def calc_w3_heating_case(t5, w2, w5, t3, gv):
"""
Algorithm 1 Determination of the room's supply moisture content (w3) for the heating case
from Kaempf's HVAC model [1]
Source:
[1] Kämpf, Jérôme Henri
On the modelling and optimisation of urban energy fluxes
http://dx.doi.org/10.5075/epfl-thesis-4548
Parameters
----------
t5 : temperature 5 in (°C)
w2 : moisture content 2 in (kg/kg dry air)
w5 : moisture content 5 in (kg/kg dry air)
t3 : temperature 3 in (°C)
gv : globalvar
Returns
-------
w3 : moisture content of HVAC supply air in (kg/kg dry air)
"""
# get constants and properties
temp_comf_max = gv.temp_comf_max # limits of comfort in zone TODO: get from properties
hum_comf_max = gv.rhum_comf_max # limits of comfort in zone TODO: get from properties
w_liminf = calc_w(t5, 30) # TODO: document
w_limsup = calc_w(t5, 70) # TODO: document
w_comf_max = calc_w(
temp_comf_max,
hum_comf_max) # moisture content at maximum comfortable state
if w5 < w_liminf:
# humidification
w3 = w_liminf - w5 + w2
elif w5 > w_limsup and w5 < w_comf_max:
# heating and no dehumidification
# delta_HVAC = calc_t(w5,70)-t5
w3 = w2
elif w5 > w_comf_max:
# dehumidification
w3 = max(
min(min(w_comf_max - w5 + w2, calc_w(t3, 100)),
w_limsup - w5 + w2), 0)
else:
# no moisture control
w3 = w2
return w3
def calc_w3_heating_case(t5, w2, w5, t3, gv):
"""
Algorithm 1 Determination of the room's supply moisture content (w3) for the heating case from Kaempf's HVAC model
[Kämpf2009]_
:param t5: temperature 5 in (°C)
:type t5: numpy.float64
:param w2: moisture content 2 in (kg/kg dry air)
:type w2: numpy.float64
:param w5: moisture content 5 in (kg/kg dry air)
:type w5: numpy.float64
:param t3: temperature 3 in (°C)
:type t3: numpy.float64
:param gv: global variables
:type gv: cea.globalvar.GlobalVariables
:return: w3, moisture content of HVAC supply air in (kg/kg dry air)
:rtype: numpy.float64
"""
# get constants and properties
temp_comf_max = gv.temp_comf_max # limits of comfort in zone TODO: get from properties
hum_comf_max = gv.rhum_comf_max # limits of comfort in zone TODO: get from properties
w_liminf = calc_w(t5, 30) # TODO: document
w_limsup = calc_w(t5, 70) # TODO: document
w_comf_max = calc_w(
temp_comf_max,
hum_comf_max) # moisture content at maximum comfortable state
if w5 < w_liminf:
# humidification
w3 = w_liminf - w5 + w2
elif w5 > w_limsup and w5 < w_comf_max:
# heating and no dehumidification
# delta_HVAC = calc_t(w5,70)-t5
w3 = w2
elif w5 > w_comf_max:
# dehumidification
w3 = max(
min(min(w_comf_max - w5 + w2, calc_w(t3, 100)),
w_limsup - w5 + w2), 0)
else:
# no moisture control
w3 = w2
return w3
def calc_w3_heating_case(t5, w2, w5, t3, gv):
"""
Algorithm 1 Determination of the room's supply moisture content (w3) for the heating case
from Kaempf's HVAC model [1]
Source:
[1] Kämpf, Jérôme Henri
On the modelling and optimisation of urban energy fluxes
http://dx.doi.org/10.5075/epfl-thesis-4548
Parameters
----------
t5 : temperature 5 in (°C)
w2 : moisture content 2 in (kg/kg dry air)
w5 : moisture content 5 in (kg/kg dry air)
t3 : temperature 3 in (°C)
gv : globalvar
Returns
-------
w3 : moisture content of HVAC supply air in (kg/kg dry air)
"""
# get constants and properties
temp_comf_max = gv.temp_comf_max # limits of comfort in zone TODO: get from properties
hum_comf_max = gv.rhum_comf_max # limits of comfort in zone TODO: get from properties
w_liminf = calc_w(t5, 30) # TODO: document
w_limsup = calc_w(t5, 70) # TODO: document
