def Run_Fleet(self, ts, sim_step, P_req, Q_req, return_forecast, WP):
# this module aggregates the PV information from a large pool of PV/invertre system
# Updates prepares report for system operator based on PV fleet
# Breaks down the operation command from system operator to subfleet and device level
if P_req == None:
P_req = []
if Q_req == None:
Q_req = []
def Grid_Param():
from grid_info import GridInfo
a = GridInfo('Grid_Info_DATA_2.csv')
V = a.get_voltage('XX')
f = a.get_frequency('XX')
return f, V
# pull information about the PV subfleet
P_rated = self.p_rated
P_min = self.p_min
S_max = self.s_max
Qmax_Plus = self.qmax_plus
Qmax_minus = self.qmax_minus
P_up = self.p_ramp_down
P_down = self.p_ramp_down
Q_up = self.q_ramp_down
Q_down = self.q_ramp_down
# Create Battery equivalent model (BEM) variables for the subfleets and PV fleet
# SubFleetA_NP_C='NA'
# SubFleetA_NP_P_grid_max=P_rated*self.SubFleet_NumberOfUnits #Minimum real power for services
# SubFleetA_NP_Q_grid_max=Qmax_Plus*self.SubFleet_NumberOfUnits#Maximum reactive power for services
# SubFleetA_NP_P_grid_min=P_min*self.SubFleet_NumberOfUnits#Minimum reactive power for services
# SubFleetA_NP_Q_grid_min=Qmax_minus*self.SubFleet_NumberOfUnits#Ramp rate real power up
# SubFleetA_NP_P_service_max=SubFleetA_NP_P_grid_max-SubFleetA_NP_P_grid_min#Ramp rate real power down
# SubFleetA_NP_Q_service_max=SubFleetA_NP_Q_grid_max-SubFleetA_NP_Q_grid_min#Ramp rate reactive power up
# SubFleetA_NP_P_service_min=0#Ramp rate reactive power down
# SubFleetA_NP_Q_service_min=0
SubFleetA_NP_P_up = P_up
SubFleetA_NP_Q_up = Q_up
SubFleetA_NP_P_down = P_down
SubFleetA_NP_Q_down = Q_down
# SubFleetA_NP_e_in='NA'
SubFleetA_NP_e_out = []
SubFleetA_NP_S_rating = S_max * self.SubFleet_NumberOfUnits
Fleet_PV_NP_C = 'NA'
# Fleet_PV_NP_P_grid_max=SubFleetA_NP_P_grid_max#Minimum real power for services
# Fleet_PV_NP_Q_grid_max=SubFleetA_NP_Q_grid_max#Maximum reactive power for services
# Fleet_PV_NP_P_grid_min=SubFleetA_NP_P_grid_min#Minimum reactive power for services
# Fleet_PV_NP_Q_grid_min=SubFleetA_NP_Q_grid_min#Ramp rate real power up
# Fleet_PV_NP_P_service_max=SubFleetA_NP_P_service_max#Ramp rate real power down
# Fleet_PV_NP_Q_service_max=SubFleetA_NP_Q_service_max#Ramp rate reactive power up
# Fleet_PV_NP_P_service_min=0#Ramp rate reactive power down
# Fleet_PV_NP_Q_service_min=0
Fleet_PV_NP_P_up = SubFleetA_NP_P_up
Fleet_PV_NP_Q_up = SubFleetA_NP_Q_up
Fleet_PV_NP_P_down = SubFleetA_NP_P_down
Fleet_PV_NP_Q_down = SubFleetA_NP_Q_down
Fleet_PV_NP_e_in = 'NA'
# Fleet_PV_NP_e_out=[]
FleetA_NP_S_rating = SubFleetA_NP_S_rating
# break down the command for fleet to command for device
Command_to_Device = self.Aggregator_Command(
P_req, Q_req, self.SubFleet_NumberOfUnits)
# Grid parameters required for autonomous mode of operation
#[Time_,P_rec,Q_rec,P_req_,Q_req_,P_MPP,G_rec,T_rec]\
[P_grid,Q_grid,P_service,Q_service,E_t0,c,P_output,Q_output,P_grid_max,Q_grid_max,\
P_grid_min,Q_grid_min,P_service_max,Q_service_max,P_service_min,Q_service_min,del_t_hold,\
t_restore,SP,N_req,Effeciency,sim_step]=self.Device_PV(ts,sim_step,Command_to_Device,return_forecast,WP)
#print(P_Output)
SubFleetA_P_grid = P_grid * self.SubFleet_NumberOfUnits / 1000
SubFleetA_Q_grid = Q_grid * self.SubFleet_NumberOfUnits / 1000
