working on fixing base year bug shares

energy_demand/dwelling_stock/dw_stock.py

@@ -751,10 +751,10 @@ def generate_dw_existing(
         dwtype_floorarea = floorarea_p[dwtype_name] * floorarea_by
 
         # Distribute according to age
-        for dwtype_age in dwtype_age_distr_by.keys():
+        for dwtype_age, distribution in dwtype_age_distr_by.items():
 
             # Floor area of dwelling_class_age (distribute proportionally floor area)
-            dwtype_age_class_floorarea = dwtype_floorarea * dwtype_age_distr_by[dwtype_age]
+            dwtype_age_class_floorarea = dwtype_floorarea * distribution
 
             # Floor area per person is divided by base area value to calc pop
             if floorarea_pp != 0:

energy_demand/enduse_func.py

@@ -126,8 +126,8 @@ def __init__(
             #print("------INFO  {} {} {}  {}".format(self.enduse, sector, region, curr_yr))
             #print("FUEL TRAIN A0: " + str(np.sum(self.fuel_y)))
 
-            if curr_yr > 2015:
-                print("tt")
+            #if curr_yr > 2015 and enduse == 'rs_space_heating':
+            #    print("tt")
             # Get technologies of enduse
             self.enduse_techs = get_enduse_techs(fuel_tech_p_by)
 
@@ -247,7 +247,7 @@ def __init__(
                 # ------------------------------------
                 # Calculate regional energy service
                 # ------------------------------------
-                print("A " + str(np.sum(self.fuel_y)))
+                #print("A " + str(np.sum(self.fuel_y)))
                 s_tot_y_cy, s_tech_y_by = fuel_to_service(
                     enduse,
                     sector,
@@ -256,7 +256,8 @@ def __init__(
                     tech_stock,
                     fueltypes,
                     mode_constrained)
-                print(np.sum(s_tot_y_cy))
+                #print(np.sum(s_tot_y_cy))
+                #print(np.sum(list(s_tech_y_by.values()))) #NEW
                 # ------------------------------------
                 # Reduction of service because of heat recovery
                 # ------------------------------------
@@ -266,7 +267,8 @@ def __init__(
                     s_tot_y_cy,
                     s_tech_y_by,
                     curr_yr)
-                print(np.sum(s_tot_y_cy))
+                #print(np.sum(s_tot_y_cy))
+                #print(np.sum(list(s_tech_y_cy.values()))) #NEW
                 # ------------------------------------
                 # Reduction of service because of improvement in air leakeage
                 # ------------------------------------
@@ -276,7 +278,8 @@ def __init__(
                     s_tot_y_cy,
                     s_tech_y_cy,
                     curr_yr)
-                print(np.sum(s_tot_y_cy))
+                #print(np.sum(s_tot_y_cy))
+                #print(np.sum(list(s_tech_y_cy.values()))) #NEW
                 # --------------------------------
                 # Switches
                 # --------------------------------
@@ -287,14 +290,15 @@ def __init__(
                     curr_yr=curr_yr,
                     base_yr=base_yr,
                     sector=sector,
-                    annual_tech_diff_params=strategy_vars['annual_tech_diff_params'],
+                    annual_tech_diff_params=strategy_vars['annual_tech_diff_params'][enduse][sector],
                     crit_switch_happening=assumptions.crit_switch_happening)
-                print(np.sum(s_tot_y_cy))
+                #print(np.sum(s_tot_y_cy))
+                #print(np.sum(list(s_tech_y_cy.values()))) #NEW
                 # -------------------------------------------
                 # Convert annual service to fuel per fueltype
                 # -------------------------------------------
-                print("--")
-                print(np.sum(self.fuel_y))
+                #print("--")
+                #print(np.sum(self.fuel_y))
                 self.fuel_y, fuel_tech_y = service_to_fuel(
                     enduse,
                     sector,
@@ -303,7 +307,7 @@ def __init__(
                     fueltypes_nr,
                     fueltypes,
                     mode_constrained)
-                print("B" + str(np.sum(self.fuel_y)))
+                #print("B" + str(np.sum(self.fuel_y)))
                 # Delete all technologies with no fuel assigned
                 for tech, fuel_tech in fuel_tech_y.items():
                     if np.sum(fuel_tech) == 0:
@@ -834,10 +838,9 @@ def service_to_fuel(
             fuel_tech_y[tech] = fuel_tech
 
             fuel_y[fueltype_int] += fuel_tech
-            #logging.debug("S --> F: tech: {} eff: {} fuel: {} fuel {}".format(tech, tech_eff, fuel_y[fueltype_int], fuel_tech))
+            #print("S --> F: tech: {} eff: {} fuel: {} service {}".format(tech, tech_eff, fuel_y[fueltype_int], service))
     else:
         for tech, fuel_tech in service_tech.items():
-
             fuel_y[fueltypes['heat']] += fuel_tech
             fuel_tech_y[tech] = fuel_tech
 
