120V HPWH

bin/run_dwelling.py

@@ -23,8 +23,10 @@
     'time_zone': None,                            # option to specify daylight savings, in development
 
     # Input parameters - Sample building (uses HPXML file and time series schedule file)
-    'hpxml_file': os.path.join(default_input_path, 'Input Files', 'sample_resstock_properties.xml'),
-    'schedule_input_file': os.path.join(default_input_path, 'Input Files', 'sample_resstock_schedule.csv'),
+    #'hpxml_file': os.path.join(default_input_path, 'Input Files', 'sample_resstock_properties.xml'),
+    #'schedule_input_file': os.path.join(default_input_path, 'Input Files', 'sample_resstock_schedule.csv'),
+    'hpxml_file': 'C:/OCHRE-120V-hpwh/in.xml',
+    'schedule_input_file': 'C:/OCHRE-120V-hpwh/schedules.csv',
 
     # Input parameters - weather (note weather_path can be used when Weather Station is specified in HPXML file)
     # 'weather_path': weather_path,

ochre/Equipment/WaterHeater.py

@@ -413,8 +413,12 @@ class HeatPumpWaterHeater(ElectricResistanceWaterHeater):
     def __init__(self, hp_only_mode=False, water_nodes=12, **kwargs):
         super().__init__(water_nodes=water_nodes, **kwargs)
 
+        self.low_power_hpwh = kwargs.get('Low Power HPWH', False)
+
         # Control parameters
         self.hp_only_mode = hp_only_mode
+        if self.low_power_hpwh:
+            self.hp_only_mode = True
         self.er_only_mode = False  # True when ambient temp is very hot or cold, forces HP off
         hp_on_time = kwargs.get('HPWH Minimum On Time (min)', 10)
         hp_off_time = kwargs.get('HPWH Minimum Off Time (min)', 0)
@@ -424,25 +428,38 @@ def __init__(self, hp_only_mode=False, water_nodes=12, **kwargs):
         self.deadband_temp = kwargs.get('Deadband Temperature (C)', 8.17)  # different default than ERWH
 
         # Nominal COP based on simulation of the UEF test procedure at varying COPs
-        self.cop_nominal = kwargs['HPWH COP (-)']
-        self.hp_cop = self.cop_nominal
-        if self.cop_nominal < 2:
-            self.warn("Low Nominal COP:", self.cop_nominal)
-
-        # Heat pump capacity and power parameters - hardcoded for now
-        if 'HPWH Capacity (W)' in kwargs:
-            self.hp_capacity_nominal = kwargs['HPWH Capacity (W)']  # max heating capacity, in W
-        else:
-            hp_power_nominal = kwargs.get('HPWH Power (W)', 500)  # in W
+        if self.low_power_hpwh: #TODO: can read a lot of these directly when properly integrated into HPXML
+            self.cop_nominal = 4.2
+            self.hp_cop = self.cop_nominal
+            self.hp_capacity_nominal = 1499.4
+            hp_power_nominal =  self.hp_capacity_nominal / self.cop_nominal # in W
             self.hp_capacity_nominal = hp_power_nominal * self.hp_cop  # in W
-        self.hp_capacity = self.hp_capacity_nominal  # in W
+            self.hp_capacity = self.hp_capacity_nominal  # in W
+        else:
+            self.cop_nominal = kwargs['HPWH COP (-)']
+            self.hp_cop = self.cop_nominal
+            if self.cop_nominal < 2:
+                self.warn("Low Nominal COP:", self.cop_nominal)
+
+            # Heat pump capacity and power parameters - hardcoded for now
+            if 'HPWH Capacity (W)' in kwargs:
+                self.hp_capacity_nominal = kwargs['HPWH Capacity (W)']  # max heating capacity, in W
+            else:
+                hp_power_nominal = kwargs.get('HPWH Power (W)', 500)  # in W
+                self.hp_capacity_nominal = hp_power_nominal * self.hp_cop  # in W
+            self.hp_capacity = self.hp_capacity_nominal  # in W
         self.parasitic_power = kwargs.get('HPWH Parasitics (W)', 1)  # Standby power in W
         self.fan_power = kwargs.get('HPWH Fan Power (W)', 35)  # in W
 
