def set_HVAC_T(dt_sim_time,df_bids_HVAC,mean_p,var_p, Pd):
df_bids_HVAC.at[df_bids_HVAC['bid_p'] >= Pd,'active'] = 1
df_bids_HVAC['p_max'] = mean_p+df_bids_HVAC['k']*var_p
df_bids_HVAC['temp'] = df_bids_HVAC['T_min'] + (df_bids_HVAC['p_max'] - Pd)*(df_bids_HVAC['T_h0'] - df_bids_HVAC['T_min'])/(2*df_bids_HVAC['k']*var_p)
df_bids_HVAC['temp'] = df_bids_HVAC[['temp','T_min']].max(axis=1)
df_bids_HVAC['temp'] = df_bids_HVAC[['temp','T_h0']].min(axis=1)
df_bids_HVAC.loc[df_bids_HVAC['system_mode'] == 'HEAT','heating_setpoint'] = df_bids_HVAC['temp']
df_bids_HVAC.loc[df_bids_HVAC['system_mode'] == 'HEAT','cooling_setpoint'] = p_max #where should those be to not harm?
df_bids_HVAC.loc[df_bids_HVAC['system_mode'] == 'OFF','cooling_setpoint'] = p_max #where should those be to not harm?
df_bids_HVAC['temp'] = df_bids_HVAC['T_max'] + (df_bids_HVAC['p_max'] - Pd)*(df_bids_HVAC['T_c0'] - df_bids_HVAC['T_max'])/(2*df_bids_HVAC['k']*var_p)
df_bids_HVAC['temp'] = df_bids_HVAC[['temp','T_c0']].max(axis=1)
df_bids_HVAC['temp'] = df_bids_HVAC[['temp','T_max']].min(axis=1)
df_bids_HVAC.loc[df_bids_HVAC['system_mode'] == 'COOL','cooling_setpoint'] = df_bids_HVAC['temp']
df_bids_HVAC.loc[df_bids_HVAC['system_mode'] == 'COOL','heating_setpoint'] = 0.0 #where should those be to not harm?
df_bids_HVAC.loc[df_bids_HVAC['system_mode'] == 'OFF','heating_setpoint'] = 0.0 #where should those be to not harm?
#Write to GridlabD objects
#Read information via database later on!
for house in houselist:
cooling_setpoint = df_bids_HVAC['cooling_setpoint'].loc[df_bids_HVAC['house_name'] == house].values[0]
heating_setpoint = df_bids_HVAC['heating_setpoint'].loc[df_bids_HVAC['house_name'] == house].values[0]
active = df_bids_HVAC['active'].loc[df_bids_HVAC['house_name'] == house].values[0]
#Can I do that for the whole table with a dataframe?
#mysql_functions.set_values('market_HVAC_meter', '(system_mode,heating_setpoint,cooling_setpoint,active,timedate,appliance_id)',('OFF',float(heating_setpoint),float(cooling_setpoint),int(active),dt_sim_time,houselist.index(house)+1,))
#Write to gridlabd (to be done from mysql in future)
gridlabd_functions.set(house,'cooling_setpoint',cooling_setpoint)
gridlabd_functions.set(house,'heating_setpoint',heating_setpoint)
return df_bids_HVAC
def transactive_price(house, T_curr, T_c_set, T_h_set, mean_p, var_p, epsilon): T_zero_h = T_h_set + (T_c_set - T_h_set)/2 - epsilon/2 T_zero_c = T_c_set - (T_c_set - T_h_set)/2 + epsilon/2 T_max = float(gridlabd_functions.get(house,'T_max')['value'][1:]) T_min = float(gridlabd_functions.get(house,'T_min')['value'][1:]) k = float(gridlabd_functions.get(house,'k')['value'][1:]) if T_curr > T_max or T_curr < T_min: return 1 #max price # cooling elif T_curr > T_zero_c: #Remains here if comfort settings are changed during operation m = (mean_p + k * np.sqrt(var_p))/(T_max - T_zero_c) gridlabd_functions.set(house,'m',m) n = - m * T_zero_c gridlabd_functions.set(house,'n',n) return (m * T_curr + n) # heating elif T_curr < T_zero_h: m = (mean_p + k * np.sqrt(var_p))/(T_min - T_zero_h) gridlabd_functions.set(house,'m',m) n = - m * T_zero_h gridlabd_functions.set(house,'n',n) return (m * T_curr + n) else: return 0
def shutdown_house(unresp_load,dt_sim_time,houses_off=[],market=None):
if market:
Pmax = market.Pmax
else:
Pmax = 100.0
while True:
house_OFF = np.random.choice(houselist_inflex)
while house_OFF in houses_off:
house_OFF = np.random.choice(houselist_inflex)
house_currHVAC = float(gridlabd_functions.get(house_OFF,'hvac_load')['value'][:-3])
if house_currHVAC > 0.0:
unresp_load -= house_currHVAC
print 'Switch off '+str(house_OFF)+' to '+str(unresp_load)
gridlabd_functions.set(house_OFF,'thermostat_control','NONE')
gridlabd_functions.set(house_OFF,'system_mode','OFF')
houses_off += [house_OFF]
mysql_functions.set_values('system_operations', '(timedate,q,costs,appliance_name)',(dt_sim_time,house_currHVAC,Pmax,'HVAC'+house_OFF[3:],))
break
