.691;0.003
+27.74642;27.74642;0.667;0
+26.08866;26.08866;0.586;0.001
+30.49567;30.49567;0.452999999999999;0.003
+22.4239;22.4239;0.261;0.01
+37.05759;37.05759;0.07;0.0279999999999999
+53.93324;53.93324;0;0.088
+70.82166;70.82166;0;0.141
+91.01241;91.01241;0;0.175
+60.04138;60.04138;0;0.211
+32.50716;32.50716;0;0.23
+16.75658;16.75658;0;0.237
+8.12757;8.12757;0;0.26
+4.82961999999999;4.82961999999999;0;0.284
+4.27489;4.27489;0;0.31
+4.30445;4.30445;0;0.333999999999999
+4.96756;4.96756;0;0.351
+10.68728;10.68728;0;0.351
+15.4072299999999;15.4072299999999;0;0.35
+18.45173;18.45173;0.099;0.315
+14.27575;14.27575;0.308;0.254
+15.89393;15.89393;0.486;0.119
+20.04378;20.04378;0.621;0.01
+22.36161;22.36161;0.684;0.002
+23.45244;23.45244;0.699;0.001
+24.81012;24.81012;0.657999999999999;0.003
+22.86923;22.86923;0.572;0.009
+25.68738;25.68738;0.437;0.017
+24.1494;24.1494;0.256;0.027
+25.4651;25.4651;0.066;0.033
+42.96353;42.96353;0;0.051
+62.40561;62.40561;0;0.044
+65.60637;65.60637;0;0.034
+51.64414;51.64414;0;0.0409999999999999
+29.45994;29.45994;0;0.055
+11.08806;11.08806;0;0.078
+6.50314;6.50314;0;0.12
+4.08379;4.08379;0;0.172
+3.86385;3.86385;0;0.211
+4.43386;4.43386;0;0.228
+4.40577;4.40577;0;0.236
+10.88069;10.88069;0;0.237
+14.63274;14.63274;0;0.236
+21.13797;21.13797;0.086;0.218999999999999
+14.40833;14.40833;0.278;0.159
+15.91996;15.91996;0.451;0.024
+24.42585;24.42585;0.576;0.006
+23.75702;23.75702;0.647;0.004
+24.55258;24.55258;0.665999999999999;0.008
+20.40438;20.40438;0.634;0.021
+25.022;25.022;0.552999999999999;0.0409999999999999
+25.23213;25.23213;0.422;0.052
+28.97149;28.97149;0.233;0.054
+25.32377;25.32377;0.0579999999999999;0.0409999999999999
+40.07939;40.07939;0;0.037
+54.98804;54.98804;0;0.018
+57.99258;57.99258;0;0.003
+49.65411;49.65411;0;0
+35.57427;35.57427;0;0
+13.74549;13.74549;0;0.004
+4.57201;4.57201;0;0.019
+6.04388;6.04388;0;0.051
+4.91675;4.91675;0;0.0969999999999999
+5.52931999999999;5.52931999999999;0;0.157
+4.90279;4.90279;0;0.228
+10.67337;10.67337;0;0.298
+15.73559;15.73559;0;0.335
+25.06351;25.06351;0.09;0.315
+17.66286;17.66286;0.286;0.283
+22.14251;22.14251;0.461;0.188
+21.31061;21.31061;0.599;0.047
+26.44562;26.44562;0.669;0.017
+28.02357;28.02357;0.687;0.01
+31.38329;31.38329;0.659;0.008
+27.35516;27.35516;0.579;0.008
+30.40207;30.40207;0.447;0.01
+30.70017;30.70017;0.259;0.011
+35.72139;35.72139;0.054;0.013
+53.9038;53.9038;0;0.0279999999999999
+68.04301;68.04301;0;0.027
+82.2406199999999;82.2406199999999;0;0.031
+60.29079;60.29079;0;0.083
+26.08371;26.08371;0;0.159
+15.24404;15.24404;0;0.221
+7.43961;7.43961;0;0.268
+3.4231;3.4231;0;0.31
+3.69287;3.69287;0;0.341
+4.31144;4.31144;0;0.362
+3.2011;3.2011;0;0.38
+6.56016999999999;6.56016999999999;0;0.405
+8.95558;8.95558;0;0.395
+15.46905;15.46905;0.105;0.352
+11.07772;11.07772;0.311;0.348
+16.33365;16.33365;0.482;0.267
+18.23924;18.23924;0.596;0.163
+19.57509;19.57509;0.660999999999999;0.111
+16.79295;16.79295;0.675999999999999;0.067
+21.39498;21.39498;0.65;0.037
+19.5481;19.5481;0.571;0.02
+23.92334;23.92334;0.414;0.012
+21.58958;21.58958;0.196999999999999;0.009
+26.17668;26.17668;0.044;0.011
+33.94537;33.94537;0;0.0279999999999999
+48.43045;48.43045;0;0.057
+60.39715;60.39715;0;0.077
+39.45402;39.45402;0;0.093
+22.67802;22.67802;0;0.114
+9.33867;9.33867;0;0.14
+5.90681;5.90681;0;0.171
+5.10016;5.10016;0;0.203
+4.71448;4.71448;0;0.253
+4.32779;4.32779;0;0.314
+4.5603;4.5603;0;0.347
+10.09373;10.09373;0;0.347
+13.11992;13.11992;0;0.336
+19.11832;19.11832;0.096;0.288
+17.67471;17.67471;0.296;0.26
+18.02422;18.02422;0.467;0.113
+26.0012;26.0012;0.607;0.0409999999999999
+24.39119;24.39119;0.67;0.02
+27.77322;27.77322;0.684;0.011
+26.39946;26.39946;0.637;0.00699999999999999
+22.43919;22.43919;0.548999999999999;0.005
+28.91763;28.91763;0.415;0.004
+21.08925;21.08925;0.22;0.006
+30.11988;30.11988;0.0579999999999999;0.015
+52.15019;52.15019;0;0.031
+54.40204;54.40204;0;0.024
+86.78675;86.78675;0;0.011
+53.29828;53.29828;0;0.017
+31.11376;31.11376;0;0.037
+17.40072;17.40072;0;0.063
+7.09158;7.09158;0;0.098
+5.34385;5.34385;0;0.149
+3.90404;3.90404;0;0.213
+5.16663;5.16663;0;0.268
+5.06424;5.06424;0;0.313
+11.88616;11.88616;0;0.351
+16.91786;16.91786;0;0.379
+20.30695;20.30695;0.105;0.356
+18.2039;18.2039;0.308;0.318
+20.14462;20.14462;0.477;0.178
+26.25448;26.25448;0.613;0.074
+29.14181;29.14181;0.669;0.032
+29.5983;29.5983;0.669;0.0139999999999999
+31.10156;31.10156;0.635;0.005
+23.94263;23.94263;0.566;0.002
+29.50956;29.50956;0.451;0.003
+24.64571;24.64571;0.283;0.01
+34.44422;34.44422;0.085;0.016
+44.20961;44.20961;0;0.035
+57.86625;57.86625;0;0.065
+86.71133;86.71133;0;0.088
+60.89797;60.89797;0;0.109
+35.90664;35.90664;0;0.135
+16.85376;16.85376;0;0.163999999999999
+5.83536;5.83536;0;0.214
diff --git a/src/B_read_from_files.py b/src/B_read_from_files.py
index 07496dde..6ce86b5a 100644
--- a/src/B_read_from_files.py
+++ b/src/B_read_from_files.py
@@ -27,11 +27,15 @@
     TARIFF,
     TITLE_TIME,
     TITLE_DEMAND_AC,
+    TITLE_DEMAND_AC_CRITICAL,
     TITLE_DEMAND_DC,
+    TITLE_DEMAND_DC_CRITICAL,
     TITLE_PV,
     TITLE_WIND,
     DEMAND_AC,
+    DEMAND_AC_CRITICAL,
     DEMAND_DC,
+    DEMAND_DC_CRITICAL,
     PV_GENERATION_PER_KWP,
     WIND_GENERATION_PER_KW,
     GRID_AVAILABILITY,
@@ -110,7 +114,7 @@ def process_excel_file(input_excel_file):
     # -------- Check for, create or empty results directory -----------------------#
     check_output_directory(settings, input_excel_file)
 
-    (parameters_constant_units, parameters_constant_values,) = get_parameters_constant(
+    (parameters_constant_units, parameters_constant_values) = get_parameters_constant(
         input_excel_file, sheet_input_constant
     )
     parameters_sensitivity = get_parameters_sensitivity(
@@ -406,10 +410,7 @@ def get_case_definitions(file, sheet_project_sites):
                 {MAX_SHORTAGE: float(case_definitions[case][MAX_SHORTAGE])}
             )
 
-        if case_definitions[case][EVALUATION_PERSPECTIVE] not in [
-            AC_SYSTEM,
-            DC_SYSTEM,
-        ]:
+        if case_definitions[case][EVALUATION_PERSPECTIVE] not in [AC_SYSTEM, DC_SYSTEM]:
             logging.error(
                 f"Parameter {EVALUATION_PERSPECTIVE} has to be either {AC_SYSTEM} or {DC_SYSTEM}, but is {case_definitions[case][EVALUATION_PERSPECTIVE]}"
             )
@@ -551,7 +552,9 @@ def from_file(project_site, path_from):
     list_columns = [
         TITLE_TIME,
         TITLE_DEMAND_AC,
+        TITLE_DEMAND_AC_CRITICAL,
         TITLE_DEMAND_DC,
+        TITLE_DEMAND_DC_CRITICAL,
         TITLE_PV,
         TITLE_WIND,
         TITLE_GRID_AVAILABILITY,
@@ -584,6 +587,10 @@ def from_file(project_site, path_from):
                 dictionary_title = DEMAND_AC
             elif column_item == TITLE_DEMAND_DC:
                 dictionary_title = DEMAND_DC
+            elif column_item == TITLE_DEMAND_AC_CRITICAL:
+                dictionary_title = DEMAND_AC_CRITICAL
+            elif column_item == TITLE_DEMAND_DC_CRITICAL:
+                dictionary_title = DEMAND_DC_CRITICAL
             elif column_item == TITLE_PV:
                 dictionary_title = PV_GENERATION_PER_KWP
             elif column_item == TITLE_WIND:
@@ -611,6 +618,9 @@ def from_file(project_site, path_from):
                     project_site.update(
                         {dictionary_title: pd.Series([0 for i in range(0, 8760)])}
                     )
+            logging.debug(
+                f"Data input: {column_item} will be read from column {dictionary_title}"
+            )
 