w_comf_max = calc_w(temp_comf_max, hum_comf_max) # moisture content at maximum comfortable state
if w5 < w_liminf:
# humidification
w3 = w_liminf - w5 + w2
elif w5 > w_limsup and w5 < w_comf_max:
# heating and no dehumidification
# delta_HVAC = calc_t(w5,70)-t5
w3 = w2
elif w5 > w_comf_max:
# dehumidification
w3 = max(min(min(w_comf_max - w5 + w2, calc_w(t3, 100)), w_limsup - w5 + w2), 0)
else:
# no moisture control
w3 = w2
return w3
def calc_hex(rel_humidity_ext, gv, temp_ext, temp_zone_prev, timestep):
"""
Calculates air properties of mechanical ventilation system with heat exchanger
Modeled after 2.4.2 in SIA 2044
Parameters
----------
rel_humidity_ext : (%)
gv : globalvar
qv_mech : required air volume flow (kg/s)
temp_ext : external temperature at time t (°C)
temp_zone_prev : ventilation zone air temperature at time t-1 (°C)
Returns
-------
t2, w2 : temperature and moisture content of inlet air after heat exchanger
"""
# TODO add literature
# FIXME: dynamic HEX efficiency
# Properties of heat recovery and required air incl. Leakage
# qv_mech = qv_mech * 1.0184 # in m3/s corrected taking into account leakage # TODO: add source
# Veff = gv.Vmax * qv_mech / qv_mech_dim # Eq. (85) in SIA 2044
# nrec = gv.nrec_N - gv.C1 * (Veff - 2) # heat exchanger coefficient # TODO: add source
nrec = gv.nrec_N # for now use constant efficiency for heat recovery
# State No. 1
w1 = calc_w(temp_ext, rel_humidity_ext) # outdoor moisture (kg/kg)
# State No. 2
# inlet air temperature after HEX calculated from zone air temperature at time step t-1 (°C)
t2 = temp_ext + nrec * (temp_zone_prev - temp_ext)
w2 = min(w1, calc_w(t2,
100)) # inlet air moisture (kg/kg), Eq. (4.24) in [1]
# TODO: document
# bypass heat exchanger if use is not beneficial
if temp_zone_prev > temp_ext and not gv.is_heating_season(timestep):
t2 = temp_ext
w2 = w1
# print('bypass HEX cooling')
elif temp_zone_prev < temp_ext and gv.is_heating_season(timestep):
t2 = temp_ext
w2 = w1
# print('bypass HEX heating')
return t2, w2
def calc_hex(rel_humidity_ext, gv, temp_ext, temp_zone_prev, timestep):
"""
Calculates air properties of mechanical ventilation system with heat exchanger
Modeled after 2.4.2 in SIA 2044
Parameters
----------
rel_humidity_ext : (%)
gv : globalvar
qv_mech : required air volume flow (kg/s)
temp_ext : external temperature at time t (°C)
temp_zone_prev : ventilation zone air temperature at time t-1 (°C)
Returns
-------
t2, w2 : temperature and moisture content of inlet air after heat exchanger
"""
# TODO add literature
# FIXME: dynamic HEX efficiency
# Properties of heat recovery and required air incl. Leakage
# qv_mech = qv_mech * 1.0184 # in m3/s corrected taking into account leakage # TODO: add source
# Veff = gv.Vmax * qv_mech / qv_mech_dim # Eq. (85) in SIA 2044
# nrec = gv.nrec_N - gv.C1 * (Veff - 2) # heat exchanger coefficient # TODO: add source
nrec = gv.nrec_N # for now use constant efficiency for heat recovery
# State No. 1
w1 = calc_w(temp_ext, rel_humidity_ext) # outdoor moisture (kg/kg)
# State No. 2
# inlet air temperature after HEX calculated from zone air temperature at time step t-1 (°C)
t2 = temp_ext + nrec * (temp_zone_prev - temp_ext)
w2 = min(w1, calc_w(t2, 100)) # inlet air moisture (kg/kg), Eq. (4.24) in [1]
# TODO: document
# bypass heat exchanger if use is not beneficial
if temp_zone_prev > temp_ext and not gv.is_heating_season(timestep):
t2 = temp_ext
w2 = w1
