Merge pull request #158 from nismod/p3_weather_final

updated for model runs and plotting

docs/documentation.md

@@ -556,6 +556,8 @@ To calculate regional daily hourly load heating profiles, hourly temperature dat
 - The station ID can be retreived [here](http://badc.nerc.ac.uk/cgi-bin/midas_stations/search_by_name.cgi.py?name=&minyear=&maxyear=)
 - Metadatda of raw data can be found [here](http://artefacts.ceda.ac.uk/badc_datadocs/ukmo-midas/WH_Table.html)
 
+Alternatively, daily minimum and maximum temperature data can be downloaded from the [ weather@home dataset](https://catalogue.ceda.ac.uk/uuid/0cea8d7aca57427fae92241348ae9b03).
+
 ### 4.5 Census data
 Employment statistics from the census (Office for National Statistics 2011)
 are used to disaggregate industry related energy demands for different end uses and sectors.

energy_demand/main.py

@@ -4,7 +4,7 @@
 ----
 Always execute from root folder and pass the path to the .ini file as argument:
 
-    Example:
+    Examples
     python energy_demand/energy_demand/main.py C:/Users/cenv0553/ed/energy_demand/local_run_config_file.ini test_run
     python energy_demand/energy_demand/main.py C:/Users/cenv0553/ed/energy_demand/local_run_config_file.ini h_max NF1 h_max
 """
@@ -94,8 +94,6 @@ def energy_demand_model(
 
     data = {}
     sim_yrs = [2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050]
-    sim_yrs = [2015, 2050]
-
 
     if len(sys.argv) > 3: #user defined arguments are provide
         print("Arguments taken from comand line")
@@ -122,14 +120,11 @@ def energy_demand_model(
         path_weather_data = "/soge-home/staff/cenv0553/_weather_realisation"
     else:
         path_weather_data = "C:/Users/cenv0553/ED/data/scenarios"
-        #path_weather_data = "//linux-filestore.ouce.ox.ac.uk/mistral/nismod/data/energy_demand/J-MARIUS_data/_weather_realisation"
-        #path_ = 'L:\_weather_realisation'
-        #path_weather_data = "/soge-home/staff/cenv0553/_weather_realisation"
 
     if name_config_path == 'h_max' or name_config_path == 'l_max' or name_config_path in ['test_run', 'h_max_0', 'h_max_10', 'h_max_0_only', 'h_max_10_only']:
-        local_scenario = 'pop-b_econ-c_fuel-c' #high
+        local_scenario = 'pop-b_econ-c_fuel-c'
     elif name_config_path == 'h_min' or name_config_path == 'l_min' or name_config_path in ['h_min_zero', 'h_min_5dm', 'h_min_10dm']:
-        local_scenario = 'pop-f_econ-c_fuel-c' #low
+        local_scenario = 'pop-f_econ-c_fuel-c'
 
     # --- Paths
     path_strategy_vars = os.path.join(config['DATA_PATHS']['path_strategy_vars'], name_config_path)

energy_demand/plotting/fig_3_plot_over_time.py

@@ -223,8 +223,8 @@ def scenario_over_time(
         #two_std_line_neg.plot.line(color=color, linestyle='--', linewidth=0.1, label='_nolegend_')
 
         # plot min and maximum values
-        plt.plot(sim_yrs_smoothed, min_values, color=color, linestyle='--', linewidth=0.1, label='_nolegend_')
-        plt.plot(sim_yrs_smoothed, max_values, color=color, linestyle='--', linewidth=0.1, label='_nolegend_')
+        plt.plot(sim_yrs_smoothed, min_values, color=color, linestyle='--', linewidth=0.3, label='_nolegend_')
+        plt.plot(sim_yrs_smoothed, max_values, color=color, linestyle='--', linewidth=0.3, label='_nolegend_')
 
         plt.fill_between(
             sim_yrs_smoothed,

energy_demand/result_processing/p3_weather_plots.py

@@ -271,7 +271,7 @@ def main(
         # Plot national sum over time per fueltype and scenario
         # ------------------------------
         try:
-            crit_smooth_line = False
+            crit_smooth_line = True
             seperate_legend = True
             print("... plotting national sum of fueltype over time ")
             fig_3_plot_over_time.fueltypes_over_time(

energy_demand/result_processing/p3_weather_results.py

@@ -33,7 +33,6 @@
 
 # Scenario definitions
 all_scenarios = ['h_max']#, 'h_min', 'l_max', 'l_min']
-all_scenarios = ['l_min']
 fueltypes = ['electricity', 'gas', 'hydrogen']
 folder_types = ['mean', 'pos_two_sigma', 'neg_two_sigma']
 simulation_yrs = range(2015, 2051, 5)