@@ -907,10 +910,10 @@ def fuel_to_service(
             techs_with_fuel = tech_list
 
         for tech, fuel_share in techs_with_fuel.items():
-
+
+            #Constrained version
             if mode_constrained:
-                """Constrained version
-                """
+
                 tech_eff = tech_stock.get_tech_attr(enduse, sector, tech, 'eff_by')
 
                 # Get fuel share and convert fuel to service per technology
@@ -921,12 +924,10 @@ def fuel_to_service(
                 # Sum total yearly service
                 s_tot_y += s_tech #(y)
 
-                ##logging.debug("F --> S: tech: {} eff: {} fuel: {} service {}".format(tech, tech_eff, fuel_y[fueltype_int], s_tech))
+                #print("F --> S: tech: {} eff: {} fuel: {} service {}".format(tech, tech_eff, fuel_y[fueltype_int], s_tech))
             else:
-                """Unconstrained version
-                efficiencies are not considered, because not technology
-                specific service calculation
-                """
+                #Unconstrained version (efficiencies are not considered, because not technology specific service calculation)
+
                 # Calculate fuel share
                 fuel_tech = fuel_y[fueltype_int] * fuel_share
 
@@ -1470,18 +1471,24 @@ def apply_service_switch(
         base_yr,
         curr_yr)
 
+    # TESTING
+    #_sum = 0
+    #for tech in annual_tech_diff_params:
+    #    _sum += annual_tech_diff_params[tech][curr_yr]
+    #
+    #print("TOTAL SUM " + str(_sum))
     # ---------------------------------------
     # Calculate switch
     # ----------------------------------------
     if crit_switch_service:
-        switched_s_tech_y_cy = {}
 
         # Service of all technologies
         service_all_techs = sum(s_tech_y_cy.values())
-
+
+        switched_s_tech_y_cy = {}
         for tech in all_technologies:
             # Get service share per tech of cy of sigmoid parameter calculations
-            p_s_tech_cy = annual_tech_diff_params[enduse][sector][tech][curr_yr]
+            p_s_tech_cy = annual_tech_diff_params[tech][curr_yr]
             switched_s_tech_y_cy[tech] = service_all_techs * p_s_tech_cy
         return switched_s_tech_y_cy
     else:

energy_demand/geography/weather_region.py

@@ -676,7 +676,7 @@ def get_weather_station_selection(
         station_id = all_stations_of_weather_yr[counter]
 
         all_weather_stations_out = {station_id: all_weather_stations[weather_yr][station_id]}
-    except:
+    except KeyError:
         # Not enough stations to select position in list
         station_id = False
         all_weather_stations_out = []

energy_demand/main.py

@@ -109,7 +109,8 @@ def energy_demand_model(
     # Simulated yrs
     #sim_yrs = [base_yr, 2030, user_defined_simulation_end_yr]
     #sim_yrs = [2015, 2020, 2025, 2030, 2035, 2040, 2045, 2050]
-    sim_yrs = [2015, 2020, 2050]
+    #sim_yrs = [2015, 2020, 2050]
+    sim_yrs = [2015, 2050]
     weather_yr_scenario = 2015   # Default weather year
 
     if len(sys.argv) > 3: #user defined arguments are provide

energy_demand/plotting/fig_3_plot_over_time.py

@@ -47,7 +47,8 @@ def scenario_over_time(
         scenario_result_container,
         sim_yrs,
         fig_name,
-        result_path
+        result_path,
+        plot_points
     ):
     """Plot peak over time
     """
@@ -80,6 +81,18 @@ def scenario_over_time(
         df_q_05 = national_peak.quantile(quantile_05)
         df_q_95 = national_peak.quantile(quantile_95)
 
+        # ------------------------
+        # Plot calculated data points
+        # ------------------------
+        if plot_points:
+
+            plt.scatter(
+                sim_yrs,
+                mean_national_peak,
+                c=color,
+                s=10,
+                clip_on=False) #do not clip points on axis
+
         # --------------------
         # Try to smooth lines
         # --------------------
@@ -177,6 +190,7 @@ def fueltypes_over_time(
         fig_name,
         fueltypes,
         result_path,
+        plot_points=False,
         unit='TWh'
     ):
     """Plot fueltypes over time
@@ -238,6 +252,18 @@ def fueltypes_over_time(
             df_q_05 = national_sum.quantile(quantile_05)
             df_q_95 = national_sum.quantile(quantile_95)
 