# print('bypass HEX cooling')
elif temp_zone_prev < temp_ext and gv.is_heating_season(timestep):
t2 = temp_ext
w2 = w1
# print('bypass HEX heating')
return t2, w2
def calc_w3_cooling_case(t5, w2, t3, w5):
"""
Algorithm 2 Determination of the room's supply moisture content (w3) for the cooling case from Kaempf's HVAC model
for non-evaporative cooling
Source:
[1] Kämpf, Jérôme Henri
On the modelling and optimisation of urban energy fluxes
http://dx.doi.org/10.5075/epfl-thesis-4548
Parameters
----------
t5 : temperature 5 in (°C)
w2 : moisture content 2 in (kg/kg dry air)
t3 : temperature 3 in (°C)
w5 : moisture content 5 in (kg/kg dry air)
Returns
-------
w3 : moisture content of HVAC supply air in (kg/kg dry air)
"""
# get constants and properties
w_liminf = calc_w(t5, 30) # TODO: document
w_limsup = calc_w(t5, 70) # TODO: document
if w5 > w_limsup:
# dehumidification
w3 = max(min(w_limsup - w5 + w2, calc_w(t3, 100)), 0)
elif w5 < w_liminf:
# humidification
w3 = w_liminf - w5 + w2
else:
w3 = min(w2, calc_w(t3, 100))
return w3
def calc_w3_cooling_case(t5, w2, t3, w5):
"""
Algorithm 2 Determination of the room's supply moisture content (w3) for the cooling case from Kaempf's HVAC model
for non-evaporative cooling
Source: [Kämpf2009]_
:param t5: temperature 5 in (°C)
:type t5: numpy.float64
:param w2 : moisture content 2 in (kg/kg dry air)
:type w2: numpy.float64
:param t3: temperature 3 in (°C)
:type t3: numpy.float64
:param w5: moisture content 5 in (kg/kg dry air)
:type w5: numpy.float64
:return: w3, moisture content of HVAC supply air in (kg/kg dry air)
:rtype: numpy.float64
"""
# get constants and properties
w_liminf = calc_w(t5, 30) # TODO: document
w_limsup = calc_w(t5, 70) # TODO: document
if w5 > w_limsup:
# dehumidification
w3 = max(min(w_limsup - w5 + w2, calc_w(t3, 100)), 0)
elif w5 < w_liminf:
# humidification
w3 = w_liminf - w5 + w2
else:
w3 = min(w2, calc_w(t3, 100))
return w3
def calc_w3_cooling_case(t5, w2, t3, w5):
"""
Algorithm 2 Determination of the room's supply moisture content (w3) for the cooling case from Kaempf's HVAC model
for non-evaporative cooling
Source:
[1] Kämpf, Jérôme Henri
On the modelling and optimisation of urban energy fluxes
http://dx.doi.org/10.5075/epfl-thesis-4548
Parameters
----------
t5 : temperature 5 in (°C)
w2 : moisture content 2 in (kg/kg dry air)
t3 : temperature 3 in (°C)
w5 : moisture content 5 in (kg/kg dry air)
Returns
-------
w3 : moisture content of HVAC supply air in (kg/kg dry air)
"""
# get constants and properties
w_liminf = calc_w(t5, 30) # TODO: document
w_limsup = calc_w(t5, 70) # TODO: document
if w5 > w_limsup:
# dehumidification
w3 = max(min(w_limsup - w5 + w2, calc_w(t3, 100)), 0)
elif w5 < w_liminf:
# humidification
w3 = w_liminf - w5 + w2
else:
w3 = min(w2, calc_w(t3, 100))
return w3
def calc_hvac_cooling(tsd, hoy, gv):
"""
Calculate AC air mass flows, energy demand and temperatures
For the cooling case for AC systems with demand controlled ventilation air flows (mechanical ventilation) and
conditioning of recirculated air (outdoor air flows are not modified)
:param tsd: time series data dict
:type tsd: Dict[str, numpy.ndarray[numpy.float64]]
:param hoy: time step
:type hoy: int
:param gv: global variables
:type gv: cea.globalvar.GlobalVariables
:return: AC air mass flows, energy demand and temperatures for the cooling case
:rtype: Dict[str, numpy.float64]
"""
temp_zone_set = tsd['theta_a'][
hoy] # zone set temperature according to scheduled set points
qe_sen = tsd['Qcs_sen'][