     return
 
diff --git a/src/D0_process_input.py b/src/D0_process_input.py
index 472f654f..fb49d76c 100644
--- a/src/D0_process_input.py
+++ b/src/D0_process_input.py
@@ -32,19 +32,29 @@
     TIME_FREQUENCY,
     FILE_INDEX,
     DEMAND_PROFILE_AC,
+    DEMAND_PROFILE_AC_CRITICAL,
     DEMAND_PROFILE_DC,
+    DEMAND_PROFILE_DC_CRITICAL,
     ACCUMULATED_PROFILE_AC_SIDE,
     ACCUMULATED_PROFILE_DC_SIDE,
     TOTAL_DEMAND_AC,
+    TOTAL_DEMAND_AC_CRITICAL,
     PEAK_DEMAND_AC,
+    PEAK_DEMAND_AC_CRITICAL,
     TOTAL_DEMAND_DC,
+    TOTAL_DEMAND_DC_CRITICAL,
     PEAK_DEMAND_DC,
+    PEAK_DEMAND_DC_CRITICAL,
     PEAK_PV_GENERATION_PER_KWP,
     PEAK_WIND_GENERATION_PER_KW,
     MEAN_DEMAND_AC,
+    MEAN_DEMAND_AC_CRITICAL,
     MEAN_DEMAND_DC,
+    MEAN_DEMAND_DC_CRITICAL,
     PEAK_MEAN_DEMAND_RATIO_AC,
+    PEAK_MEAN_DEMAND_RATIO_AC_CRITICAL,
     PEAK_MEAN_DEMAND_RATIO_DC,
+    PEAK_MEAN_DEMAND_RATIO_DC_CRITICAL,
     ABS_PEAK_DEMAND_AC_SIDE,
     PROJECT_LIFETIME,
     WACC,
@@ -53,10 +63,12 @@
     FUEL_PRICE_CHANGE_ANNUAL,
     TAX,
     DEMAND_AC,
+    DEMAND_AC_CRITICAL,
     PV_GENERATION_PER_KWP,
     WIND_GENERATION_PER_KW,
     GRID_AVAILABILITY,
     DEMAND_DC,
+    DEMAND_DC_CRITICAL,
     LP_FILE_FOR_ONLY_3_TIMESTEPS,
     RECTIFIER_AC_DC_EFFICIENCY,
     INVERTER_DC_AC_EFFICIENCY,
@@ -229,7 +241,27 @@ def economic_values(experiment):
     return experiment
 
 
-def add_timeseries(experiment_s):
+MAPPING_DEMAND_TYPE_TO_PROFILE = {
+    DEMAND_AC: DEMAND_PROFILE_AC,
+    DEMAND_AC_CRITICAL: DEMAND_PROFILE_AC_CRITICAL,
+    DEMAND_DC_CRITICAL: DEMAND_PROFILE_DC_CRITICAL,
+    DEMAND_DC: DEMAND_PROFILE_DC,
+}
+
+
+def update_demand_profile(experiment_s, experiment, demand_type):
+    index = experiment_s[experiment][DATE_TIME_INDEX]
+    experiment_s[experiment].update(
+        {
+            MAPPING_DEMAND_TYPE_TO_PROFILE[demand_type]: pd.Series(
+                experiment_s[experiment][demand_type][0 : len(index)].values,
+                index=index,
+            )
+        }
+    )
+
+
+def add_timeseries(experiment_s) -> object:
     """
     Update experiments and add longest date_time_index to settings
 
@@ -278,7 +310,7 @@ def add_timeseries(experiment_s):
 
     for experiment in experiment_s:
         index = experiment_s[experiment][DATE_TIME_INDEX]
-        if experiment_s[experiment][FILE_INDEX] != None:
+        if experiment_s[experiment][FILE_INDEX] is not None:
             if DEMAND_AC in experiment_s[experiment]:
                 year_timeseries_in_file = (
                     experiment_s[experiment][DEMAND_AC].index[0].year
@@ -300,10 +332,18 @@ def add_timeseries(experiment_s):
                     experiment_s[experiment][DEMAND_AC].values,
                     index=experiment_s[experiment][FILE_INDEX],
                 )
+                demand_ac_critical = pd.Series(
+                    experiment_s[experiment][DEMAND_AC_CRITICAL].values,
+                    index=experiment_s[experiment][FILE_INDEX],
+                )
                 demand_dc = pd.Series(
                     experiment_s[experiment][DEMAND_DC].values,
                     index=experiment_s[experiment][FILE_INDEX],
                 )
+                demand_dc_critical = pd.Series(
+                    experiment_s[experiment][DEMAND_DC_CRITICAL].values,
+                    index=experiment_s[experiment][FILE_INDEX],
+                )
                 pv_generation_per_kWp = pd.Series(
                     experiment_s[experiment][PV_GENERATION_PER_KWP].values,
                     index=experiment_s[experiment][FILE_INDEX],
@@ -314,7 +354,13 @@ def add_timeseries(experiment_s):
                 )
                 # from provided data use only analysed timeframe
                 experiment_s[experiment].update({DEMAND_PROFILE_AC: demand_ac[index]})
+                experiment_s[experiment].update(
+                    {DEMAND_PROFILE_AC_CRITICAL: demand_ac_critical[index]}
+                )
                 experiment_s[experiment].update({DEMAND_PROFILE_DC: demand_dc[index]})
+                experiment_s[experiment].update(
+                    {DEMAND_PROFILE_DC_CRITICAL: demand_dc_critical[index]}
+                )
                 experiment_s[experiment].update(
                     {PV_GENERATION_PER_KWP: pv_generation_per_kWp[index]}
                 )
@@ -335,24 +381,15 @@ def add_timeseries(experiment_s):
                 # file index is date time index, no change necessary
                 pass
 
-        elif experiment_s[experiment][FILE_INDEX] == None:
-            # limit based on index
-            experiment_s[experiment].update(
-                {
-                    DEMAND_PROFILE_AC: pd.Series(
-                        experiment_s[experiment][DEMAND_AC][0 : len(index)].values,
-                        index=index,
-                    )
-                }
-            )
-            experiment_s[experiment].update(
-                {
-                    DEMAND_PROFILE_DC: pd.Series(
-                        experiment_s[experiment][DEMAND_DC][0 : len(index)].values,
-                        index=index,
-                    )
-                }
-            )
+        elif experiment_s[experiment][FILE_INDEX] is None:
+            for demand_type in [
+                DEMAND_AC,
+                DEMAND_AC_CRITICAL,
+                DEMAND_DC_CRITICAL,
+                DEMAND_DC,
+            ]:
+                update_demand_profile(experiment_s, experiment, demand_type)
+
             experiment_s[experiment].update(
                 {
                     PV_GENERATION_PER_KWP: pd.Series(
@@ -363,6 +400,7 @@ def add_timeseries(experiment_s):
                     )
                 }
             )
+
             experiment_s[experiment].update(
                 {
                     WIND_GENERATION_PER_KW: pd.Series(
@@ -419,9 +457,24 @@ def add_timeseries(experiment_s):
             experiment_s[experiment].update(
                 {DEMAND_PROFILE_AC: experiment_s[experiment][DEMAND_PROFILE_AC][index]}
             )
+            experiment_s[experiment].update(
+                {
+                    DEMAND_PROFILE_AC_CRITICAL: experiment_s[experiment][
+                        DEMAND_PROFILE_AC_CRITICAL
+                    ][index]
+                }
+            )
             experiment_s[experiment].update(
                 {DEMAND_PROFILE_DC: experiment_s[experiment][DEMAND_PROFILE_DC][index]}
             )
+            experiment_s[experiment].update(
+                {
+                    DEMAND_PROFILE_DC_CRITICAL: experiment_s[experiment][
+                        DEMAND_PROFILE_DC_CRITICAL
+                    ][index]
+                }
+            )
+
             experiment_s[experiment].update(
                 {
                     PV_GENERATION_PER_KWP: experiment_s[experiment][
@@ -444,7 +497,6 @@ def add_timeseries(experiment_s):
                         ]
                     }
                 )
-
         experiment_s[experiment].update(
             {
                 ACCUMULATED_PROFILE_AC_SIDE: experiment_s[experiment][DEMAND_PROFILE_AC]
@@ -452,7 +504,6 @@ def add_timeseries(experiment_s):
                 / experiment_s[experiment][RECTIFIER_AC_DC_EFFICIENCY]
             }
         )
-
         experiment_s[experiment].update(
             {
                 ACCUMULATED_PROFILE_DC_SIDE: experiment_s[experiment][DEMAND_PROFILE_AC]
@@ -460,12 +511,25 @@ def add_timeseries(experiment_s):
                 + experiment_s[experiment][DEMAND_PROFILE_DC]
             }
         )
+
         experiment_s[experiment].update(
             {
                 TOTAL_DEMAND_AC: sum(experiment_s[experiment][DEMAND_PROFILE_AC]),
+                TOTAL_DEMAND_AC_CRITICAL: sum(
+                    experiment_s[experiment][DEMAND_PROFILE_AC_CRITICAL]
+                ),
                 PEAK_DEMAND_AC: max(experiment_s[experiment][DEMAND_PROFILE_AC]),
+                PEAK_DEMAND_AC_CRITICAL: max(
+                    experiment_s[experiment][DEMAND_PROFILE_AC_CRITICAL]
+                ),
                 TOTAL_DEMAND_DC: sum(experiment_s[experiment][DEMAND_PROFILE_DC]),
+                TOTAL_DEMAND_DC_CRITICAL: sum(
+                    experiment_s[experiment][DEMAND_PROFILE_DC_CRITICAL]
+                ),
                 PEAK_DEMAND_DC: max(experiment_s[experiment][DEMAND_PROFILE_DC]),
+                PEAK_DEMAND_DC_CRITICAL: max(
+                    experiment_s[experiment][DEMAND_PROFILE_DC_CRITICAL]
+                ),
                 PEAK_PV_GENERATION_PER_KWP: max(
                     experiment_s[experiment][PV_GENERATION_PER_KWP]
                 ),
@@ -515,15 +579,23 @@ def add_timeseries(experiment_s):
 