SubFleetA_P_service = P_service * self.SubFleet_NumberOfUnits / 1000
SubFleetA_Q_service = Q_service * self.SubFleet_NumberOfUnits / 1000
SubFleetA_E_t0 = E_t0
SubFleetA_c = c
SubFleetA_P_output = [
x * self.SubFleet_NumberOfUnits / 1000 for x in P_output
]
SubFleetA_Q_output = [
x * self.SubFleet_NumberOfUnits / 1000 for x in Q_output
]
SubFleetA_P_grid_max = [
x * self.SubFleet_NumberOfUnits / 1000 for x in P_grid_max
]
SubFleetA_Q_grid_max = [
x * self.SubFleet_NumberOfUnits / 1000 for x in Q_grid_max
]
SubFleetA_P_grid_min = [
x * self.SubFleet_NumberOfUnits / 1000 for x in P_grid_min
]
SubFleetA_Q_grid_min = [
x * self.SubFleet_NumberOfUnits / 1000 for x in Q_grid_min
]
SubFleetA_P_service_max = [
x * self.SubFleet_NumberOfUnits / 1000 for x in P_service_max
]
SubFleetA_Q_service_max = [
x * self.SubFleet_NumberOfUnits / 1000 for x in Q_service_max
]
SubFleetA_P_service_min = [
x * self.SubFleet_NumberOfUnits / 1000 for x in P_service_min
]
SubFleetA_Q_service_min = [
x * self.SubFleet_NumberOfUnits / 1000 for x in Q_service_min
]
SubFleetA_del_t_hold = del_t_hold
SubFleetA_t_restore = t_restore
SubFleetA_SP = SP
SubFleetA_N_req = N_req
SubFleetA_NP_e_out = Effeciency
# Calculate information about Subfleets
# Calculate information about Device Fleet: PV
# Calculate information about Subfleets
Fleet_PV_P_grid = SubFleetA_P_grid
Fleet_PV_Q_grid = SubFleetA_Q_grid
Fleet_PV_P_service = SubFleetA_P_service
Fleet_PV_Q_service = SubFleetA_Q_service
Fleet_PV_E_t0 = SubFleetA_E_t0
# Fleet_PV_c=SubFleetA_c
#
# Fleet_PV_P_output=SubFleetA_P_output
# Fleet_PV_Q_output=SubFleetA_Q_output
Fleet_PV_P_grid_max = SubFleetA_P_grid_max
Fleet_PV_Q_grid_max = SubFleetA_Q_grid_max
Fleet_PV_P_grid_min = SubFleetA_P_grid_min
Fleet_PV_Q_grid_min = SubFleetA_Q_grid_min
Fleet_PV_P_service_max = SubFleetA_P_service_max
Fleet_PV_Q_service_max = SubFleetA_Q_service_max
Fleet_PV_P_service_min = SubFleetA_P_service_min
Fleet_PV_Q_service_min = SubFleetA_Q_service_min
Fleet_PV_del_t_hold = SubFleetA_del_t_hold
Fleet_PV_t_restore = SubFleetA_t_restore
# Fleet_PV_SP=SubFleetA_SP
# Fleet_PV_N_req=SubFleetA_N_req
response = FleetResponse()
response.ts = ts
response.C = Fleet_PV_NP_C
response.dT_hold_limit = Fleet_PV_del_t_hold
response.E = Fleet_PV_E_t0
response.Eff_charge = Fleet_PV_NP_e_in
response.Eff_discharge = SubFleetA_NP_e_out
response.P_dot_down = Fleet_PV_NP_P_down
response.P_dot_up = Fleet_PV_NP_P_up
response.P_service = Fleet_PV_P_service
response.P_service_max = Fleet_PV_P_service_max
response.P_service_min = Fleet_PV_P_service_min
response.P_togrid = Fleet_PV_P_grid
response.P_togrid_max = Fleet_PV_P_grid_max[0]
response.P_togrid_min = Fleet_PV_P_grid_min[0]
response.Q_dot_down = Fleet_PV_NP_Q_down
response.Q_dot_up = Fleet_PV_NP_Q_up
response.Q_service = Fleet_PV_Q_service
response.Q_service_max = Fleet_PV_Q_service_max
response.Q_service_min = Fleet_PV_Q_service_min
response.Q_togrid = Fleet_PV_Q_grid
response.Q_togrid_max = Fleet_PV_Q_grid_max[0]
response.Q_togrid_min = Fleet_PV_Q_grid_min[0]
response.S_Rating = FleetA_NP_S_rating
response.T_restore = Fleet_PV_t_restore
response.P_base = Fleet_PV_P_grid_max[0]
response.sim_step = sim_step
response.Strike_price = 0
response.SOC_cost = 'na'
self.energy_impacts += abs(