         # Dynamic capacity coefficients
         # curve format: [1, t_in_wet, t_in_wet ** 2, t_lower, t_lower ** 2, t_lower * t_in_wet]
-        self.hp_capacity_coeff = np.array([0.563, 0.0437, 0.000039, 0.0055, -0.000148, -0.000145])
-        self.cop_coeff = np.array([1.1332, 0.063, -0.0000979, -0.00972, -0.0000214, -0.000686])
+        if self.low_power_hpwh:
+            self.hp_capacity_coeff = np.array([0.813, 0.0160, 0.000537, 0.0020319, -0.0000860, -0.0000686])
+            self.cop_coeff = np.array([1.1332, 0.063, -0.0000979, -0.00972, -0.0000214, -0.000686])
+
+        else:
+            self.hp_capacity_coeff = np.array([0.563, 0.0437, 0.000039, 0.0055, -0.000148, -0.000145])
+            self.cop_coeff = np.array([1.0132, .0436, 0.0000117, -0.01113, 0.00003688, -0.000498])
 
         # Sensible and latent heat parameters
         self.shr_nominal = kwargs.get('HPWH SHR (-)', 0.88)  # unitless
@@ -562,7 +579,13 @@ def run_thermostat_control(self, use_future_states=False):
     def update_internal_control(self):
         # operate as ERWH when ambient temperatures are out of bounds
         t_amb = self.current_schedule['Zone Temperature (C)']
-        if t_amb < 7.222 or t_amb > 43.333:
+        if self.low_power_hpwh:
+            t_low = 2.778
+            t_high = 62.778
+        else:
+            t_low = 7.222
+            t_high = 43.333
+        if t_amb < t_low or t_amb > t_high:
             self.er_only_mode = True
         else:
             self.er_only_mode = False

ochre/Models/Water.py

@@ -37,7 +37,8 @@ class StratifiedWaterModel(RCModel):
     """
     name = 'Water Tank'
     optional_inputs = [
-        'Water Heating (L/min)',
+        'Water Fixtures (L/min)',
+        'Showers (L/min)',
         'Clothes Washer (L/min)',
         'Dishwasher (L/min)',
         'Mains Temperature (C)',
@@ -73,6 +74,8 @@ def __init__(self, water_nodes=12, water_vol_fractions=None, **kwargs):
 
         # mixed temperature (i.e. target temperature) setpoint for fixtures - Sink/Shower/Bath (SSB)
         self.tempered_draw_temp = kwargs.get('Mixed Delivery Temperature (C)', convert(105, 'degF', 'degC'))
+        self.hot_draw_temp = kwargs.get('Tempering Valve Setpoint (C)', convert(125, 'degF', 'degC'))
+        self.setpoint_temp = kwargs.get('Setpoint Temperature (C)', convert(125, 'degF', 'degC'))
         # Removing target temperature for clothes washers
         # self.washer_draw_temp = kwargs.get('Clothes Washer Delivery Temperature (C)', convert(92.5, 'degF', 'degC'))
 
@@ -131,7 +134,8 @@ def update_water_draw(self):
         self.outlet_temp = self.states[self.t_1_idx]  # initial outlet temp, for estimating draw volume
 
         # Note: removing target draw temperature for clothes washers, not implemented in ResStock
-        draw_tempered = self.current_schedule.get('Water Heating (L/min)', 0)
+        draw_tempered = self.current_schedule.get('Water Fixtures (L/min)', 0)
+        draw_showers = self.current_schedule.get('Showers (L/min)', 0)
         draw_hot = (self.current_schedule.get('Clothes Washer (L/min)', 0)
                     + self.current_schedule.get('Dishwasher (L/min)', 0))
         # draw_cw = self.current_schedule.get('Clothes Washer (L/min)', 0)
@@ -148,7 +152,15 @@ def update_water_draw(self):
 
