UrbanHeatPro.Classes.SpaceHeatingDemand

SpaceHeatingDemand.py A. Molar-Cruz @ TUM ENS

Module Contents

Classes

SpaceHeatingDemand

Initializes an instance of the SpaceHeatingDemand class.

class UrbanHeatPro.Classes.SpaceHeatingDemand.SpaceHeatingDemand(dt_vector, resolution, heated_area, Tamb, I, Tb0, dT_per_hour, eta, thermal_intertia, U, V, C, Tset, dTset, activity_vector, occupancy_vector, sh_prob, _solar_gains, _internal_gains, _night_set_back, schedule_nsb, T_nsb, power_reduction, window_areas, coords, debug)

Initializes an instance of the SpaceHeatingDemand class.

Parameters:

• dt_vector – List of time steps as datetime objects.

• resolution – Resolution in minutes.

• heated_area – Heated area in square meters.

• Tamb – Ambient temperature vector in degrees Celsius.

• I – Solar radiation vector in W/m2.

• Tb0 – Initial building temperature in degrees Celsius.

• dT_per_hour – Maximum change in temperature allowed per hour in degrees Celsius.

• eta – Heating process efficiency.

• thermal_intertia – Thermal inertia of the heating system.

• U – Building transmission losses in W/K.

• V – Building ventilation losses in W/K.

• C – Equivalent building thermal mass in J/K.

• Tset – Set temperature or target temperature in degrees Celsius.

• dTset – Delta temperature for Tset_min and Tset_max.

• activity_vector – Building activity vector (0, 1).

• occupancy_vector – Number of occupants in the building in each time step.

• sh_prob – Probability vector of using space heating.

• _solar_gains – Solar gains in W/m2.

• _internal_gains – Internal gains in W/m2.

• _night_set_back – Share of buildings with night set-back.

• schedule_nsb – Start and end of night set-back in hours.

• T_nsb – Night set-back temperature in degrees Celsius.

• power_reduction – Percentage of power reduced (as decimal).

• window_areas – Window area oriented to [E, S, W, N] in square meters.

• coords – (latitude, longitude) of the building centroid.

• debug – Debug flag.

calculate()

Calculates the time series of space heating demand for a single building as the numerical solution of a first order building thermal model (1R1C). Transmission and ventilation losses through infiltration are included.

Returns:

self.Tb self.sh_power self.internal_gains self.solar_gains

calculate_Tset(iii)

Returns Tset to original value or recalculates it depending on night set-back

calculate_flags(iii)

Calculates if heating system is active based on building temperature and building occupancy

calculate_internal_gains(iii)

Calculates heat gain in time step due to the activeness of the occupants:

• 80 W/occupant during the night (23:00 to 6:00)

• Random between 100 - 125 W/occupant for the rest of the day

From Validation of RC Building Models for Application in Energy and DSM (Kuniyoshi, 2017) EESC Kramer [VDI 2078]

Returns:

self.internal_gains[iii]: Heat gain in W

Return type:

float

calculate_solar_gains(iii, RED_FACTORS, ORIENTATION)

Calculates solar gains based on the windows size and orientation. Method adapted from TABULA

Returns:

self.solar_gains[iii]: Heat gain in W

Return type:

float

calculate_incident_solar_irradiation(day_of_year, hour, I_Gh, I_Dh, I_ex, hs, lat, lon, slope, orientation)

Calculates the global incident solar irradiation on tilted surface in W/m2. Based on HDKR radiation model (anisotropic model) from High-resolution spatio-temporal matching of residential electricity consumption and PV power production at the urban scale (Molar-Cruz, 2015)

Parameters:

• I_Gh (float) – Global horizonal radiation in W/m2

• I_Dh (float) – Diffuse horizontal radiation in W/m2

• I_ex (float) – Extraterrestrial solar radiation in W/m2

• hs (float) – Sun elevation angle in deg

• lat (float) – Latitude in degrees

• lon (float) – Longitude in degrees

• slope (int) – Inclination angle of window. Vertical = 90 deg

• orientation (int) – Window orientation

Returns:

I_Gt: Incident global solar radiation on tilted surface

Return type:

float