response.P_service) * (int(sim_step.total_seconds()) / 3600)
return response
def run(self, P_req, Q_req, initSOC, t, dt, ts):
# ExecuteFleet(self, Steps, Timestep, P_request, Q_request, forecast):
# run(self, P_req=[0], Q_req=[0], ts=datetime.utcnow(), del_t=timedelta(hours=1)):
# Give the code the capability to respond to None requests
if P_req == None:
P_req = 0
if Q_req == None:
Q_req = 0
P_togrid = 0
P_service = 0
P_base = 0
P_service_max = 0
self.P_request_perWH = P_req / self.numWH # this is only for the first step
number = 0 # index for running through all the water heaters
NumDevicesToCall = 0
P_service_max0 = 0
# decision making about which water heater to call on for service, check if available at last step, if so then
# check for SoC > self.minSOC and Soc < self.maxSOC
for n in range(self.numWH):
if self.P_request_perWH < 0 and self.IsAvailableAdd[
n] > 0 and self.SOC[n] < self.maxSOC:
NumDevicesToCall += 1
elif self.P_request_perWH > 0 and self.IsAvailableShed[
n] > 0 and self.SOC[n] > self.minSOC:
NumDevicesToCall += 1
if P_req != None:
self.P_request_perWH = P_req / max(
NumDevicesToCall, 1
) # divide the fleet request by the number of devices that can be called upon
# create a .csv outputfile with each water heater's metrics
# outputfilename = join(self.base_path,"WH_fleet_outputs.csv")
# self.outputfile = open(outputfilename,"w")
# self.outputfile.write("Timestep,")
# create a .csv outputfile with P_service, P_togrid, and P_base
# outputfilename = join(self.base_path,"WH_fleet_outputs.csv")
#################################
for wh in self.whs: # loop through all water heaters
if P_req == None:
response = wh.execute(
self.TtankInitial[number], self.TtankInitial_b[number],
self.TsetInitial[number], self.Tamb[number][0],
self.RHamb[number][0], self.Tmains[number][0],
self.draw[number][0], 0, self.Type, self.dt,
self.draw_fleet_ave[0], self.element_on_last)
P_service = 0
if P_req < 0 and self.IsAvailableAdd[number] > 0:
response = wh.execute(
self.TtankInitial[number], self.TtankInitial_b[number],
self.TsetInitial[number], self.Tamb[number][0],
self.RHamb[number][0], self.Tmains[number][0],
self.draw[number][0], P_req, self.Type, self.dt,
self.draw_fleet_ave[0], self.element_on_last)
P_req = P_req - response.Eservice
P_service += response.Eservice
elif P_req > 0 and self.IsAvailableShed[number] > 0:
response = wh.execute(
self.TtankInitial[number], self.TtankInitial_b[number],
self.TsetInitial[number], self.Tamb[number][0],
self.RHamb[number][0], self.Tmains[number][0],
self.draw[number][0], P_req, self.Type, self.dt,
self.draw_fleet_ave[0], self.element_on_last)
P_req = P_req + response.Eservice
P_service -= response.Eservice
#print("P_req = {}, P_service = {}, Eservice = {}".format(P_req,P_service,response.Eservice))
else:
response = wh.execute(
self.TtankInitial[number], self.TtankInitial_b[number],
self.TsetInitial[number], self.Tamb[number][0],
self.RHamb[number][0], self.Tmains[number][0],
self.draw[number][0], 0, self.Type, self.dt,
self.draw_fleet_ave[0], self.element_on_last)
# print('P_req = {}'.format(P_req))
# assign returned parameters to associated lists to be recorded
self.element_on_last[number] = response.ElementOn
self.TtankInitial[number] = response.Ttank