         # calculate total draw volume from tempered draw volume(s)
         # for tempered draw, assume outlet temperature == T1, slightly off if the water draw is very large
-        self.draw_total = draw_hot
+        if self.tempered_draw_temp < self.setpoint_temp:
+            if self.outlet_temp <= self.hot_draw_temp:
+                self.draw_total = draw_hot
+            else:
+                vol_ratio_hot = (self.hot_draw_temp - self.mains_temp) / (self.outlet_temp - self.mains_temp)
+                self.draw_total += draw_hot * vol_ratio_hot
+        else:
+            self.draw_total = draw_hot
+
         if draw_tempered:
             if self.outlet_temp <= self.tempered_draw_temp:
                 self.draw_total += draw_tempered
@@ -214,8 +226,10 @@ def update_water_draw(self):
         self.h_delivered = q_delivered / t_s
         heats_to_model += q_nodes / t_s
 
-        # calculate unmet loads, fixtures only, in W
-        self.h_unmet_load = max(draw_tempered / 60 * water_c * (self.tempered_draw_temp - self.outlet_temp), 0)  # in W
+        # calculate unmet loads, showers only, in W
+        self.h_unmet_load = max(
+            draw_showers / 60 * water_c * (self.tempered_draw_temp - self.outlet_temp), 0
+        )  # in W
 
         return heats_to_model
 

ochre/utils/hpxml.py

@@ -932,6 +932,7 @@ def parse_water_heater(water_heater, water, construction, solar_fraction=0):
     first_hour_rating = water_heater.get('FirstHourRating')
     recovery_efficiency = water_heater.get('RecoveryEfficiency')
     tank_jacket_r = water_heater.get('WaterHeaterInsulation', {}).get('Jacket', {}).get('JacketRValue', 0)
+    low_power_hpwh = False
 
     # calculate actual volume from rated volume
     if volume_gal is not None:
@@ -959,6 +960,9 @@ def parse_water_heater(water_heater, water, construction, solar_fraction=0):
     elif water_heater_type == 'heat pump water heater':
         assert is_electric
         eta_c = 1
+        if uniform_energy_factor == 4.9: #FIXME: temporary flag for designating 120V HPWHs in panels branch of ResStock
+            low_power_hpwh = True
+
         # HPWH UA calculation taken from ResStock:
         # https://github.com/NREL/resstock/blob/run/restructure-v3/resources/hpxml-measures/HPXMLtoOpenStudio/resources/waterheater.rb#L765
         if volume_gal <= 58.0:
@@ -1014,6 +1018,7 @@ def parse_water_heater(water_heater, water, construction, solar_fraction=0):
 
     else:
         raise OCHREException(f'Unknown water heater type: {water_heater_type}')
+
 
     # Increase insulation from tank jacket (reduces UA)
     if tank_jacket_r:
@@ -1031,18 +1036,26 @@ def parse_water_heater(water_heater, water, construction, solar_fraction=0):
     if eta_c > 1.0:
         raise OCHREException('A water heater heat source (either burner or element) efficiency of > 1 has been calculated.'
                         ' Double check water heater inputs.')
-
+
+    if low_power_hpwh:
+        t_set = convert(140, 'degF', 'degC')
+        t_temper = convert(125, 'degF', 'degC')
+    else:
+        t_set =  convert(water_heater.get('HotWaterTemperature', 125), 'degF', 'degC')
+        t_temper = t_set
     wh = {
         'Equipment Name': water_heater_type,
         'Fuel': water_heater['FuelType'].capitalize(),
         'Zone': parse_zone_name(water_heater['Location']),
-        'Setpoint Temperature (C)': convert(water_heater.get('HotWaterTemperature', 125), 'degF', 'degC'),
+        'Setpoint Temperature (C)': t_set,
+        'Temepring Valve Setpoint (C)': t_temper,
         # 'Heat Transfer Coefficient (W/m^2/K)': u,
         'UA (W/K)': convert(ua, 'Btu/hour/degR', 'W/K'),
         'Efficiency (-)': eta_c,
         'Energy Factor (-)': energy_factor,
         'Tank Volume (L)': volume,
         'Tank Height (m)': height,
+        'Low Power HPWH': low_power_hpwh,
     }
     if heating_capacity is not None:
         wh['Capacity (W)'] = convert(heating_capacity, 'Btu/hour', 'W')
@@ -1103,8 +1116,7 @@ def parse_water_heater(water_heater, water, construction, solar_fraction=0):
     distribution_gal_per_day = mw_gpd * fixture_multiplier
 