         # Warnings
         if (
-            experiment_s[experiment][TOTAL_DEMAND_AC]
-            == 0 + experiment_s[experiment][TOTAL_DEMAND_DC]
-            == 0
+            experiment_s[experiment][TOTAL_DEMAND_AC] == 0
+            and experiment_s[experiment][TOTAL_DEMAND_DC] == 0
         ):
             logging.warning(
                 "No demand in evaluated timesteps at project site "
                 + experiment_s[experiment][PROJECT_SITE_NAME]
                 + " - simulation will crash."
             )
+        if (
+            experiment_s[experiment][TOTAL_DEMAND_AC_CRITICAL] == 0
+            and experiment_s[experiment][TOTAL_DEMAND_DC_CRITICAL] == 0
+        ):
+            logging.warning(
+                "No critical demand in evaluated timesteps at project site "
+                + experiment_s[experiment][PROJECT_SITE_NAME]
+                + " - simulation will not provide expected results if you wanted to distinguish between critical and non-critical demand."
+            )
         if experiment_s[experiment][PEAK_PV_GENERATION_PER_KWP] == 0:
             logging.info(
                 "No pv generation in evaluated timesteps at project site "
@@ -557,7 +629,9 @@ def apply_noise(experiment_s):
     """
     for experiment in experiment_s:
         on_series(experiment_s[experiment], WHITE_NOISE_DEMAND, DEMAND_AC)
+        on_series(experiment_s[experiment], WHITE_NOISE_DEMAND, DEMAND_AC_CRITICAL)
         on_series(experiment_s[experiment], WHITE_NOISE_DEMAND, DEMAND_DC)
+        on_series(experiment_s[experiment], WHITE_NOISE_DEMAND, DEMAND_DC_CRITICAL)
         on_series(experiment_s[experiment], WHITE_NOISE_PV, PV_GENERATION_PER_KWP)
         on_series(experiment_s[experiment], WHITE_NOISE_WIND, WIND_GENERATION_PER_KW)
     return
diff --git a/src/F_case_definitions.py b/src/F_case_definitions.py
index 71d9e320..bb6a2854 100644
--- a/src/F_case_definitions.py
+++ b/src/F_case_definitions.py
@@ -20,6 +20,8 @@
     FILENAME,
     TOTAL_DEMAND_AC,
     TOTAL_DEMAND_DC,
+    TOTAL_DEMAND_AC_CRITICAL,
+    TOTAL_DEMAND_DC_CRITICAL,
     ABS_PEAK_DEMAND_AC_SIDE,
     EVALUATED_DAYS,
     GENSET_WITH_MINIMAL_LOADING,
@@ -58,6 +60,7 @@
     RENEWABLE_CONSTRAINT,
     MIN_RENEWABLE_SHARE,
     RENEWABLE_SHARE_CONSTRAINT,
+    CRITICAL_CONSTRAINT,
     NUMBER_OF_EQUAL_GENERATORS,
     EVALUATION_PERSPECTIVE,
     FORCE_CHARGE_FROM_MAINGRID,
@@ -69,6 +72,7 @@
     SHARE_BACKUP,
     SHARE_USAGE,
     SHARE_HYBRID,
+    CRITICAL,
     DEFAULT,
 )
 
@@ -107,6 +111,8 @@ def update_dict(capacities_oem, specific_case, experiment):
             ],  # experiment['output_folder'] + "_" + specific_case['case_name'] + experiment['filename']
             TOTAL_DEMAND_AC: experiment[TOTAL_DEMAND_AC],
             TOTAL_DEMAND_DC: experiment[TOTAL_DEMAND_DC],
+            TOTAL_DEMAND_AC_CRITICAL: experiment[TOTAL_DEMAND_AC_CRITICAL],
+            TOTAL_DEMAND_DC_CRITICAL: experiment[TOTAL_DEMAND_DC_CRITICAL],
             PEAK_DEMAND: experiment[ABS_PEAK_DEMAND_AC_SIDE],
             EVALUATED_DAYS: experiment[EVALUATED_DAYS],
             GENSET_WITH_MINIMAL_LOADING: specific_case[GENSET_WITH_MINIMAL_LOADING],
@@ -234,6 +240,7 @@ def update_dict(capacities_oem, specific_case, experiment):
         or specific_case[STABILITY_CONSTRAINT] == SHARE_BACKUP
         or specific_case[STABILITY_CONSTRAINT] == SHARE_USAGE
         or specific_case[STABILITY_CONSTRAINT] == SHARE_HYBRID
+        or specific_case[STABILITY_CONSTRAINT] == CRITICAL
     ):
         experiment_case_dict.update(
             {STABILITY_CONSTRAINT: specific_case[STABILITY_CONSTRAINT]}
@@ -245,8 +252,22 @@ def update_dict(capacities_oem, specific_case, experiment):
         )
 
     ###########################################
-    # Include renewable constraint            #
+    # Include critical constraint            #
     ###########################################
+    if specific_case[CRITICAL_CONSTRAINT] == DEFAULT:
+        experiment_case_dict.update({CRITICAL_CONSTRAINT: False})
+    elif specific_case[CRITICAL_CONSTRAINT] is False:
+        experiment_case_dict.update({CRITICAL_CONSTRAINT: False})
+    elif specific_case[CRITICAL_CONSTRAINT] is True:
+        experiment_case_dict.update({CRITICAL_CONSTRAINT: True})
+    else:
+        logging.warning(
+            warning_string
+            + f" value {CRITICAL_CONSTRAINT} (True/False/default) not defined properly"
+        )
+    ###########################################
+    # Include renewable constraint            #
+    ###########################################>>
 
     if specific_case[RENEWABLE_CONSTRAINT] == DEFAULT:
         if experiment[MIN_RENEWABLE_SHARE] == 0:
diff --git a/src/G0_oemof_simulate.py b/src/G0_oemof_simulate.py
index 93a7ca53..870f9b0c 100644
--- a/src/G0_oemof_simulate.py
+++ b/src/G0_oemof_simulate.py
@@ -155,7 +155,7 @@ def run(experiment, case_dict):
             experiment,
             e_flows_df,
         )
-
+        # TODO maybe separate critical and non critical here for results plotting
         oemof_results.update(
             {
                 SUPPLY_RELIABILITY_KWH: oemof_results[TOTAL_DEMAND_SUPPLIED_ANNUAL_KWH]
diff --git a/src/G1_oemof_create_model.py b/src/G1_oemof_create_model.py
index 684ae8c3..68f2d1db 100644
--- a/src/G1_oemof_create_model.py
+++ b/src/G1_oemof_create_model.py
@@ -10,7 +10,12 @@
     BUS_FUEL,
     DATE_TIME_INDEX,
     BUS_ELECTRICITY_AC,
+    DEMAND_DC,
+    DEMAND_AC,
+    DEMAND_DC_CRITICAL,
+    DEMAND_AC_CRITICAL,
     DEMAND_PROFILE_AC,
+    DEMAND_PROFILE_AC_CRITICAL,
     GENSET_FIXED_CAPACITY,
     GENSET_WITH_MINIMAL_LOADING,
     NUMBER_OF_EQUAL_GENERATORS,
@@ -21,6 +26,7 @@
     PEAK_DEMAND,
     BUS_ELECTRICITY_DC,
     DEMAND_PROFILE_DC,
+    DEMAND_PROFILE_DC_CRITICAL,
     PV_FIXED_CAPACITY,
     STORAGE_FIXED_CAPACITY,
     STORAGE_FIXED_POWER,
@@ -31,7 +37,9 @@
     SHARE_BACKUP,
     SHARE_USAGE,
     SHARE_HYBRID,
+    CRITICAL,
     RENEWABLE_SHARE_CONSTRAINT,
+    CRITICAL_CONSTRAINT,
     FORCE_CHARGE_FROM_MAINGRID,
     DISCHARGE_ONLY_WHEN_BLACKOUT,
     ENABLE_INVERTER_ONLY_AT_BLACKOUT,
@@ -85,6 +93,8 @@ def build(experiment, case_dict):
     # create energy system
     micro_grid_system = solph.EnergySystem(timeindex=experiment[DATE_TIME_INDEX])
 
+    critical_constraint = case_dict.get(CRITICAL_CONSTRAINT, False)
+
     ###################################
     ## AC side of the energy system   #
     ###################################
@@ -93,10 +103,24 @@ def build(experiment, case_dict):
     bus_electricity_ac = solph.Bus(label=BUS_ELECTRICITY_AC)
     micro_grid_system.add(bus_electricity_ac)
 
-    # ------------demand sink ac------------#
-    sink_demand_ac = generate.demand_ac(
-        micro_grid_system, bus_electricity_ac, experiment[DEMAND_PROFILE_AC]
-    )
+    if critical_constraint is True:
+        # ------------demand sink ac critical ------------#
+        # the function already add the sink to the energy system
+        # demand_ac_critical \
+        sink_demand_ac, sink_demand_ac_reducable, sink_demand_ac_critical = generate.demand_critical(
+            micro_grid_system,
+            bus_electricity_ac,
+            experiment,
+            demand_type=DEMAND_AC_CRITICAL,
+        )
+    else:
+        # ------------demand sink ac------------#
+        # the function already add the sink to the energy system
+        sink_demand_ac = generate.demand(
+            micro_grid_system, bus_electricity_ac, experiment, demand_type=DEMAND_AC
+        )
+
+
 
     # ------------fuel source------------#
     if case_dict[GENSET_FIXED_CAPACITY] != None:
@@ -219,10 +243,9 @@ def build(experiment, case_dict):
 
     # ------------point of coupling (feedin)------------#
     if case_dict[PCC_FEEDIN_FIXED_CAPACITY] == None:
-        pass
-        # pointofcoupling_feedin = None
+        pointofcoupling_feedin = None
     elif case_dict[PCC_FEEDIN_FIXED_CAPACITY] is False:
-        generate.pointofcoupling_feedin_oem(
+        pointofcoupling_feedin = generate.pointofcoupling_feedin_oem(
             micro_grid_system,
             bus_electricity_ac,
             bus_electricity_ng_feedin,
@@ -231,7 +254,7 @@ def build(experiment, case_dict):
         )
 
     elif isinstance(case_dict[PCC_FEEDIN_FIXED_CAPACITY], float):
-        generate.pointofcoupling_feedin_fix(
+        pointofcoupling_feedin = generate.pointofcoupling_feedin_fix(
             micro_grid_system,
             bus_electricity_ac,
             bus_electricity_ng_feedin,
@@ -254,10 +277,23 @@ def build(experiment, case_dict):
     bus_electricity_dc = solph.Bus(label=BUS_ELECTRICITY_DC)
     micro_grid_system.add(bus_electricity_dc)
 
-    # ------------demand sink dc------------#
-    sink_demand_dc = generate.demand_dc(
-        micro_grid_system, bus_electricity_dc, experiment[DEMAND_PROFILE_DC]
-    )
+    if critical_constraint is True:
+        # ------------demand sink dc critical ------------#
+        # the function already add the sink to the energy system
+        #demand_dc_critical
+        sink_demand_dc, sink_demand_dc_reducable, sink_demand_dc_critical = generate.demand_critical(
+            micro_grid_system,
+            bus_electricity_dc,
+            experiment,
+            demand_type=DEMAND_DC_CRITICAL,
+        )
+    else:
+        # ------------demand sink dc------------#
+        # the function already add the sink to the energy system
+        sink_demand_dc = generate.demand(
+            micro_grid_system, bus_electricity_dc, experiment, demand_type=DEMAND_DC
+        )
+
 
     # ------------PV------------#
     if case_dict[PV_FIXED_CAPACITY] == None:
@@ -416,6 +452,7 @@ def build(experiment, case_dict):
             experiment=experiment,
             storage=storage,
             sink_demand=sink_demand_ac,
+            demand_ac_critical=demand_ac_critical,
             genset=genset,
             pcc_consumption=pointofcoupling_consumption,
             source_shortage=source_shortage,
@@ -429,6 +466,64 @@ def build(experiment, case_dict):
             + " faulty at stability_constraint. Value can only be False, float or None"
         )
 
