Merge pull request #145 from nismod/update/cluster

Update/cluster

energy_demand/assumptions/fuel_shares.py

@@ -155,7 +155,6 @@ def assign_by_fuel_tech_p(
     fuel_tech_p_by['rs_space_heating'][fueltypes['gas']] = {
         'boiler_condensing_gas': 0.60,
         'boiler_gas': 0.37,
-        'stirling_micro_CHP_gas': 0.0,
         'district_heating_CHP_gas': 0.03}
 
     fuel_tech_p_by['rs_space_heating'][fueltypes['electricity']] = {
@@ -179,7 +178,6 @@ def assign_by_fuel_tech_p(
     fuel_tech_p_by['rs_water_heating'][fueltypes['gas']] = {
         'boiler_condensing_gas': 0.60,
         'boiler_gas': 0.37,
-        'stirling_micro_CHP_gas': 0.0,
         'district_heating_CHP_gas': 0.03}
 
     fuel_tech_p_by['rs_water_heating'][fueltypes['electricity']] = {
@@ -246,7 +244,6 @@ def assign_by_fuel_tech_p(
     fuel_tech_p_by['ss_water_heating'][fueltypes['gas']] = {
         'boiler_condensing_gas': 0.60,
         'boiler_gas': 0.37,
-        'stirling_micro_CHP_gas': 0.0,
         'district_heating_CHP_gas': 0.03}
 
     fuel_tech_p_by['ss_water_heating'][fueltypes['electricity']] = {

energy_demand/basic/date_prop.py

@@ -8,11 +8,25 @@
 
 from energy_demand.basic import basic_functions
 
+def convert_yearday_to_8760h_selection(yearday):
+    """Select from 8760 hours the 24 hours of yearday
+
+    Arguments
+    ---------
+    yearday : int
+        Range between 0 and 364
+    """
+    hour_start = yearday * 24
+    hour_end = (yearday + 1) * 24
+
+    hours = range(hour_start, hour_end, 1)
+    return hours
+
 def convert_h_to_day_year_and_h(hour):
     """Convert a 8760 hour in a year
     to the yearday and hour of that day
 
-    Input
+    Arguments
     -----
     hour : int
         Hour of 8760 hours in a year

energy_demand/basic/demand_supply_interaction.py

@@ -84,7 +84,6 @@ def constrained_results(
             fueltype_int = technologies[tech].fueltype_int
 
             key_name = "{}_{}_{}".format(submodel, fueltype_str, tech_simplified)
-
             supply_results[key_name] = fuel_tech[submodel_nr][:, fueltype_int, :]
 
     # ---------------------------------
@@ -97,7 +96,7 @@ def constrained_results(
                 pass #Do not add non_heating demand for fueltype heat
             else:
                 key_name = "{}_{}_{}".format(submodel, fueltype_str, "non_heating")
-
+                logging.info("key_name d: " + str(key_name))
                 # Add fuel for all regions for specific fueltype
                 supply_results[key_name] = non_heating_ed[submodel_nr][:, fueltype_int, :]
 

energy_demand/main.py

@@ -1,5 +1,7 @@
 """Allows to run HIRE locally outside the SMIF framework
 
+write_national_results_amman
+
 Note
 ----
 Always execute from root folder. (e.g. energy_demand/energy_demand/main.py
@@ -78,18 +80,17 @@ def energy_demand_model(
 if __name__ == "__main__":
     """
     """
-
     # ------------------------------------------
     # Local run model configuration
     # ------------------------------------------
-
-    # Paths
     local_data_path = os.path.abspath('data')
     path_main = os.path.abspath(
         os.path.join(
             os.path.dirname(__file__), '..', "energy_demand/config_data"))
     path_config = os.path.abspath(os.path.join(
             os.path.dirname(__file__), '..', 'local_run_config_file.ini'))
+            #os.path.dirname(__file__), '..', 'local_run_config_file_cluster.ini'))
+
     print("Configuration path: " + str(path_config))
 
     # Get configuration
@@ -105,51 +106,49 @@ def energy_demand_model(
 
     # Simulated yrs
     sim_yrs = [base_yr, user_defined_simulation_end_yr]
+    weather_yr_scenario = 2015   # Default weather year
 
     if len(sys.argv) > 1: #user defined arguments are provide
-
         scenario_name = str(sys.argv[1])
-        weather_yr_scenario = int(sys.argv[2])        # Weather year
-        try:
-            weather_station_count_nr = int(sys.argv[3])       # Weather station cnt
-        except:
-            weather_station_count_nr = []
+        weather_realisation = str(sys.argv[2]) # Weather realisation 
     else:
         scenario_name = "_run_"
-        weather_yr_scenario = 2015                      # Default weather year
-        weather_station_count_nr = []                   # Default weather year
+        weather_realisation = 'NF1'
 
     print("Information")
     print("-------------------------------------")
     print("weather_yr_scenario:        " + str(weather_yr_scenario))
-    print("weather_station_count_nr:    " + str(weather_station_count_nr))
+    print("weather_realisation:        " + str(weather_realisation))
+
+    path_weather_data = "X:/nismod/data/energy_demand/J-MARIUS_data/_weather_realisation"
+    #path_weather_data = "/soge-home/staff/cenv0553/_weather_realisation"
+
+    path_strategy_vars = os.path.join(local_data_path, 'energy_demand', '00_user_defined_variables')
 