     # Combine fixture and distribution water draws in schedule
-    wh['Fixture Average Water Draw (L/day)'] = convert(fixture_gal_per_day + distribution_gal_per_day, 'gallon/day',
-                                                       'L/day')
+    wh['Average Water Draw (L/day)'] = convert(fixture_gal_per_day + distribution_gal_per_day, 'gallon/day', 'L/day')
 
     return wh
 

ochre/utils/schedule.py

@@ -47,7 +47,8 @@
         # 'basement_mels': 'Basement MELs',  # not modeled
     },
     "Water": {
-        "hot_water_fixtures": "Water Heating",
+        "hot_water_fixtures": "Water Fixtures",
+        # "hot_water_showers": "Showers",  # for unmet loads only
         "hot_water_clothes_washer": "Clothes Washer",
         "hot_water_dishwasher": "Dishwasher",
     },
@@ -284,59 +285,67 @@ def create_simple_schedule(weekday_fractions, weekend_fractions=None, month_mult
     return df['w_fracs'] * df['m_fracs']
 
 
-def convert_schedule_column(s_hpxml, ochre_name, properties, category='Power'):
-    if category == 'Power':
-        # try getting from max power or from annual energy, priority goes to max power
-        if 'Max Electric Power (W)' in properties:
-            max_value = properties['Max Electric Power (W)'] / 1000  # W to kW
-        elif 'Annual Electric Energy (kWh)' in properties:
-            annual_mean = properties['Annual Electric Energy (kWh)'] / 8760
-            schedule_mean = s_hpxml.mean()
-            max_value = annual_mean / schedule_mean if schedule_mean != 0 else 0
-        else:
-            max_value = None
-        if max_value is not None:
-            out = s_hpxml * max_value
-            out.name = f'{ochre_name} (kW)'
-        else:
-            out = None
-
-        # check for gas (max power and annual energy), and copy schedule
-        if 'Max Gas Power (therms/hour)' in properties:
-            max_value = properties['Max Gas Power (therms/hour)']  # in therms/hour
-        elif 'Annual Gas Energy (therms)' in properties:
-            annual_mean = properties['Annual Gas Energy (therms)'] / 8760  # in therms/hour
-            schedule_mean = s_hpxml.mean()
-            max_value = annual_mean / schedule_mean if schedule_mean != 0 else 0
-        else:
-            max_value = None
-        if max_value is None:
-            pass
-        elif out is None:
-            out = s_hpxml * max_value
-            out.name = f'{ochre_name} (therms/hour)'
-        else:
-            # combine 2 series into data frame
-            s_gas = s_hpxml * max_value
-            s_gas.name = f'{ochre_name} (therms/hour)'
-            out = pd.concat([out, s_gas], axis=1)
-
-        if out is None:
-            raise OCHREException(f'Could not determine max value for {s_hpxml.name} schedule ({ochre_name}).')
-
-    elif category == 'Water':
-        if ochre_name == 'Water Heating':
-            # Fixtures include sinks, showers, and baths (SSB), all combined
-            avg_water_draw = properties.get('Fixture Average Water Draw (L/day)', 0)
-            annual_mean = avg_water_draw / 1440  # in L/min
-        else:
-            # For dishwasher and clothes washer, get average draw value from their properties dict
-            annual_mean = properties['Average Water Draw (L/day)'] / 1440  # in L/min
-            schedule_mean = s_hpxml.mean()
+def convert_power_column(s_hpxml, ochre_name, properties):