+    # ------------Critical demand constraint------------#
+    if case_dict[CRITICAL_CONSTRAINT] is True:
+        logging.info("Added constraint: Critical demand fulfilled at all timesteps")
+
+        if case_dict[STABILITY_CONSTRAINT] != False:
+            raise ValueError(
+                "At the moment you cannot use the stability constraint with critical demand"
+            )
+
+        # list of assets which bring energy into the AC bus which could be used to fullfill critical demand
+        ac_generation_assets = [
+            asset
+            for asset in [
+                wind_plant,
+                pointofcoupling_consumption,
+                source_shortage,
+                inverter,
+            ]
+            if asset is not None
+        ]
+
+        if case_dict[GENSET_FIXED_CAPACITY] != None:
+            for number in range(1, case_dict[NUMBER_OF_EQUAL_GENERATORS] + 1):
+                ac_generation_assets.append(genset[number])
+
+        # TODO should we include the excess in the equation here?
+        # list of assets which take energy away from the AC bus which then compete with critical demand
+        ac_consumption_assets = [
+            asset
+            for asset in [pointofcoupling_feedin, rectifier, sink_demand_ac, sink_demand_ac_reducable]
+            if asset is not None
+        ]
+
+        # list of assets which bring energy into the DC bus which could be used to fullfill demand
+        dc_generation_assets = [
+            asset
+            for asset in [solar_plant, rectifier, source_shortage, storage]
+            if asset is not None
+        ]
+
+        # TODO should we include the excess in the equation here?
+        # list of assets which take energy away from the DC bus which then compete with critical demand
+        dc_consumption_assets = [
+            asset for asset in [inverter, storage, sink_demand_dc, sink_demand_dc_reducable] if asset is not None
+        ]
+
+        constraints_custom.critical(
+            model,
+            ac_generation_assets=ac_generation_assets,
+            ac_consumption_assets=ac_consumption_assets,
+            dc_generation_assets=dc_generation_assets,
+            dc_consumption_assets=dc_consumption_assets,
+            demand_dc_critical=sink_demand_dc_critical,
+            demand_ac_critical=sink_demand_ac_critical,
+            el_bus_ac=bus_electricity_ac,
+            el_bus_dc=bus_electricity_dc,
+        )
+
     # ------------Renewable share constraint------------#
     if case_dict[RENEWABLE_SHARE_CONSTRAINT] is False:
         pass
@@ -497,6 +592,7 @@ def build(experiment, case_dict):
             + " faulty at enable_inverter_at_backout. Value can only be True or False"
         )
 
+    # TODO maybe important for critical
     """
     # ------------Allow shortage only for certain percentage of demand in a timestep------------#
     if case_dict['allow_shortage'] is True:
diff --git a/src/G2a_oemof_busses_and_componets.py b/src/G2a_oemof_busses_and_componets.py
index d6ad3e6a..1a91564d 100644
--- a/src/G2a_oemof_busses_and_componets.py
+++ b/src/G2a_oemof_busses_and_componets.py
@@ -19,10 +19,14 @@
     PRICE_FUEL,
     COMBUSTION_VALUE_FUEL,
     SOURCE_SHORTAGE,
+    STABILITY_CONSTRAINT,
+    CRITICAL_CONSTRAINT,
     SHORTAGE_PENALTY_COST,
     MAX_SHORTAGE,
     TOTAL_DEMAND_AC,
     TOTAL_DEMAND_DC,
+    TOTAL_DEMAND_AC_CRITICAL,
+    TOTAL_DEMAND_DC_CRITICAL,
     BUS_ELECTRICITY_NG_CONSUMPTION,
     SOURCE_MAINGRID_CONSUMPTION,
     SINK_MAINGRID_CONSUMPTION_SYMBOLIC,
@@ -56,6 +60,7 @@
     MAINGRID_ELECTRICITY_PRICE,
     PCOUPLING_EFFICIENCY,
     GENERIC_STORAGE,
+    SHORTAGE_MAX_ALLOWED,
     STORAGE_SOC_INITIAL,
     STORAGE_CAPACITY_COST_ANNUITY,
     STORAGE_COST_VAR,
@@ -70,8 +75,15 @@
     SINK_EXCESS,
     TRANSFORMER_RECTIFIER,
     DISTRIBUTION_GRID_EFFICIENCY,
+    DEMAND_AC,
+    DEMAND_AC_CRITICAL,
+    DEMAND_DC,
+    DEMAND_DC_CRITICAL,
     SINK_DEMAND_AC,
     SINK_DEMAND_DC,
+    NON_CRITICAL_REDUCABLE_SUFFIX,
+    SINK_DEMAND_AC_CRITICAL,
+    SINK_DEMAND_DC_CRITICAL,
     SINK_MAINGRID_FEEDIN,
     GRID_AVAILABILITY,
     SINK_MAINGRID_FEEDIN_SYMBOLIC,
@@ -79,6 +91,7 @@
     WIND_GENERATION,
     WIND_COST_ANNUITY,
     BUS_ELECTRICITY_NG_FEEDIN,
+    TITLE_DEMAND_DC_CRITICAL,
 )
 
 ###############################################################################
@@ -110,22 +123,44 @@ def shortage(
     Creates source for shortages "source_shortage" including boundary conditions
     for maximal unserved demand and the variable costs of unserved demand.
     """
-    logging.debug("Added to oemof model: source shortage")
-    source_shortage = solph.Source(
-        label=SOURCE_SHORTAGE,
-        outputs={
-            bus_electricity_ac: solph.Flow(
-                variable_costs=experiment[SHORTAGE_PENALTY_COST],
-                nominal_value=case_dict[MAX_SHORTAGE] * case_dict[TOTAL_DEMAND_AC],
-                summed_max=1,
-            ),
-            bus_electricity_dc: solph.Flow(
-                variable_costs=experiment["shortage_penalty_costs"],
-                nominal_value=case_dict["max_shortage"] * case_dict["total_demand_dc"],
-                summed_max=1,
-            ),
-        },
-    )
+
+    critical_constraint = case_dict.get(CRITICAL_CONSTRAINT, False)
+    if critical_constraint is True:
+        logging.debug("Added to oemof model: source shortage for critical demand")
+        source_shortage = solph.Source(
+            label=SOURCE_SHORTAGE,
+            outputs={
+                bus_electricity_ac: solph.Flow(
+                    variable_costs=experiment[SHORTAGE_PENALTY_COST],
+                    nominal_value=case_dict[MAX_SHORTAGE]
+                    * case_dict[TOTAL_DEMAND_AC],
+                    summed_max=1,
+                ),
+                bus_electricity_dc: solph.Flow(
+                    variable_costs=experiment[SHORTAGE_PENALTY_COST],
+                    nominal_value=case_dict[MAX_SHORTAGE]
+                    * case_dict[TOTAL_DEMAND_DC],
+                    summed_max=1,
+                ),
+            },
+        )
+    else:
+        logging.debug("Added to oemof model: source shortage")
+        source_shortage = solph.Source(
+            label=SOURCE_SHORTAGE,
+            outputs={
+                bus_electricity_ac: solph.Flow(
+                    variable_costs=experiment[SHORTAGE_PENALTY_COST],
+                    nominal_value=case_dict[MAX_SHORTAGE] * case_dict[TOTAL_DEMAND_AC],
+                    summed_max=1,
+                ),
+                bus_electricity_dc: solph.Flow(
+                    variable_costs=experiment[SHORTAGE_PENALTY_COST],
+                    nominal_value=case_dict[MAX_SHORTAGE] * case_dict[TOTAL_DEMAND_DC],
+                    summed_max=1,
+                ),
+            },
+        )
     micro_grid_system.add(source_shortage)
     return source_shortage
 
@@ -485,7 +520,7 @@ def pointofcoupling_feedin_fix(
     )  # is efficiency of the generator?? Then this should later on be included as a function of the load factor
 
     micro_grid_system.add(pointofcoupling_feedin)
-    return
+    return pointofcoupling_feedin
 
 
 # point of coupling = max(demand) limits PV feed-in, therefore there should be a minimal pcc capacity defined with
@@ -517,7 +552,7 @@ def pointofcoupling_feedin_oem(
         conversion_factors={bus_electricity_ac: experiment[PCOUPLING_EFFICIENCY]},
     )
     micro_grid_system.add(pointofcoupling_feedin)
-    return
+    return pointofcoupling_feedin
 
 
 def pointofcoupling_consumption_fix(
@@ -701,34 +736,93 @@ def distribution_grid_ac(
     return distribution
 
 
-def demand_ac(micro_grid_system, bus_electricity_ac, demand_profile):
+def demand(micro_grid_system, bus_electricity, experiment, demand_type):
     """
-    Creates demand sink "sink_demand" with fixed flow
+    Creates demand sink of a demand type with a fixed flow
     """
-    logging.debug("Added to oemof model: demand AC")
+    dict_sink_names = {
+        DEMAND_AC: SINK_DEMAND_AC,
+        DEMAND_DC: SINK_DEMAND_DC,
+    }
+
+    if demand_type not in dict_sink_names:
+        logging.error(
+            f"The demand type you provided ({demand_type}), is not one if the allowed demand types: {','.join(dict_sink_names.keys())}"
+        )
+
+    logging.debug(f"Added to oemof model: {demand_type}")
     # create and add demand sink to micro_grid_system - fixed
-    sink_demand_ac = solph.Sink(
-        label=SINK_DEMAND_AC,
-        inputs={bus_electricity_ac: solph.Flow(fix=demand_profile, nominal_value=1)},
+
+    sink_demand = solph.Sink(
+        label=dict_sink_names[demand_type],
+        inputs={
+            bus_electricity: solph.Flow(fix=experiment[demand_type], nominal_value=1)
+        },
     )
 
-    micro_grid_system.add(sink_demand_ac)
-    return sink_demand_ac
+    micro_grid_system.add(sink_demand)
+    return sink_demand
 
