diff --git a/city_model_structure/attributes/usage_zone.py b/city_model_structure/attributes/usage_zone.py
index 6bcb07e2..83cf98c6 100644
--- a/city_model_structure/attributes/usage_zone.py
+++ b/city_model_structure/attributes/usage_zone.py
@@ -20,8 +20,12 @@ class UsageZone:
     self._heating_setpoint = None
     self._heating_setback = None
     self._cooling_setpoint = None
+    self._occupancy_density = None
     self._hours_day = None
     self._days_year = None
+    self._dhw_average_volume_pers_day = None
+    self._dhw_preparation_temperature = None
+    self._electrical_app_average_consumption_sqm_year = None
     # todo: mechanical_air_change must come from library, talk to Rabeeh
     self._mechanical_air_change = ConfigurationHelper().min_air_change
     self._occupancy = None
@@ -207,7 +211,76 @@ class UsageZone:
   @heating_schedule.setter
   def heating_schedule(self, values):
     """
-    Get heating schedule
+    heating schedule
     :param values: dict{DtaFrame(int)}
     """
     self._heating_schedule = values
+
+  @property
+  def occupancy_density(self):
+    # todo: review units
+    """
+    Get occupancy density in persons per m2
+    :return: float
+    """
+    return self._occupancy_density
+
+  @occupancy_density.setter
+  def occupancy_density(self, values):
+    """
+    occupancy density in persons per m2
+    :param values: float
+    """
+    self._occupancy_density = values
+
+  @property
+  def dhw_average_volume_pers_day(self):
+    # todo: review units
+    """
+    Get average DHW consumption in liters per person per day
+    :return: float
+    """
+    return self._dhw_average_volume_pers_day
+
+  @dhw_average_volume_pers_day.setter
+  def dhw_average_volume_pers_day(self, values):
+    """
+    average DHW consumption in liters per person per day
+    :param values: float
+    """
+    self._dhw_average_volume_pers_day = values
+
+  @property
+  def dhw_preparation_temperature(self):
+    # todo: review units
+    """
+    Get preparation temperature of the DHW in degree Celsius
+    :return: float
+    """
+    return self._dhw_preparation_temperature
+
+  @dhw_preparation_temperature.setter
+  def dhw_preparation_temperature(self, values):
+    """
+    preparation temperature of the DHW in degree Celsius
+    :param values: float
+    """
+    self._dhw_preparation_temperature = values
+
+  @property
+  def electrical_app_average_consumption_sqm_year(self):
+    # todo: review units
+    """
+    Get average consumption of electrical appliances in Watts per m2 and year
+    :return: float
+    """
+    return self._electrical_app_average_consumption_sqm_year
+
+  @electrical_app_average_consumption_sqm_year.setter
+  def electrical_app_average_consumption_sqm_year(self, values):
+    """
+    average consumption of electrical appliances in Watts per m2 and year
+    :param values: float
+    """
+    self._electrical_app_average_consumption_sqm_year = values
+
diff --git a/factories/occupancy_feeders/demo_occupancy_parameters.py b/factories/occupancy_feeders/demo_occupancy_parameters.py
index 0cd3b602..e4a70969 100644
--- a/factories/occupancy_feeders/demo_occupancy_parameters.py
+++ b/factories/occupancy_feeders/demo_occupancy_parameters.py
@@ -20,7 +20,7 @@ class DemoOccupancyParameters:
       schedules = dict()
       occupancy = pd.read_excel(xls, sheet_name=OccupancyHelper.pluto_occupancy_function(building.function),
                                 skiprows=[0, 1, 2, 3], nrows=39, usecols="A:AA")
-      # todo: should we safe the data type? How?
+      # todo: should we save the data type? How?
       for index in range(0, 13):
         data = pd.DataFrame()
         columns_names = []
diff --git a/factories/usage_feeders/us_base_usage_parameters.py b/factories/usage_feeders/us_base_usage_parameters.py
index 31a960a7..4cf71d64 100644
--- a/factories/usage_feeders/us_base_usage_parameters.py
+++ b/factories/usage_feeders/us_base_usage_parameters.py
@@ -44,13 +44,26 @@ class UsBaseUsageParameters:
 
   @staticmethod
   def _parse_zone_usage_type(zone_usage_type, usage_zone):
+    usage_zone.occupancy_density = zone_usage_type['occupancy']['occupancyDensity']
     usage_zone.hours_day = zone_usage_type['occupancy']['usageHoursPerDay']
     usage_zone.days_year = zone_usage_type['occupancy']['usageDaysPerYear']
     usage_zone.cooling_setpoint = zone_usage_type['endUses']['space_cooling']['coolingSetPointTemperature']
     usage_zone.heating_setpoint = zone_usage_type['endUses']['space_heating']['heatingSetPointTemperature']
     usage_zone.heating_setback = zone_usage_type['endUses']['space_heating']['heatingSetBackTemperature']
+    # todo: schedules set points!!!
     if 'ventilation' in zone_usage_type['endUses'] and zone_usage_type['endUses']['ventilation'] is not None:
       usage_zone.mechanical_air_change = zone_usage_type['endUses']['ventilation']['mechanicalAirChangeRate']
+    usage_zone.dhw_average_volume_pers_day = \
+        zone_usage_type['endUses']['domestic_hot_water']['averageVolumePerPersAndDay']
+    usage_zone.dhw_preparation_temperature = \
+        zone_usage_type['endUses']['domestic_hot_water']['preparationTemperature']
+    # todo: are there more than one of these electrical values?
+    # todo: schedules!!
+    if 'all_electrical_appliances' in zone_usage_type['endUses']:
+        if 'averageConsumptionPerSqmAndYear' in zone_usage_type['endUses']['all_electrical_appliances']:
+          usage_zone.electrical_app_average_consumption_sqm_year = \
+            zone_usage_type['endUses']['all_electrical_appliances']['averageConsumptionPerSqmAndYear']
+
     int_gains = InternalGains()
     int_gains.latent_fraction = zone_usage_type['occupancy']['internGains']['latentFraction']
     int_gains.convective_fraction = zone_usage_type['occupancy']['internGains']['convectiveFraction']