+    # try getting from max power or from annual energy, priority goes to max power
+    if 'Max Electric Power (W)' in properties:
+        max_value = properties['Max Electric Power (W)'] / 1000  # W to kW
+    elif 'Annual Electric Energy (kWh)' in properties:
+        annual_mean = properties['Annual Electric Energy (kWh)'] / 8760
         schedule_mean = s_hpxml.mean()
         max_value = annual_mean / schedule_mean if schedule_mean != 0 else 0
+    else:
+        max_value = None
+    if max_value is not None:
         out = s_hpxml * max_value
-        out.name = f'{ochre_name} (L/min)'
+        out.name = f'{ochre_name} (kW)'
+    else:
+        out = None
+
+    # check for gas (max power and annual energy), and copy schedule
+    if 'Max Gas Power (therms/hour)' in properties:
+        max_value = properties['Max Gas Power (therms/hour)']  # in therms/hour
+    elif 'Annual Gas Energy (therms)' in properties:
+        annual_mean = properties['Annual Gas Energy (therms)'] / 8760  # in therms/hour
+        schedule_mean = s_hpxml.mean()
+        max_value = annual_mean / schedule_mean if schedule_mean != 0 else 0
+    else:
+        max_value = None
+    if max_value is None:
+        pass
+    elif out is None:
+        out = s_hpxml * max_value
+        out.name = f'{ochre_name} (therms/hour)'
+    else:
+        # combine 2 series into data frame
+        s_gas = s_hpxml * max_value
+        s_gas.name = f'{ochre_name} (therms/hour)'
+        out = pd.concat([out, s_gas], axis=1)
+
+    if out is None:
+        raise OCHREException(f'Could not determine max value for {s_hpxml.name} schedule ({ochre_name}).')
+
+    return out
+
+
+def convert_water_column(s_hpxml, ochre_name, equipment):
+    if ochre_name in ["Water Fixtures", "Showers"]:
+        # Fixtures include sinks, showers, and baths (SSB), all combined
+        # Showers are only included for unmet loads calculation
+        equipment_name = "Water Heating"
+    else:
+        equipment_name = ochre_name
+
+    if equipment_name not in equipment:
+        return None
+
+    properties = equipment[equipment_name]
+    avg_water_draw = properties.get('Average Water Draw (L/day)', 0)
+    annual_mean = avg_water_draw / 1440  # in L/min
+
+    schedule_mean = s_hpxml.mean()
+    max_value = annual_mean / schedule_mean if schedule_mean != 0 else 0
+    out = s_hpxml * max_value
+    out.name = f'{ochre_name} (L/min)'
 
     return out
 
@@ -408,11 +417,13 @@ def import_occupancy_schedule(occupancy, equipment, start_time, schedule_input_f
             s_ochre = s_hpxml * occupancy['Number of Occupants (-)']
             s_ochre.name = f'{ochre_name} (Persons)'
             schedule_data.append(s_ochre)
-        elif category in ['Power', 'Water']:
-            if ochre_name not in equipment:
-                continue
-            else:
-                schedule_data.append(convert_schedule_column(s_hpxml, ochre_name, equipment[ochre_name], category))
+        elif category == "Power":
+            if ochre_name in equipment:
+                schedule_data.append(convert_power_column(s_hpxml, ochre_name, equipment[ochre_name]))
+        elif category == "Water":
+            s_ochre = convert_water_column(s_hpxml, ochre_name, equipment)
+            if s_ochre is not None:
+                schedule_data.append(s_ochre)
         elif category == 'Setpoint':
             # Already in the correct units
             s_ochre = s_hpxml