 
-def demand_dc(micro_grid_system, bus_electricity_dc, demand_profile):
+def demand_critical(micro_grid_system, bus_electricity, experiment, demand_type):
     """
-    Creates demand sink "sink_demand" with fixed flow
+    Creates 3 demand sinks: one fix with critical demand, and the non critical demand is modelled
+    by two sinks, one of a demand type with a fixed flow (non critical demand needed to be supplied) and
+    one with a demand type that can be reduced if demand shortages are allowed
     """
-    logging.debug("Added to oemof model: demand DC")
+    dict_sink_names = {
+        DEMAND_AC_CRITICAL: SINK_DEMAND_AC_CRITICAL,
+        DEMAND_DC_CRITICAL: SINK_DEMAND_DC_CRITICAL,
+    }
+
+    if demand_type not in dict_sink_names:
+        logging.error(
+            f"The demand type you provided ({demand_type}), is not one if the allowed demand types: {','.join(dict_sink_names.keys())}"
+        )
+
+    logging.debug(f"Added to oemof model: {demand_type}")
     # create and add demand sink to micro_grid_system - fixed
-    sink_demand_dc = solph.Sink(
-        label="sink_demand_dc",
-        inputs={bus_electricity_dc: solph.Flow(fix=demand_profile, nominal_value=1)},
+
+    logging.warning(f"experiment[SHORTAGE_MAX_ALLOWED]: {experiment[SHORTAGE_MAX_ALLOWED]}")
+
+    # The demand shortage is only allowed on the non-critical demand
+    if demand_type == DEMAND_AC_CRITICAL:
+        non_critical_demand_type = DEMAND_AC
+        non_critical_sink_name = SINK_DEMAND_AC
+    else:
+        non_critical_demand_type = DEMAND_DC
+        non_critical_sink_name = SINK_DEMAND_DC
+
+    # critical demand, need to be supplied
+    sink_demand_critical = solph.Sink(
+        label=dict_sink_names[demand_type],
+        inputs={
+            bus_electricity: solph.Flow(fix=experiment[demand_type], nominal_value=1)
+        },
     )
-    micro_grid_system.add(sink_demand_dc)
-    return sink_demand_dc
 
+    # reducable non critical demand, a percent can be subject to demand shortages, i.e. demand reductions
+    sink_demand_non_critical_reducable = solph.Sink(
+        label=non_critical_sink_name + NON_CRITICAL_REDUCABLE_SUFFIX,
+        inputs={
+            bus_electricity: solph.Flow(max=experiment[SHORTAGE_MAX_ALLOWED]*experiment[non_critical_demand_type],
+                                        nominal_value=1,variable_costs=-0.01)
+        },
+    )
+    # non critical demand, this portion cannot be subject to demand shortages, i.e. demand reductions
+    sink_demand_non_critical = solph.Sink(
+        label=non_critical_sink_name,
+        inputs={
+            bus_electricity: solph.Flow(fix=experiment[non_critical_demand_type] * (1 - experiment[SHORTAGE_MAX_ALLOWED]),
+                                        nominal_value=1)
+        },
+    )
+
+    micro_grid_system.add(sink_demand_critical)
+    micro_grid_system.add(sink_demand_non_critical_reducable)
+    micro_grid_system.add(sink_demand_non_critical)
+
+    return sink_demand_non_critical, sink_demand_non_critical_reducable, sink_demand_critical
 
 def maingrid_feedin(micro_grid_system, experiment):
     logging.debug("Added to oemof model: maingrid feedin")
diff --git a/src/G2b_constraints_custom.py b/src/G2b_constraints_custom.py
index debfbffc..c7b16c3a 100644
--- a/src/G2b_constraints_custom.py
+++ b/src/G2b_constraints_custom.py
@@ -61,6 +61,9 @@ def backup(
     el_bus_ac,
     el_bus_dc,
 ):
+
+    raise ValueError("backup")
+
     stability_limit = experiment[SHORTAGE_LIMIT]
     ## ------- Get CAP genset ------- #
     CAP_genset = 0
@@ -168,6 +171,8 @@ def backup_test(case_dict, oemof_results, experiment, e_flows_df):
     """
     Testing simulation results for adherance to above defined stability criterion
     """
+
+    raise ValueError("backup test")
     if case_dict[STABILITY_CONSTRAINT] != False:
         demand_profile = e_flows_df[DEMAND]
 
@@ -250,34 +255,57 @@ def hybrid(
     source_shortage,
     el_bus_ac,
     el_bus_dc,
+    demand_ac_critical=None,
 ):
 
     stability_limit = experiment[SHORTAGE_LIMIT]
+    print(case_dict[ALLOW_SHORTAGE])
+    print(case_dict[GENSET_FIXED_CAPACITY])
+    print(case_dict[STORAGE_FIXED_CAPACITY])
+    import ipdb
+
+    ipdb.set_trace()
+
+    # ac_critical_demand = model.flow[el_bus_ac, demand_ac_critical, t]
 
     def stability_rule_capacity(model, t):
         expr = 0
         ## ------- Get demand at t ------- #
+        # TODO adapt this
         demand = model.flow[el_bus_ac, sink_demand, t]
         expr += -stability_limit * demand
 
+        # Current state
+        # -stability*demand_nc + stability*shortage + SUM_i genset_i + storage_out (can be negative or positive) >= 0
+
+        # what do we want?
+        # a) -stability*(demand_nc + demand_c) + stabililty*shortage + SUM_i genset_i + storage_out (can be negative or positive) >= 0
+        # b) -stability*(demand_c) + stability*shortage + SUM_i genset_i + storage_out (can be negative or positive) >= 0
+
         ## ------- Get shortage at t------- #
         if case_dict[ALLOW_SHORTAGE] is True:
+            # TODO this is considered
             shortage = model.flow[source_shortage, el_bus_ac, t]
-            expr += +stability_limit * shortage
+            expr += stability_limit * shortage
 
         ## ------- Generation Diesel ------- #
         if case_dict[GENSET_FIXED_CAPACITY] != None:
+            # TODO this is considered
             for number in range(1, case_dict[NUMBER_OF_EQUAL_GENERATORS] + 1):
                 expr += model.flow[genset[number], el_bus_ac, t]
 
         ##---------Grid consumption t-------#
         if case_dict[PCC_CONSUMPTION_FIXED_CAPACITY] != None:
+            # TODO this is NOT considered
             expr += model.flow[pcc_consumption, el_bus_ac, t]
 
         ## ------- Get stored capacity storage at t------- #
         if case_dict[STORAGE_FIXED_CAPACITY] != None:
+            # TODO this is considered
+
             stored_electricity = 0
             if case_dict[STORAGE_FIXED_CAPACITY] is False:  # Storage subject to OEM
+                # TODO this is considered
                 stored_electricity += (
                     model.GenericInvestmentStorageBlock.storage_content[storage, t]
                     - experiment[STORAGE_SOC_MIN]
@@ -286,6 +314,7 @@ def stability_rule_capacity(model, t):
             elif isinstance(
                 case_dict[STORAGE_FIXED_CAPACITY], float
             ):  # Fixed storage subject to dispatch
+                # TODO this is NOT considered
                 stored_electricity += (
                     model.GenericStorageBlock.storage_content[storage, t]
                     - experiment[STORAGE_SOC_MIN] * storage.nominal_capacity
@@ -308,24 +337,36 @@ def stability_rule_power(model, t):
         demand = model.flow[el_bus_ac, sink_demand, t]
         expr += -stability_limit * demand
 
+        # Current state
+        # -stability_limit*demand_nc + stability*shortage + SUM_i genset_i + storage_out (can be negative or positive) >= 0
+
+        # what do we want?
+        # a) -stability*(demand_nc + demand_c) + stabililty*shortage + SUM_i genset_i + storage_out (can be negative or positive) >= 0
+        # b) -stability*(demand_c) + stability*shortage + SUM_i genset_i + storage_out (can be negative or positive) >= 0
+
         ## ------- Get shortage at t------- #
         if case_dict[ALLOW_SHORTAGE] is True:
+            # TODO this is considered
             shortage = model.flow[source_shortage, el_bus_ac, t]
             expr += +stability_limit * shortage
 
         ## ------- Generation Diesel ------- #
         if case_dict[GENSET_FIXED_CAPACITY] != None:
+            # TODO this is considered
             for number in range(1, case_dict[NUMBER_OF_EQUAL_GENERATORS] + 1):
                 expr += model.flow[genset[number], el_bus_ac, t]
 
         ##---------Grid consumption t-------#
         if case_dict[PCC_CONSUMPTION_FIXED_CAPACITY] != None:
+            # TODO this is NOT considered
             expr += model.flow[pcc_consumption, el_bus_ac, t]
 
         ## ------- Get power of storage ------- #
         if case_dict[STORAGE_FIXED_POWER] != None:
+            # TODO this is considered
             storage_power = 0
             if case_dict[STORAGE_FIXED_CAPACITY] is False:
+                # TODO this is considered
                 storage_power += model.InvestmentFlow.invest[storage, el_bus_dc]
             elif isinstance(case_dict[STORAGE_FIXED_CAPACITY], float):
                 storage_power += case_dict[STORAGE_FIXED_POWER]
@@ -419,7 +460,7 @@ def hybrid_test(case_dict, oemof_results, experiment, e_flows_df):
                 ],
                 index=demand_profile.index,
             )
-            ratio_below_zero = ratio.clip_upper(0)
+            ratio_below_zero = ratio.clip(upper=0)
             test_warning(ratio_below_zero, oemof_results, boolean_test)
 
     else:
@@ -440,6 +481,8 @@ def usage(
     el_bus,
 ):
 
+    raise ValueError("usage")
+
     stability_limit = experiment[SHORTAGE_LIMIT]
 
     def stability_rule(model, t):
@@ -676,6 +719,73 @@ def share_test(case_dict, oemof_results, experiment):
     return
 