     # --- Region definition configuration
     name_region_set = os.path.join(local_data_path, 'energy_demand', 'region_definitions', "lad_2016_uk_simplified.shp")
 
     local_scenario = 'pop-a_econ-c_fuel-c'
-    weather_realisation = 'NF1'
 
     name_population_dataset = os.path.join(local_data_path, 'scenarios', 'MISTRAL_pop_gva', 'data', '{}/population__lad.csv'.format(local_scenario))
     name_gva_dataset = os.path.join(local_data_path, 'scenarios', 'MISTRAL_pop_gva', 'data', '{}/gva_per_head__lad_sector.csv'.format(local_scenario))
     name_gva_dataset_per_head = os.path.join(local_data_path, 'scenarios', 'MISTRAL_pop_gva', 'data', '{}/gva_per_head__lad.csv'.format(local_scenario))
 
-    path_weather_data = "X:/nismod/data/energy_demand/J-MARIUS_data/_weather_realisation"
-
-    simulation_name = str(weather_realisation) + "__" + "all_stations"
+    #simulation_name = str(weather_realisation) + "__" + "all_stations"
+    simulation_name = "simulation_results"
 
     name_scenario_run = "{}_result_local_{}".format(scenario_name, str(time.ctime()).replace(":", "_").replace(" ", "_"))
-
     # ------------------------------------------
 
     # --------------------
     # Load all other paths
     # --------------------
     data['paths'] = data_loader.load_paths(path_main)
     data['local_paths'] = data_loader.get_local_paths(local_data_path)
-    #print("data['local_paths']")
-    #print(data['local_paths']['data_processed'])
-    #raise Exception("T")
+
+    # Manually overwrriting startegy variable path
+    data['local_paths']['path_strategy_vars'] = path_strategy_vars
+
     data['path_new_scenario'] = os.path.abspath(os.path.join(os.path.dirname(local_data_path), "results", name_scenario_run))
     data['result_paths'] = data_loader.get_result_paths(data['path_new_scenario'])
 
@@ -166,7 +165,7 @@ def energy_demand_model(
 
     reg_centroids = read_data.get_region_centroids(name_region_set)
     data['reg_coord'] = basic_functions.get_long_lat_decimal_degrees(reg_centroids)
-    print("AA " + str(name_population_dataset))
+
     data['scenario_data']['population'] = data_loader.read_scenario_data(name_population_dataset)
 
     # Read GVA sector specific data
@@ -524,8 +523,22 @@ def energy_demand_model(
             path_runs = data['result_paths']['data_results_model_runs']
 
             print("... Start writing results to file: " + str(path_runs))
-            plot_only_selection = False
+            plot_only_selection = True
             if plot_only_selection:
+                write_data.write_only_peak_total_regional(
+                    sim_yr,
+                    "only_total",
+                    path_runs,
+                    sim_obj.ed_fueltype_regs_yh,
+                    'tot_fueltype_reg')
+
+                write_data.write_only_peak(
+                    sim_yr,
+                    "only_peak",
+                    path_runs,
+                    sim_obj.ed_fueltype_regs_yh,
+                    'fueltype_reg_peak_day')
+
                 # PLot only residential total regional annual demand and
                 write_data.write_residential_tot_demands(
                     sim_yr,

energy_demand/model.py

@@ -966,47 +966,47 @@ def aggregate_from_full_results(
     """
     for enduse_array_yr, reg_fueltype_8760h in enumerate(full_sim_data):
 
-            # Test if reshaping and annual or hourly
-            if time_resolution == 'annual':
-                demand = np.sum(reg_fueltype_8760h, axis=2) # Sum all hours
-            elif time_resolution == '8760_h':
-                demand = reg_fueltype_8760h
-            elif time_resolution == '365_24':
-                demand = reg_fueltype_8760h.reshape(
-                    reg_fueltype_8760h.shape[0],
-                    reg_fueltype_8760h.shape[1],
-                    365, 24)
+        # Test if reshaping and annual or hourly
+        if time_resolution == 'annual':
+            demand = np.sum(reg_fueltype_8760h, axis=2) # Sum all hours
+        elif time_resolution == '8760_h':
+            demand = reg_fueltype_8760h
+        elif time_resolution == '365_24':
+            demand = reg_fueltype_8760h.reshape(
+                reg_fueltype_8760h.shape[0],
+                reg_fueltype_8760h.shape[1],
+                365, 24)
+        else:
+            raise Exception("Provide either 'annual' or 'hourly' or '365_24'")
+
+        # Aggregate according to criteria
+        if per_sector:
+            if per_region:
+                if per_enduse:
+                    pass
+                else:
+                    pass
             else:
-                raise Exception("Provide either 'annual' or 'hourly' or '365_24'")
-
-            # Aggregate according to criteria
-            if per_sector:
-                if per_region:
-                    if per_enduse:
-                        pass
-                    else:
-                        pass
+                if per_enduse:
+                    pass
                 else:
-                    if per_enduse:
-                        pass
-                    else:
-                        pass
+                    pass
+        else:
+            if per_region:
+                if per_enduse:
+                    aggregated_container[enduse_array_yr] += demand
+                else:
+                    aggregated_container += demand
             else:
-                if per_region:
-                    if per_enduse:
-                        aggregated_container[enduse_array_yr] += demand
-                    else:
-                        aggregated_container += demand
+                # Sum across all regions
+                demand = np.sum(demand, axis=1)
+
+                # Get enduse str
+                enduse_str = get_enduse_from_array_nr(enduse_array_yr, lookup_enduse)
+
+                if per_enduse:
+                    aggregated_container[enduse_str] += demand
                 else:
-                    # Sum across all regions
-                    demand = np.sum(demand, axis=1)
-
-                    # Get enduse str
-                    enduse_str = get_enduse_from_array_nr(enduse_array_yr, lookup_enduse)
-
-                    if per_enduse:
-                        aggregated_container[enduse_str] += demand
-                    else:
-                        aggregated_container += demand
+                    aggregated_container += demand
 
     return aggregated_container