hoy] / 1000 # get the total sensible load from the RC model in [W]
m_ve_mech = tsd['m_ve_mech'][
hoy] # mechanical ventilation flow rate according to ventilation control
wint = tsd['w_int'][hoy] # internal moisture gains from occupancy
rel_humidity_ext = tsd['rh_ext'][hoy] # exterior relative humidity
temp_ext = tsd['T_ext'][hoy] # exterior air temperature
temp_mech_vent = tsd['theta_ve_mech'][
hoy] # air temperature of mechanical ventilation air
# indoor air set point
t5 = temp_zone_set
if m_ve_mech > 0: # mechanical ventilation system is active, ventilation air and recirculation air gets conditioned
# State No. 1
w1 = calc_w(temp_ext, rel_humidity_ext) # outdoor moisture (kg/kg)
# ventilation air properties
# State No. 2
t2 = temp_mech_vent
w2 = min(w1,
calc_w(t2,
100)) # inlet air moisture (kg/kg), Eq. (4.24) in [1]
# State No. 3
# Assuming that AHU does not modify the air humidity
w3v = w2 # virtual moisture content at state 3
# determine virtual state in the zone without moisture conditioning
# moisture balance accounting for internal moisture load, see also Eq. (4.32) in [1]
w5_prime = (wint + w3v * m_ve_mech) / m_ve_mech
# supply air condition
t3 = gv.temp_sup_cool_hvac
# room supply moisture content:
# algorithm for cooling case
w3 = calc_w3_cooling_case(t5, w2, t3, w5_prime)
# State of Supply
ts = t3 # minus expected delta T rise in the ducts TODO: check and document value of temp decrease
ws = w3
# actual room condition
w5 = (wint + w3 * m_ve_mech) / m_ve_mech
h_w5_t5 = calc_h(t5, w5)
# now the energy of dehumidification can be calculated
h_t2_ws = calc_h(t2, ws)
h_t2_w2 = calc_h(t2, w2)
qe_dehum = m_ve_mech * (
h_t2_ws - h_t2_w2
) # (kW) # (kW) energy for dehumidification / latent cooling demand
# cooling load provided by conditioning ventilation air
h_t2_w2 = calc_h(t2, w2)
h_ts_w2 = calc_h(ts, w2)
q_cs_sen_mech_vent = m_ve_mech * (h_ts_w2 - h_t2_w2)
elif m_ve_mech == 0: # mechanical ventilation system is not active, only recirculation air gets conditioned
# supply air condition
t3 = gv.temp_sup_cool_hvac
# State of Supply
ts = t3 # minus expected delta T rise in the ducts TODO: check and document value of temp decrease
w5 = wint
h_w5_t5 = calc_h(t5, w5)
# No dehumidification of recirculation air as there is no model yet for internal humidity assessment
qe_dehum = 0
q_cs_sen_mech_vent = 0
t2 = temp_mech_vent
else:
raise
# calculate the part of the sensible load that is supplied by conditioning the recirculation air
# = additional load that has to be covered by conditioning room air through recirculation
# additional load can not be smaller than 0, over cooling situation
q_cs_sen_recirculation = min(qe_sen - q_cs_sen_mech_vent, 0) # (kW)
h_ts_w5 = calc_h(ts, w5)
m_ve_hvac_recirculation = q_cs_sen_recirculation / (h_ts_w5 - h_w5_t5)
# output parameters
q_cs_sen_hvac = (q_cs_sen_mech_vent + q_cs_sen_recirculation) * 1000
q_cs_lat_hvac = qe_dehum * 1000
ma_sup_cs = m_ve_mech + m_ve_hvac_recirculation
ta_sup_cs = ts
ta_re_cs = (
m_ve_mech * t2 + m_ve_hvac_recirculation *
t5) / ma_sup_cs # temperature mixing proportional to mass flow rates
# construct output dict
air_con_model_loads_flows_temperatures = {
'q_cs_sen_hvac': q_cs_sen_hvac,
'q_cs_lat_hvac': q_cs_lat_hvac,
'ma_sup_cs': ma_sup_cs,
'ta_sup_cs': ta_sup_cs,
'ta_re_cs': ta_re_cs,
'm_ve_hvac_recirculation': m_ve_hvac_recirculation
}
if m_ve_mech + m_ve_hvac_recirculation < 0:
raise ValueError
return air_con_model_loads_flows_temperatures