 
+def critical(
+    model,
+    el_bus_ac=None,
+    el_bus_dc=None,
+    demand_ac_critical=None,
+    demand_dc_critical=None,
+    ac_generation_assets=None,
+    ac_consumption_assets=None,
+    dc_generation_assets=None,
+    dc_consumption_assets=None,
+):
+    """
+    Force the system to always meet the critical demand over the non-critical one
+
+    Parameters
+    - - - - - - - -
+    model: oemof.solph.model
+
+    list of production assets and busses connected to them
+
+    list of critical demand assets and busses connected to them
+
+    """
+    # TODO check if this constraint conflicts with other ones, then issue a warning to the user
+
+    def meet_critical_ac_demand_rule(model, t):
+        """
+        wind + genset + inverter + pcc_consumption + shortage - rectifier - pcc_feedin - non-critical demand - critical demand >= 0
+        """
+        ac_production = 0
+        for ac_asset in ac_generation_assets:
+            ac_production += model.flow[ac_asset, el_bus_ac, t]
+
+        ac_consumption = 0
+        for ac_asset in ac_consumption_assets:
+            ac_consumption += model.flow[el_bus_ac, ac_asset, t]
+
+        ac_critical_demand = model.flow[el_bus_ac, demand_ac_critical, t]
+
+        return ac_production - ac_consumption - ac_critical_demand >= 0
+
+    def meet_critical_dc_demand_rule(model, t):
+        """
+        PV + storage-discharge + shortage + rectifier - inverter - storage-charge - non-critical demand - critical demand >= 0
+        """
+        dc_production = 0
+        for dc_asset in dc_generation_assets:
+            dc_production += model.flow[dc_asset, el_bus_dc, t]
+
+        dc_consumption = 0
+        for dc_asset in dc_consumption_assets:
+            dc_consumption += model.flow[el_bus_dc, dc_asset, t]
+
+        dc_critical_demand = model.flow[el_bus_dc, demand_dc_critical, t]
+
+        return dc_production - dc_consumption - dc_critical_demand >= 0
+
+    model.critical_constraint_ac = po.Constraint(
+        model.TIMESTEPS, rule=meet_critical_ac_demand_rule
+    )
+    model.critical_constraint_dc = po.Constraint(
+        model.TIMESTEPS, rule=meet_critical_dc_demand_rule
+    )
+
+    return model
+
+
 def forced_charge(model, case_dict, el_bus_dc, storage, experiment):
     ## ------- Get CAP Storage ------- #
     CAP_storage = 0
@@ -705,9 +815,9 @@ def linear_charge(model, t):
         expr = 0
         if case_dict[STORAGE_FIXED_CAPACITY] != None:
             if case_dict[STORAGE_FIXED_CAPACITY] is False:  # Storage subject to OEM
-                stored_electricity += model.GenericInvestmentStorageBlock.storage_content[
-                    storage, t
-                ]
+                stored_electricity += (
+                    model.GenericInvestmentStorageBlock.storage_content[storage, t]
+                )
             elif isinstance(
                 case_dict[STORAGE_FIXED_CAPACITY], float
             ):  # Fixed storage subject to dispatch
@@ -814,9 +924,9 @@ def discharge_rule_upper(model, t):
             expr += model.flow[storage, el_bus, t]
             # Get stored electricity at t
             if case_dict[STORAGE_FIXED_CAPACITY] is False:  # Storage subject to OEM
-                stored_electricity += model.GenericInvestmentStorageBlock.storage_content[
-                    storage, t
-                ]
+                stored_electricity += (
+                    model.GenericInvestmentStorageBlock.storage_content[storage, t]
+                )
             elif isinstance(
                 case_dict[STORAGE_FIXED_CAPACITY], float
             ):  # Fixed storage subject to dispatch
diff --git a/src/G3_oemof_evaluate.py b/src/G3_oemof_evaluate.py
index 8af664aa..3d8905ff 100644
--- a/src/G3_oemof_evaluate.py
+++ b/src/G3_oemof_evaluate.py
@@ -16,14 +16,20 @@
     EVALUATED_DAYS,
     DATE_TIME_INDEX,
     DEMAND,
+    DEMAND_CRITICAL,
+    DEMAND_NON_CRITICAL,
     SEQUENCES,
     BUS_ELECTRICITY_AC,
     SINK_DEMAND_AC,
+    SINK_DEMAND_AC_CRITICAL,
+SINK_DEMAND_AC_REDUCABLE,
     FLOW,
     EVALUATION_PERSPECTIVE,
     INVERTER_DC_AC_EFFICIENCY,
     BUS_ELECTRICITY_DC,
     SINK_DEMAND_DC,
+    SINK_DEMAND_DC_CRITICAL,
+SINK_DEMAND_DC_REDUCABLE,
     RECTIFIER_AC_DC_EFFICIENCY,
     TOTAL_DEMAND_ANNUAL_KWH,
     DEMAND_PEAK_KW,
@@ -117,7 +123,12 @@
     FEED_INTO_MAIN_GRID_MG_SIDE,
     DEMAND_AC,
     DEMAND_DC,
+    DEMAND_AC_CRITICAL,
+    DEMAND_DC_CRITICAL,
+    DEMAND_NON_CRITICAL_REDUCABLE,
     GENSET_HOURS_OF_OPERATION,
+    CRITICAL_CONSTRAINT,
+    CRITICAL,
 )
 
 
@@ -145,6 +156,8 @@ def get_demand(
         columns=[DEMAND],
         index=experiment[DATE_TIME_INDEX],
     )
+
+
     demand_ac = electricity_bus_ac[SEQUENCES][
         ((BUS_ELECTRICITY_AC, SINK_DEMAND_AC), FLOW)
     ]
@@ -166,7 +179,62 @@ def get_demand(
     else:
         e_flows_df[DEMAND] += demand_dc
 
+    critical_constraint = case_dict.get(CRITICAL_CONSTRAINT, False)
+    if critical_constraint is True:
+
+        # when the critical constraint is on, the non critical demand is split between two sinks
+        # SINK_DEMAND_AC and SINK_DEMAND_AC_REDUCABLE, SINK_DEMAND_AC was already considered above so
+        # only SINK_DEMAND_AC_REDUCABLE is added now
+        demand_ac_non_critical_reducable = electricity_bus_ac[SEQUENCES][
+            ((BUS_ELECTRICITY_AC, SINK_DEMAND_AC_REDUCABLE), FLOW)
+        ]
+        e_flows_df = join_e_flows_df(demand_ac_non_critical_reducable, DEMAND_NON_CRITICAL_REDUCABLE, e_flows_df)
+        if case_dict[EVALUATION_PERSPECTIVE] == AC_SYSTEM:
+            e_flows_df[DEMAND] += demand_ac_non_critical_reducable
+        else:
+            e_flows_df[DEMAND] += demand_ac_non_critical_reducable / experiment[INVERTER_DC_AC_EFFICIENCY]
+
+        demand_dc_non_critical_reducable = electricity_bus_dc[SEQUENCES][
+            ((BUS_ELECTRICITY_DC, SINK_DEMAND_DC_REDUCABLE), FLOW)
+        ]
+        if case_dict[EVALUATION_PERSPECTIVE] == AC_SYSTEM:
+            e_flows_df[DEMAND] += demand_dc_non_critical_reducable / experiment[RECTIFIER_AC_DC_EFFICIENCY]
+        else:
+            e_flows_df[DEMAND] += demand_dc_non_critical_reducable
+
+
+
+        e_flows_df[DEMAND_CRITICAL] = 0
+        # Add the critical demand to the total demand
+        demand_ac_critical = electricity_bus_ac[SEQUENCES][
+            ((BUS_ELECTRICITY_AC, SINK_DEMAND_AC_CRITICAL), FLOW)
+        ]
+        e_flows_df = join_e_flows_df(demand_ac_critical, DEMAND_AC_CRITICAL, e_flows_df)
+        if case_dict[EVALUATION_PERSPECTIVE] == AC_SYSTEM:
+            e_flows_df[DEMAND_CRITICAL] += demand_ac_critical
+        else:
+            e_flows_df[DEMAND_CRITICAL] += (
+                demand_ac_critical / experiment[INVERTER_DC_AC_EFFICIENCY]
+            )
+
+        demand_dc_critical = electricity_bus_dc[SEQUENCES][
+            ((BUS_ELECTRICITY_DC, SINK_DEMAND_DC), FLOW)
+        ]
+        e_flows_df = join_e_flows_df(demand_dc_critical, DEMAND_DC_CRITICAL, e_flows_df)
+        if case_dict[EVALUATION_PERSPECTIVE] == AC_SYSTEM:
+            e_flows_df[DEMAND_CRITICAL] += (
+                demand_dc_critical / experiment[RECTIFIER_AC_DC_EFFICIENCY]
+            )
+        else:
+            e_flows_df[DEMAND_CRITICAL] += demand_dc_critical
+
+        # add the critical demand to the total demand and the non critical demand
+        # is simply equal to the demand
+        e_flows_df[DEMAND_NON_CRITICAL] = e_flows_df[DEMAND]
+        e_flows_df[DEMAND] += e_flows_df[DEMAND_CRITICAL]
+
     annual_value(TOTAL_DEMAND_ANNUAL_KWH, e_flows_df[DEMAND], oemof_results, case_dict)
+
     oemof_results.update({DEMAND_PEAK_KW: max(e_flows_df[DEMAND])})
     return e_flows_df
 
@@ -190,6 +258,7 @@ def get_shortage(
             shortage_ac = electricity_bus_ac[SEQUENCES][
                 ((SOURCE_SHORTAGE, BUS_ELECTRICITY_AC), FLOW)
             ]
+            # aggregated flow into the AC bus
             annual_value(
                 TOTAL_DEMAND_SHORTAGE_AC_ANNUAL_KWH,
                 shortage_ac,
@@ -208,6 +277,7 @@ def get_shortage(
             shortage_dc = electricity_bus_dc[SEQUENCES][
                 ((SOURCE_SHORTAGE, BUS_ELECTRICITY_DC), FLOW)
             ]
+            # aggregated flow into the DC bus
             annual_value(
                 TOTAL_DEMAND_SHORTAGE_DC_ANNUAL_KWH,
                 shortage_dc,
@@ -221,9 +291,22 @@ def get_shortage(
             else:
                 shortage += shortage_dc
 
-        demand_supplied = e_flows_df[DEMAND] - shortage
+        # TODO make sure this does not raise errors when used without critical demand option
+        if case_dict[EVALUATION_PERSPECTIVE] == AC_SYSTEM:
+            # todo something here is fishy
+            demand_supplied = (
+                e_flows_df[DEMAND_AC_CRITICAL] + e_flows_df[DEMAND_AC] - shortage
+            )
+        else:
+            demand_supplied = (
+                e_flows_df[DEMAND_DC_CRITICAL] + e_flows_df[DEMAND_DC] - shortage
+            )
+
         annual_value(
-            TOTAL_DEMAND_SUPPLIED_ANNUAL_KWH, demand_supplied, oemof_results, case_dict,
+            TOTAL_DEMAND_SUPPLIED_ANNUAL_KWH,
+            demand_supplied,
+            oemof_results,
+            case_dict,
         )
         annual_value(
             TOTAL_DEMAND_SHORTAGE_ANNUAL_KWH, shortage, oemof_results, case_dict
@@ -395,7 +478,10 @@ def get_inverter(
         e_flows_df = join_e_flows_df(inverter_in, INVERTER_INPUT, e_flows_df)
 
         annual_value(
-            TOTAL_INVERTER_DC_AC_THROUGHPUT_KWH, inverter_in, oemof_results, case_dict,
+            TOTAL_INVERTER_DC_AC_THROUGHPUT_KWH,
+            inverter_in,
+            oemof_results,
+            case_dict,
         )
     else:
         oemof_results.update({TOTAL_INVERTER_DC_AC_THROUGHPUT_KWH: 0})
@@ -471,7 +557,10 @@ def get_genset(case_dict, oemof_results, electricity_bus_ac, e_flows_df):
         total_genset = genset
         for number in range(2, case_dict[NUMBER_OF_EQUAL_GENERATORS] + 1):
             genset = electricity_bus_ac[SEQUENCES][
-                ((TRANSFORMER_GENSET_ + str(number), BUS_ELECTRICITY_AC), FLOW,)
+                (
+                    (TRANSFORMER_GENSET_ + str(number), BUS_ELECTRICITY_AC),
+                    FLOW,
+                )
             ]
             e_flows_df = join_e_flows_df(
                 genset, "Genset " + str(number) + " generation", e_flows_df
@@ -490,7 +579,10 @@ def get_genset(case_dict, oemof_results, electricity_bus_ac, e_flows_df):
         genset_capacity = 0
         for number in range(1, case_dict[NUMBER_OF_EQUAL_GENERATORS] + 1):
             genset_capacity += electricity_bus_ac[SCALARS][
-                ((TRANSFORMER_GENSET_ + str(number), BUS_ELECTRICITY_AC), INVEST,)
+                (
+                    (TRANSFORMER_GENSET_ + str(number), BUS_ELECTRICITY_AC),
+                    INVEST,
+                )
             ]
         oemof_results.update({CAPACITY_GENSET_KW: genset_capacity})
     elif isinstance(case_dict[GENSET_FIXED_CAPACITY], float):
@@ -604,7 +696,10 @@ def get_storage(case_dict, oemof_results, experiment, results, e_flows_df):
         ]
 