+            # ------------------------
+            # Plot calculated data points
+            # ------------------------
+            if plot_points:
+
+                plt.scatter(
+                    sim_yrs,
+                    mean_national_sum,
+                    c=color,
+                    s=10,
+                    clip_on=False) #do not clip points on axis
+
             # --------------------
             # Try to smooth lines
             # --------------------
@@ -325,7 +351,7 @@ def fueltypes_over_time(
     legend = plt.legend(
         #title="tt",
         ncol=2,
-        prop={'size': 3},
+        prop={'size': 6},
         loc='upper center',
         bbox_to_anchor=(0.5, -0.1),
         frameon=False)

energy_demand/result_processing/weather_result_charts.py

@@ -198,7 +198,8 @@ def main(
         fig_name="fueltypes_over_time_{}.pdf".format(fueltype_str),
         fueltypes=['electricity', 'gas', 'hydrogen'],
         result_path=result_path,
-        unit='TWh')
+        unit='TWh',
+        plot_points=True)
     #raise Exception("TT")
     # ------------------------------
     # Plot national peak change over time for each scenario
@@ -208,6 +209,7 @@ def main(
         scenario_result_container=scenario_result_container,
         sim_yrs=data['assumptions']['sim_yrs'],
         fig_name="scenarios_peak_over_time_{}.pdf".format(fueltype_str),
+        plot_points=True,
         result_path=result_path)
     raise Exception("TT3")
 

energy_demand/scripts/init_scripts.py

@@ -33,7 +33,7 @@ def get_all_narrative_timesteps(switches_list):
         switches_list)
 
     for enduse in enduses:
-        narrative_timesteps[enduse] = set([])
+        narrative_timesteps[enduse] = set()
 
         for switch in switches_list:
             if switch.enduse == enduse:
@@ -239,9 +239,13 @@ def switch_calculations(
     for submodel in data['assumptions'].submodels_names:
         for enduse in data['enduses'][submodel]:
             for sector in data['sectors'][submodel]:
+
+
+                #NEW Add base year to timesteps
+                #timsteps_plus_by = [2015] + narrative_timesteps[enduse]
 
                 diffusion_param_tech[enduse][sector] = sig_param_calc_incl_fuel_switch(
-                    narrative_timesteps,
+                    narrative_timesteps, #timsteps_plus_by, 
                     data['assumptions'].base_yr,
                     data['assumptions'].crit_switch_happening,
                     data['assumptions'].technologies,
@@ -261,7 +265,26 @@ def switch_calculations(
     annual_tech_diff_params = s_scenario_param.calc_annual_switch_params(
         sim_yrs,
         data['regions'],
-        dict(diffusion_param_tech))
+        dict(diffusion_param_tech),
+        base_yr=data['assumptions'].base_yr, #NEW
+        s_tech_by_p=s_tech_by_p) #NEW
+
+    # Test whether the calculated service shares sum up to 1
+    for region in annual_tech_diff_params:
+        for enduse in annual_tech_diff_params[region]:
+            for sector in annual_tech_diff_params[region][enduse]:
+                print("TTTTTTTT {} {} {}  ".format(region, enduse, sector))
+                print(annual_tech_diff_params[region][enduse][sector])
+
+                for year in sim_yrs:
+                    if annual_tech_diff_params[region][enduse][sector] != []:
+                        _sum = 0
+                        for tech in annual_tech_diff_params[region][enduse][sector]:
+                            print("TECH " + str(tech))
+                            print("TECH " + str(annual_tech_diff_params[region][enduse][sector][tech]))
+                            _sum += annual_tech_diff_params[region][enduse][sector][tech][year]
+                        print(_sum)
+                        assert round(_sum, 2) == 1
 
     return annual_tech_diff_params
 
@@ -741,7 +764,7 @@ def sig_param_calc_incl_fuel_switch(
                 # -----------------------------------------------
                 #logging.debug("---------- switches %s %s %s", enduse, crit_switch_service, crit_fuel_switch)
                 if crit_all_the_same:
-                    logging.info("... calc parameters of `{}` for year `{}`  {}".format(enduse, switch_yr, sector))
+                    print("... calc parameters of `{}` for year `{}`  {}".format(enduse, switch_yr, sector))
                     # Calculate for one region
                     sig_param_tech_all_regs_value = s_generate_sigmoid.tech_sigmoid_parameters(
                         switch_yr,

energy_demand/scripts/s_disaggregation.py

@@ -59,7 +59,7 @@ def disaggr_demand(data, crit_temp_min_max, spatial_calibration=False):
         can be calibrated for gas and electricity based on actual
         measured demand data
 
-        Note: All other fueltypes are not skaled
+        Note: All other fueltypes are not scaled
         '''
         calibrate_residential = False # Calibrate residential demands
         calibrate_non_residential = True # Calibrate non residential demands