self.TtankInitial_b[number] = response.Ttank_b
self.SOC[number] = response.SOC
self.SOCb[number] = response.SOC_b
self.IsAvailableAdd[number] = response.IsAvailableAdd
self.IsAvailableShed[number] = response.IsAvailableShed
self.AvailableCapacityAdd[number] = response.AvailableCapacityAdd
self.AvailableCapacityShed[number] = response.AvailableCapacityShed
self.ServiceCallsAccepted[number] = response.ServiceCallsAccepted
self.ServiceProvided[number] = response.Eservice
'''
P_togrid -= response.Eused
P_base -= response.Pbase
if P_req <0 or P_req > 0:
P_response = (P_togrid - P_base)
else:
P_response = 0
'''
P_togrid -= response.Eused
P_base -= response.Pbase
# self.outputfile.write(str(response.Ttank) +"," + str(self.TsetInitial[number]) + "," + str(response.Eused) + "," + str(response.PusedMax) + "," + str(response.Eloss) + "," + str(response.ElementOn) + "," + str(response.Eservice) + "," + str(response.SOC) + "," + str(response.AvailableCapacityAdd) + "," + str(response.AvailableCapacityShed) + "," + str(response.ServiceCallsAccepted) + "," + str(response.IsAvailableAdd) + "," + str(response.IsAvailableShed) + "," + str(self.draw[number][0]) + "," + str(response.Edel) + ",")
# resp.sim_step = response.sim_step
number += 1 # go to next device
if P_req <= 0:
P_service_max += response.AvailableCapacityShed # NOTE THIS ASSUMES THE MAX SERVICE IS LOAD SHED
else:
P_service_max0 += response.AvailableCapacityAdd
P_service_max = -1.0 * P_service_max0
# self.outputfile.write("\n")
self.step += 1 # To advance the step by step in the disturbance file
# Output Fleet Response
resp = FleetResponse()
resp.P_service = []
resp.P_service_max = []
resp.P_service_min = []
resp.P_togrid = []
resp.P_togrid_max = []
resp.P_togrid_min = []
resp.P_forecast = []
resp.P_base = []
resp.E = []
resp.C = []
resp.ts = ts
resp.sim_step = dt
# resp.P_dot_up = resp.P_togrid_max / ServiceRequest.Timestep.seconds
resp.P_service_max = P_service_max
resp.P_service = P_service
resp.P_base = P_base
resp.P_togrid = P_togrid
# if P_service != 0:
# print("resp.P_base = {}".format(resp.P_base))
# print("Pbase = {}".format(resp.P_base))
# print("Ptogrid = {}".format(resp.P_togrid))
# Available Energy stored at the end of the most recent timestep
# resp.E += response.Estored
resp.E = 0
resp.C += response.SOC / (self.numWH)
resp.Q_togrid = 'NA'
resp.Q_service = 'NA'
resp.Q_service_max = 'NA'
resp.Q_service_min = 'NA'
resp.Q_togrid_min = 'NA'
resp.Q_togrid_max = 'NA'
resp.Q_dot_up = 'NA'
resp.Q_dot_down = 'NA'
resp.P_dot_up = 0
resp.P_dot_down = 0
resp.Eff_charge = 1.0 # TODO: change this if we ever use a HPWH to use the HP efficiency
resp.Eff_discharge = 1.0 # always equal to 1 for this device
resp.P_dot = resp.P_togrid / dt
resp.P_service_min = 0
resp.dT_hold_limit = 'NA'
resp.T_restore = 'NA'
resp.Strike_price = 'NA'
resp.SOC_cost = 'NA'
# TotalServiceProvidedPerTimeStep[step] = -1.0*self.P_service # per time step for all hvacs -1.0*
"""
Modify the power and SOC of the different subfeets according
to the frequency droop regulation according to IEEE standard
"""
if self.FW21_Enabled and self.is_autonomous:
power_ac = resp.P_service_max
p_prev = resp.P_togrid
power_fleet = self.frequency_watt(power_ac, p_prev, self.ts,
self.location,
self.db_UF_subfleet,
self.db_OF_subfleet)