         oemof_results.update(
-            {CAPACITY_STORAGE_KWH: storage_capacity, POWER_STORAGE_KW: storage_power,}
+            {
+                CAPACITY_STORAGE_KWH: storage_capacity,
+                POWER_STORAGE_KW: storage_power,
+            }
         )
 
     elif isinstance(case_dict[STORAGE_FIXED_CAPACITY], float):
@@ -669,7 +764,10 @@ def get_national_grid(case_dict, oemof_results, results, e_flows_df, grid_availa
             results, BUS_ELECTRICITY_NG_CONSUMPTION
         )
         consumption_utility_side = bus_electricity_ng_consumption[SEQUENCES][
-            ((BUS_ELECTRICITY_NG_CONSUMPTION, TRANSFORMER_PCC_CONSUMPTION), FLOW,)
+            (
+                (BUS_ELECTRICITY_NG_CONSUMPTION, TRANSFORMER_PCC_CONSUMPTION),
+                FLOW,
+            )
         ]
         e_flows_df = join_e_flows_df(
             consumption_utility_side,
diff --git a/src/G3b_plausability_tests.py b/src/G3b_plausability_tests.py
index d55d3505..234b1798 100644
--- a/src/G3b_plausability_tests.py
+++ b/src/G3b_plausability_tests.py
@@ -6,6 +6,7 @@
     COMMENTS,
     DEMAND_SUPPLIED,
     DEMAND,
+    DEMAND_AC,
     DEMAND_SHORTAGE,
     CONSUMPTION_FROM_MAIN_GRID,
     FEED_INTO_MAIN_GRID,
@@ -90,7 +91,7 @@ def demand_supply_shortage(oemof_results, e_flows_df):
     logging.debug("Plausibility test: Demand/Supply/Shortage")
     if (
         (DEMAND_SUPPLIED in e_flows_df.columns)
-        and (DEMAND in e_flows_df.columns)
+        and (DEMAND_AC in e_flows_df.columns)
         and (DEMAND_SHORTAGE in e_flows_df.columns)
     ):
 
@@ -99,12 +100,12 @@ def demand_supply_shortage(oemof_results, e_flows_df):
         test = [
             (
                 (
-                    e_flows_df[DEMAND_SUPPLIED][t] == e_flows_df[DEMAND][t]
+                    e_flows_df[DEMAND_SUPPLIED][t] == e_flows_df[DEMAND_AC][t]
                     and e_flows_df[DEMAND_SHORTAGE][t] == 0
                 )
                 or (
                     (
-                        e_flows_df[DEMAND_SUPPLIED][t] != e_flows_df[DEMAND][t]
+                        e_flows_df[DEMAND_SUPPLIED][t] != e_flows_df[DEMAND_AC][t]
                         and e_flows_df[DEMAND_SHORTAGE][t] != 0
                     )
                 )
diff --git a/src/G4_output_functions.py b/src/G4_output_functions.py
index ffca2fed..dbb5c885 100644
--- a/src/G4_output_functions.py
+++ b/src/G4_output_functions.py
@@ -37,6 +37,8 @@
     GENSET_GENERATION,
     GRID_AVAILABILITY,
     DEMAND,
+    DEMAND_CRITICAL,
+    DEMAND_NON_CRITICAL,
     FEED_INTO_MAIN_GRID,
     CONSUMPTION_FROM_MAIN_GRID,
     SAVE_TO_CSV_FLOWS_ELECTRICITY_MG,
@@ -55,6 +57,10 @@
     FEED_INTO_MAIN_GRID_MG_SIDE,
     DEMAND_AC,
     DEMAND_DC,
+    DEMAND_AC_CRITICAL,
+    DEMAND_DC_CRITICAL,
+DEMAND_NON_CRITICAL_REDUCABLE,
+    CRITICAL_CONSTRAINT,
     SUFFIX_GRAPH,
     BASE_OEM,
     BASE_OEM_WITH_MIN_LOADING,
@@ -66,6 +72,25 @@
     SUFFIX_STORAGE_4DAYS_PNG,
 )
 
+# website with websafe hexacolours: https://www.colorhexa.com/web-safe-colors
+COLOR_DICT = {
+    DEMAND: "#33ff00",  # dark green
+    DEMAND_SUPPLIED: "#66cc33",  # grass green
+    DEMAND_CRITICAL: "#009900",  # green
+    DEMAND_NON_CRITICAL: "#33ffcc",  # green blue
+    PV_GENERATION: "#ffcc00",  # orange
+    WIND_GENERATION: "#33ccff",  # light blue
+    GENSET_GENERATION: "#000000",  # black
+    CONSUMPTION_FROM_MAIN_GRID: "#990099",  # violet
+    STORAGE_CHARGE: "#0033cc",  # light green
+    EXCESS_GENERATION: "#996600",  # brown
+    FEED_INTO_MAIN_GRID: "#ff33cc",  # pink
+    STORAGE_DISCHARGE: "#ccccff",  # pidgeon blue
+    DEMAND_SHORTAGE: "#ff3300",  # bright red
+    STORAGE_SOC: "#0033cc",  # blue
+    GRID_AVAILABILITY: "#cc0000",  # red
+}
+
 
 def print_oemof_meta_main_invest(experiment, meta, electricity_bus, case_name):
     if experiment[DISPLAY_META] is True:
@@ -135,8 +160,21 @@ def save_mg_flows(experiment, case_dict, e_flows_df, filename):
         STORAGE_CHARGE_DC,
     ]
 
+    critical_constraint = case_dict.get(CRITICAL_CONSTRAINT, False)
+    if critical_constraint is True:
+        flows_connected_to_electricity_mg_bus = (
+            [DEMAND_NON_CRITICAL, DEMAND_CRITICAL, DEMAND_NON_CRITICAL_REDUCABLE]
+            + flows_connected_to_electricity_mg_bus[:2]
+            + [DEMAND_AC_CRITICAL, DEMAND_DC_CRITICAL]
+            + flows_connected_to_electricity_mg_bus[2:]
+        )
+
+        droplist += [DEMAND_AC_CRITICAL, DEMAND_DC_CRITICAL]
+
     mg_flows = pd.DataFrame(
-        e_flows_df[DEMAND].values, columns=[DEMAND], index=e_flows_df[DEMAND].index,
+        e_flows_df[DEMAND].values,
+        columns=[DEMAND],
+        index=e_flows_df[DEMAND].index,
     )
     for entry in flows_connected_to_electricity_mg_bus:
         if entry in e_flows_df.columns:
@@ -250,31 +288,15 @@ def plot_flows(case_dict, experiment, mg_flows, e_flows_df, number_of_subplots):
         fig, axes = plt.subplots(nrows=2, figsize=(16 / 2.54, 10 / 2.54))
         axes_mg = axes[0]
 
-    # website with websafe hexacolours: https://www.colorhexa.com/web-safe-colors
-    color_dict = {
-        DEMAND: "#33ff00",  # dark green
-        DEMAND_SUPPLIED: "#66cc33",  # grass green
-        PV_GENERATION: "#ffcc00",  # orange
-        WIND_GENERATION: "#33ccff",  # light blue
-        GENSET_GENERATION: "#000000",  # black
-        CONSUMPTION_FROM_MAIN_GRID: "#990099",  # violet
-        STORAGE_CHARGE: "#0033cc",  # light green
-        EXCESS_GENERATION: "#996600",  # brown
-        FEED_INTO_MAIN_GRID: "#ff33cc",  # pink
-        STORAGE_DISCHARGE: "#ccccff",  # pidgeon blue
-        DEMAND_SHORTAGE: "#ff3300",  # bright red
-        STORAGE_SOC: "#0033cc",  # blue
-        GRID_AVAILABILITY: "#cc0000",  # red
-    }
-
     mg_flows.plot(
         title="MG Operation of case "
         + case_dict[CASE_NAME]
         + " in "
         + experiment[PROJECT_SITE_NAME],
-        color=[color_dict.get(x, "#333333") for x in mg_flows.columns],
+        color=[COLOR_DICT.get(x, "#333333") for x in mg_flows.columns],
         ax=axes_mg,
         drawstyle="steps-mid",
+        # style=[":" if "ritical" in x else "-" for x in mg_flows.columns]
     )
     axes_mg.set(xlabel="Time", ylabel="Electricity flow in kWh")
     axes_mg.legend(loc="center left", bbox_to_anchor=(1, 0.5), frameon=False)
@@ -287,7 +309,7 @@ def plot_flows(case_dict, experiment, mg_flows, e_flows_df, number_of_subplots):
         ) and (GRID_AVAILABILITY in e_flows_df.columns):
             e_flows_df[GRID_AVAILABILITY].plot(
                 ax=axes[1],
-                color=color_dict.get(GRID_AVAILABILITY, "#333333"),
+                color=COLOR_DICT.get(GRID_AVAILABILITY, "#333333"),
                 drawstyle="steps-mid",
             )
             ylabel += GRID_AVAILABILITY
@@ -300,7 +322,7 @@ def plot_flows(case_dict, experiment, mg_flows, e_flows_df, number_of_subplots):
         ):
             e_flows_df[STORAGE_SOC].plot(
                 ax=axes[1],
-                color=color_dict.get(STORAGE_SOC, "#333333"),
+                color=COLOR_DICT.get(STORAGE_SOC, "#333333"),
                 drawstyle="steps-mid",
             )
             ylabel += STORAGE_SOC
diff --git a/src/cli.py b/src/cli.py
index cce6e0cd..f7c8d75f 100644
--- a/src/cli.py
+++ b/src/cli.py
@@ -152,12 +152,11 @@ def main(input_file=None):
     # import all scripts necessary for loop
     experiment_count = 0
     total_number_of_simulations = settings[TOTAL_NUMBER_OF_EXPERIMENTS] * len(case_list)
-
-    for experiment in sensitivity_experiment_s:
+    for experiment_id in sensitivity_experiment_s:
 
         capacities_oem = {}
 
-        if GRID_AVAILABILITY in sensitivity_experiment_s[experiment].keys():
+        if GRID_AVAILABILITY in sensitivity_experiment_s[experiment_id].keys():
             logging.debug(
                 "Using grid availability as included in timeseries file of project location."
             )
@@ -168,9 +167,9 @@ def main(input_file=None):
                 "Using grid availability timeseries that was randomly generated."
             )
             blackout_experiment_name = generate_sensitvitiy_experiments.get_blackout_experiment_name(
-                sensitivity_experiment_s[experiment]
+                sensitivity_experiment_s[experiment_id]
             )
-            sensitivity_experiment_s[experiment].update(
+            sensitivity_experiment_s[experiment_id].update(
                 {
                     GRID_AVAILABILITY: sensitivity_grid_availability[
                         blackout_experiment_name
@@ -187,7 +186,7 @@ def main(input_file=None):
             experiment_case_dict = cases.update_dict(
                 capacities_oem,
                 case_definitions[specific_case],
-                sensitivity_experiment_s[experiment],
+                sensitivity_experiment_s[experiment_id],
             )
 