print 'Ready: '+str(unresp_load)
return unresp_load, houses_off
def switch_on(s_SO):
#houses
if 'GLD' in s_SO['appliance_name']:
gridlabd_functions.set(s_SO['appliance_name'],'thermostat_control','FULL')
#batteries
elif 'Bat' in s_SO['appliance_name']:
gridlabd_functions.set('Bat_inverter_'+s_SO['appliance_name'][8:],'P_Out',-s_SO['q']*1000)
#EV
elif 'EV' in s_SO['appliance_name']:
gridlabd_functions.set('EV_inverter_'+s_SO['appliance_name'][3:],'P_Out',-s_SO['q']*1000)
else:
print s_SO['appliance_name']+' is not recognized'
return
def switch_off(s_awarded,dt_sim_time):
#houses
if 'GLD' in s_awarded['appliance_name']:
gridlabd_functions.set(s_awarded['appliance_name'],'thermostat_control','NONE')
#batteries
elif 'Bat' in s_awarded['appliance_name']:
gridlabd_functions.set('Bat_inverter_'+s_awarded['appliance_name'][8:],'P_Out',0.0)
#EV
elif 'EV' in s_awarded['appliance_name']:
gridlabd_functions.set('EV_inverter_'+s_awarded['appliance_name'][3:],'P_Out',0.0)
else:
print s_awarded['appliance_name']+' is not recognized'
mysql_functions.set_values('system_operations', '(timedate,q,costs,appliance_name)',(dt_sim_time,float(s_awarded['q_bid']),float(s_awarded['p_bid']),s_awarded['appliance_name'],))
return
#C = 3262 + random.uniform(-10,10) #for test purposes [in kW]
C = 800.0 #capacity restriction
mysql_functions.set_values('capacity_restrictions', '(cap_rest,timedate)',(C,dt_sim_time,)) #in kW
retail.sell(C,supply_costs,gen_name='WS') #in [USD/kW] #How can I tweak clearing that we can name biider 'WS'?
mysql_functions.set_values('supply_bids', '(bid_price,bid_quantity,timedate,gen_name)',(float(supply_costs),float(C),dt_sim_time,'wholesale'))
###
#Market clearing (kW)
###
retail.clear()
Pd = retail.Pd # cleared demand price
Qd = retail.Qd #in kW
mysql_functions.set_values('clearing_pq', '(clearing_price,clearing_quantity,timedate)',(Pd,Qd,dt_sim_time,))
#for calculation of monthly bill in GridlabD / to be deleted when DB is active in GridlabD
gridlabd_functions.set('retail','price',Pd)
###
#Redistribute prices and quantities to market participants
###
#Save market result for each HVAC system
#df_bids_HVAC = HHfct.set_HVAC_T(dt_sim_time,df_bids_HVAC,mean_p,var_p, Pd) #Sets new T setpoint according to price
#df_bids_HVAC = HHfct.set_HVAC_by_price(dt_sim_time,df_bids_HVAC,mean_p,var_p, Pd) #Switches the HVAC system on and off directly (depending on bid >= p)
df_bids_HVAC = HHfct.set_HVAC_by_award(dt_sim_time,df_bids_HVAC,retail) #Switches the HVAC system on and off directly (depending on award)
#Battery
#df_bids_battery = HHfct.set_battery_by_price(dt_sim_time,df_bids_battery,mean_p,var_p, Pd) #Controls battery based on bid <-> p
df_bids_battery = HHfct.set_battery_by_award(dt_sim_time,df_bids_battery,retail) #Controls battery based on award
def initialize():
mysql_functions.clear_databases()
print('Initialize')
#Start time of simulation is '2017-07-01 12:00:00' EST+5 - get this from GLOBALS or likewise
interval = int(gridlabd_functions.get('retail',
'interval')['value']) #in seconds
#prev_timedate = datetime.datetime(2015, 6, 30, 23, 60 - (interval/60))
#prev_timedate = datetime.datetime(2015, 7, 1, 4, 60 - (interval/60))
dt = parser.parse(os.getenv("clock"))
prev_timedate = dt - timedelta(minutes=interval / 60)
#Get list of house objects in GLM file and assign to global GLD variable "houselist"
#houses = gridlabd_functions.find('class=house')
#houselist = [];
#Read in wholesale market prices
df_prices = pandas.read_csv('ercot_2017.csv', parse_dates=[0])
mysql_functions.set_WSmarket(df_prices)
#Check if downgrading pycurl changes gridlabd_functions
# from sqlalchemy import create_engine
# engine = create_engine("mysql://*****:*****@127.0.0.1/gridlabd")
# con = engine.connect()
# df_prices.to_sql(name='WS_market',con=con,if_exists='append')
# con.close()
for house in houselist:
#houselist.append(name)
#Fills TABLE market_houses (can this be done via GridlabD directly?)
