t_set_heating = np.zeros(timesteps) # in Kelvin t_set_cooling = np.zeros(timesteps) + 600 # in Kelvin heater_limit = np.zeros((timesteps, 3)) + 1e10 cooler_limit = np.zeros((timesteps, 3)) - 1e10 # Calculate indoor air temperature T_air, Q_hc, Q_iw, Q_ow = low_order_VDI.reducedOrderModelVDI( houseData, weatherTemperature, solarRad_in, equalAirTemp, alphaRad, ventRate, Q_ig, source_igRad, krad, t_set_heating, t_set_cooling, heater_limit, cooler_limit, heater_order=np.array([1, 2, 3]), cooler_order=np.array([1, 2, 3]), dt=int(3600 / times_per_hour)) # Compute averaged results T_air_c = T_air - 273.15 T_air_mean = np.array([ np.mean(T_air_c[i * times_per_hour:(i + 1) * times_per_hour]) for i in range(24 * 60) ])
# Load constant house parameters houseData = tc.get_house_data(case=3) krad = 1 # Define set points (prevent heating or cooling!) t_set_heating = np.zeros(timesteps) # in Kelvin t_set_cooling = np.zeros(timesteps) + 600 # in Kelvin heater_limit = np.zeros((timesteps,3)) + 1e10 cooler_limit = np.zeros((timesteps,3)) - 1e10 # Calculate indoor air temperature T_air, Q_hc, Q_iw, Q_ow = low_order_VDI.reducedOrderModelVDI(houseData, weatherTemperature, solarRad_in, equalAirTemp, alphaRad, ventRate, Q_ig, source_igRad, krad, t_set_heating, t_set_cooling, heater_limit, cooler_limit, heater_order=np.array([1,2,3]), cooler_order=np.array([1,2,3]), dt=int(3600/times_per_hour)) # Compute averaged results T_air_c = T_air - 273.15 T_air_mean = np.array([np.mean(T_air_c[i*times_per_hour:(i+1)*times_per_hour]) for i in range(24*60)]) T_air_1 = T_air_mean[0:24] T_air_10 = T_air_mean[216:240] T_air_60 = T_air_mean[1416:1440] # Load reference results (T_air_ref_1, T_air_ref_10, T_air_ref_60) = tc.load_res("inputs/case03_res.csv") T_air_ref_1 = T_air_ref_1[:,0] T_air_ref_10 = T_air_ref_10[:,0]