             ###############################################################################
@@ -200,7 +199,7 @@ def main(input_file=None):
                 + specific_case
                 + ", "
                 + "project site "
-                + sensitivity_experiment_s[experiment][PROJECT_SITE_NAME]
+                + sensitivity_experiment_s[experiment_id][PROJECT_SITE_NAME]
                 + ", "
                 + "experiment no. "
                 + str(experiment_count)
@@ -211,7 +210,7 @@ def main(input_file=None):
 
             # Run simulation, evaluate results
             oemof_results = oemof_simulate.run(
-                sensitivity_experiment_s[experiment], experiment_case_dict
+                sensitivity_experiment_s[experiment_id], experiment_case_dict
             )
 
             # Extend base capacities for cases utilizing these values, only valid for specific experiment
@@ -225,9 +224,9 @@ def main(input_file=None):
                 )
 
             # Extend oemof_results by blackout characteristics
-            if GRID_AVAILABILITY in sensitivity_experiment_s[experiment].keys():
+            if GRID_AVAILABILITY in sensitivity_experiment_s[experiment_id].keys():
                 blackout_result = central_grid.oemof_extension_for_blackouts(
-                    sensitivity_experiment_s[experiment][GRID_AVAILABILITY]
+                    sensitivity_experiment_s[experiment_id][GRID_AVAILABILITY]
                 )
                 oemof_results = central_grid.extend_oemof_results(
                     oemof_results, blackout_result
@@ -239,13 +238,13 @@ def main(input_file=None):
 
             # Extend overall results dataframe with simulation results
             overall_results = helpers.store_result_matrix(
-                overall_results, sensitivity_experiment_s[experiment], oemof_results
+                overall_results, sensitivity_experiment_s[experiment_id], oemof_results
             )
             # Writing DataFrame with all results to csv file
             overall_results.to_csv(
-                sensitivity_experiment_s[experiment][OUTPUT_FOLDER]
+                sensitivity_experiment_s[experiment_id][OUTPUT_FOLDER]
                 + "/"
-                + sensitivity_experiment_s[experiment][OUTPUT_FILE]
+                + sensitivity_experiment_s[experiment_id][OUTPUT_FILE]
                 + ".csv"
             )  # moved from below
 
@@ -267,7 +266,7 @@ def main(input_file=None):
 
         if settings[DISPLAY_EXPERIMENT] is True:
             logging.info("The experiment with following parameters has been analysed:")
-            pp.pprint(sensitivity_experiment_s[experiment])
+            pp.pprint(sensitivity_experiment_s[experiment_id])
 
     # display all results
     output_names = [PROJECT_SITE_NAME, CASE]
diff --git a/src/constants.py b/src/constants.py
index f76cce09..432f68d0 100644
--- a/src/constants.py
+++ b/src/constants.py
@@ -43,11 +43,15 @@
 TARIFF = "tariff"
 TITLE_TIME = "title_time"
 TITLE_DEMAND_AC = "title_demand_ac"
+TITLE_DEMAND_AC_CRITICAL = "title_demand_ac_critical"
 TITLE_DEMAND_DC = "title_demand_dc"
+TITLE_DEMAND_DC_CRITICAL = "title_demand_dc_critical"
 TITLE_PV = "title_pv"
 TITLE_WIND = "title_wind"
 DEMAND_AC = "demand_ac"
+DEMAND_AC_CRITICAL = "demand_ac_critical"
 DEMAND_DC = "demand_dc"
+DEMAND_DC_CRITICAL = "demand_dc_critical"
 PV_GENERATION_PER_KWP = "pv_generation_per_kWp"
 WIND_GENERATION_PER_KW = "wind_generation_per_kW"
 GRID_AVAILABILITY = "grid_availability"
@@ -83,7 +87,9 @@
 BLACKOUT_FREQUENCY_STD_DEVIATION = "blackout_frequency_std_deviation"
 SENSITIVITY_ALL_COMBINATIONS = "sensitivity_all_combinations"
 DEMAND_AC_SCALING_FACTOR = "demand_ac_scaling_factor"
+DEMAND_AC_CRITICAL_SCALING_FACTOR = "demand_ac_critical_scaling_factor"
 DEMAND_DC_SCALING_FACTOR = "demand_dc_scaling_factor"
+DEMAND_DC_CRITICAL_SCALING_FACTOR = "demand_dc_critical_scaling_factor"
 STORAGE_SOC_INITIAL = "storage_soc_initial"
 TOTAL_NUMBER_OF_EXPERIMENTS = "total_number_of_experiments"
 PROJECT_SITE_NAME = "project_site_name"
@@ -262,19 +268,31 @@
 TIME_FREQUENCY = "time_frequency"
 FILE_INDEX = "file_index"
 DEMAND_PROFILE_AC = "demand_profile_ac"
+DEMAND_PROFILE_AC_CRITICAL = "demand_profile_ac_critical"
 DEMAND_PROFILE_DC = "demand_profile_dc"
+DEMAND_PROFILE_DC_CRITICAL = "demand_profile_dc_critical"
 ACCUMULATED_PROFILE_AC_SIDE = "accumulated_profile_ac_side"
+ACCUMULATED_PROFILE_AC_CRITICAL_SIDE = "accumulated_profile_ac_critical_side"
 ACCUMULATED_PROFILE_DC_SIDE = "accumulated_profile_dc_side"
+ACCUMULATED_PROFILE_DC_CRITICAL_SIDE = "accumulated_profile_dc_critical_side"
 TOTAL_DEMAND_AC = "total_demand_ac"
+TOTAL_DEMAND_AC_CRITICAL = "total_demand_ac_critical"
 PEAK_DEMAND_AC = "peak_demand_ac"
+PEAK_DEMAND_AC_CRITICAL = "peak_demand_ac_critical"
 TOTAL_DEMAND_DC = "total_demand_dc"
+TOTAL_DEMAND_DC_CRITICAL = "total_demand_dc_critical"
 PEAK_DEMAND_DC = "peak_demand_dc"
+PEAK_DEMAND_DC_CRITICAL = "peak_demand_dc_critical"
 PEAK_PV_GENERATION_PER_KWP = "peak_pv_generation_per_kWp"
 PEAK_WIND_GENERATION_PER_KW = "peak_wind_generation_per_kW"
 MEAN_DEMAND_AC = "mean_demand_ac"
+MEAN_DEMAND_AC_CRITICAL = "mean_demand_ac_critical"
 MEAN_DEMAND_DC = "mean_demand_dc"
+MEAN_DEMAND_DC_CRITICAL = "mean_demand_dc_critical"
 PEAK_MEAN_DEMAND_RATIO_AC = "peak/mean_demand_ratio_ac"
+PEAK_MEAN_DEMAND_RATIO_AC_CRITICAL = "peak/mean_demand_ratio_ac_critical"
 PEAK_MEAN_DEMAND_RATIO_DC = "peak/mean_demand_ratio_dc"
+PEAK_MEAN_DEMAND_RATIO_DC_CRITICAL = "peak/mean_demand_ratio_dc_critical"
 ABS_PEAK_DEMAND_AC_SIDE = "abs_peak_demand_ac_side"
 
 SUFFIX_COST_INVESTMENT = "_cost_investment"
@@ -312,6 +330,7 @@
 STABILITY_CONSTRAINT = "stability_constraint"
 RENEWABLE_CONSTRAINT = "renewable_constraint"
 RENEWABLE_SHARE_CONSTRAINT = "renewable_share_constraint"
+CRITICAL_CONSTRAINT = "critical_constraint"
 EVALUATION_PERSPECTIVE = EVALUATION_PERSPECTIVE
 FORCE_CHARGE_FROM_MAINGRID = "force_charge_from_maingrid"
 DISCHARGE_ONLY_WHEN_BLACKOUT = "discharge_only_when_blackout"
@@ -329,6 +348,7 @@
 SHARE_BACKUP = "share_backup"
 SHARE_USAGE = "share_usage"
 SHARE_HYBRID = "share_hybrid"
+CRITICAL = "critical"
 BUS_FUEL = "bus_fuel"
 
 PREFIX_RESULTS = "results_"
@@ -364,14 +384,22 @@
 STORAGE_POWER_COST_ANNUITY = "storage_power_cost_annuity"
 SINK_EXCESS = "sink_excess"
 DISTRIBUTION_GRID_EFFICIENCY = "distribution_grid_efficiency"
+NON_CRITICAL_REDUCABLE_SUFFIX = "_reducable"
 SINK_DEMAND_AC = "sink_demand_ac"
+SINK_DEMAND_AC_CRITICAL = "sink_demand_ac_critical"
+SINK_DEMAND_AC_REDUCABLE = SINK_DEMAND_AC + NON_CRITICAL_REDUCABLE_SUFFIX
 SINK_DEMAND_DC = "sink_demand_dc"
+SINK_DEMAND_DC_CRITICAL = "sink_demand_dc_critical"
+SINK_DEMAND_DC_REDUCABLE = SINK_DEMAND_DC + NON_CRITICAL_REDUCABLE_SUFFIX
 SINK_MAINGRID_FEEDIN = "sink_maingrid_feedin"
 SINK_MAINGRID_FEEDIN_SYMBOLIC = "source_maingrid_feedin_symbolic"
 
 # G2b
 STORAGE_CAPACITY_MIN = "storage_capacity_min"
 DEMAND = "Demand"
+DEMAND_CRITICAL = "Critical demand"
+DEMAND_NON_CRITICAL = "Non critical demand"
+DEMAND_NON_CRITICAL_REDUCABLE = "Non critical demand reducable"
 STORED_CAPACITY = "Stored capacity"
 GRID_AVAILABILITY = "Grid availability"
 DEMAND_SHORTAGE = "Demand shortage"
@@ -425,7 +453,9 @@
 FEEDIN_MAIN_GRID_UTILITY_SIDE_ANNUAL_KWH = "feedin_main_grid_utility_side_annual_kWh"
 TOTAL_PCOUPLING_THROUGHPUT_KWH = "total_pcoupling_throughput_kWh"
 DEMAND_AC = "Demand AC"
+DEMAND_AC_CRITICAL = "Demand AC critical"
 DEMAND_DC = "Demand DC"
+DEMAND_DC_CRITICAL = "Demand DC critical"
 
 # G3a
 WIND_COST_ANNUITY = "wind_cost_annuity"