power_fleet, SOC_step = self.update_soc_due_to_frequency_droop(
initSOC, power_fleet, dt)
self.time = t + dt
self.ts = self.ts + timedelta(seconds=dt)
# Restart time if it surpasses 24 hours
if self.time > 24 * 3600:
self.time = self.time - 24 * 3600
# Impact Metrics
# Update the metrics
'''
Ttotal = 0
SOCTotal = 0
self.cycle_basee = np.sum(self.cycle_off_base)
self.cycle_basee += np.sum(self.cycle_on_base)
self.cycle_grid = np.sum(self.cycle_off_grid)
self.cycle_grid += np.sum(self.cycle_on_grid)
'''
for number in range(self.numWH):
if response.Ttank <= self.TsetInitial[
number] - 10: # assume 10F deadband (consistent with wh.py)
self.unmet_hours += 1 * self.sim_step / 3600.0
if resp.P_base == 0 and resp.P_togrid == 0:
self.ratio_P_togrid_P_base = 1.0
elif resp.P_base == 0 and resp.P_togrid != 0:
self.ratio_P_togrid_P_base = 'NA'
else:
self.ratio_P_togrid_P_base = resp.P_togrid / (resp.P_base)
self.energy_impacts += abs(resp.P_service) * (self.sim_step / 3600)
return resp
def fc_model(self, ts, sim_step, Preq, forecast=False, start_time=None):
"""
:param ts: Request created for current time-step: datetime
:param sim_step: Request for simulation time-step: timedelta object
:param Preq: Request for current real power request
:param forecast: Returns fleet response forecast
:param start_time: Request for current real power request
:return resp: Fleet response object
"""
if self.P_tank_ideal <= self.min_charge:
pass
else:
# Create base power profile
if isinstance(self.p, ndarray):
self.__p_base = sum([
self.p[j] * (self.__inc + 1)**(21 - j) for j in range(22)
])
else:
self.__p_base = self.p
# Ptogrid: Pbase for None or zero requests since FC is a source
if Preq is None or float(Preq) == 0.0:
Preq = self.__p_base
# Ptogrid: Preq+Pbase for +ve or -ve requests
else:
Preq += self.__p_base
# Compute the power generated by the fleet
self.__fc_p_calc(Preq)
if self.FW21_Enabled and self.is_autonomous:
# all in kW
Preq, self.f = self.frequency_watt(p_pre=self.__p_tot_ideal,
p_avl=self.fc_Pmax_fleet,
p_min=self.fc_Pmin_fleet,
ts=ts,
start_time=start_time)
self.__p_tot_ideal = Preq
# Update SOC
self.__soc_calc()
self.__inc += 1
# Response
# Power injected is positive
resp = FleetResponse()
resp.ts = ts
resp.sim_step = sim_step
resp.C = 0
resp.dT_hold_limit = 0
resp.E = self.soc_ideal
resp.Eff_charge = 1.0
resp.Eff_discharge = self.__eta_ds
resp.P_dot_down = 0
resp.P_dot_up = 0
resp.P_togrid = self.__p_tot_ideal
resp.P_togrid_max = self.fc_Pmax_fleet
resp.P_togrid_min = self.fc_Pmin_fleet
resp.P_service = resp.P_togrid - self.__p_base
resp.P_service_max = self.fc_Pmax_fleet - self.__p_base
resp.P_service_min = self.__p_base - self.fc_Pmin_fleet
resp.Q_dot_down = 0
resp.Q_dot_up = 0
resp.Q_service = 0
resp.Q_service_max = 0
resp.Q_service_min = 0
resp.Q_togrid = 0
resp.Q_togrid_max = 0
resp.Q_togrid_min = 0
resp.T_restore = 0
resp.P_base = self.__p_base
resp.Q_base = 0
resp.Strike_price = 0
resp.SOC_cost = 0
# Impact metrics
if not forecast:
self.metrics.append([
str(ts),
str(self.__Vr),
str(self.__Vr_age),
str(self.__ne),
str(self.__ne_age),
str(self.soc_ideal * 1e2),
str(self.soc_age * 1e2),
str(self.lka_h2),
str(self.__eta_ds * 1e2)
])
# Print Soc every 5 secs.
if self.__inc % 5000 == 0:
print("Soc:%4.2f%%" % (resp.E * 1e2))
return resp