mysql_functions.set_values('market_houses', '(house_name)', (house, ))
#Fills TABLE market_appliances (can this be done via GridlabD directly?)
#HVAC
k = float(gridlabd_functions.get(house, 'k')['value'])
T_min = float(gridlabd_functions.get(house, 'T_min')['value'])
T_max = float(gridlabd_functions.get(house, 'T_max')['value'])
heat_q = float(
gridlabd_functions.get(
house,
'heating_demand')['value'][1:-3]) #heating_demand is in kW
hvac_q = float(
gridlabd_functions.get(
house,
'cooling_demand')['value'][1:-3]) #cooling_demand is in kW
#mysql_functions.set_values('market_HVAC', '(house_name,appliance_name,k,T_min,T_max,P_heat,P_cool)',(house['name'],'HVAC_'+str(houses.index(house)+1),k,T_min,T_max,heat_q,hvac_q,))
mysql_functions.set_values(
'market_HVAC',
'(house_name,appliance_name,k,T_min,T_max,P_heat,P_cool)', (
house,
'HVAC_' + house[4:],
k,
T_min,
T_max,
heat_q,
hvac_q,
))
#Fills TABLE market_appliance_meter
#HVAC
heating_setpoint = float(
gridlabd_functions.get(house, 'heating_setpoint')['value'][1:-5])
cooling_setpoint = float(
gridlabd_functions.get(house, 'cooling_setpoint')['value'][1:-5])
#Set values for previous period, i.e. start - interval
#mysql_functions.set_values('market_HVAC_meter', '(system_mode,heating_setpoint,cooling_setpoint,active,timedate,appliance_id)',('OFF',heating_setpoint,cooling_setpoint,0,prev_timedate,houses.index(house)+1,))
mysql_functions.set_values(
'market_HVAC_meter',
'(system_mode,av_power,heating_setpoint,cooling_setpoint,active,timedate,appliance_id)',
(
'OFF',
0.0,
heating_setpoint,
cooling_setpoint,
0,
prev_timedate,
int(house.split('_')[-1]),
))
#gridlabd_functions.set('houselist',';'.join(houselist))
#batteries = gridlabd_functions.find('class=battery')
for battery in batterylist:
house_name = 'GLD_' + battery[8:]
#Fills TABLE market_appliances
SOC_max = float(
gridlabd_functions.get(battery, 'battery_capacity')['value']
[:-3]) / 1000 #Wh in Gridlabd -> kWh
str_i_max = gridlabd_functions.get(battery,
'I_Max')['value'][:-2].replace(
'-', '+')
i_max = str_i_max.split('+')[1]
u_max = float(gridlabd_functions.get(battery, 'V_Max')['value']
[:-2]) * float(i_max) / 1000 #W -> kW #better inverter?
eff = float(
gridlabd_functions.get(battery, 'base_efficiency')['value'][:-5])
mysql_functions.set_values(
'market_battery',
'(house_name,appliance_name,appliance_id,SOC_max,u_max,eff)', (
house_name,
battery,
int(battery.split('_')[-1]),
SOC_max,
u_max,
eff,
))
#Fills TABLE market_appliance_meter
SOC_0 = float(
gridlabd_functions.get(battery,
'state_of_charge')['value'][:-3]) * SOC_max
mysql_functions.set_values('market_battery_meter',
'(SOC,active,timedate,appliance_id)', (
SOC_0,
0,
prev_timedate,
int(battery.split('_')[-1]),
))
for EV in EVlist:
house_name = 'GLD_' + EV[3:]
#Fills TABLE market_appliances
SOC_max = float(
gridlabd_functions.get(EV, 'battery_capacity')['value']
[:-3]) / 1000 #Wh in Gridlabd -> kWh
str_i_max = gridlabd_functions.get(EV, 'I_Max')['value'][:-2].replace(
'-', '+')
i_max = str_i_max.split('+')[1]
u_max = float(gridlabd_functions.get(EV, 'V_Max')['value']
[:-2]) * float(i_max) / 1000 #W -> kW #better inverter?
eff = float(
gridlabd_functions.get(EV, 'base_efficiency')['value'][:-5])
charging_type = gridlabd_functions.get(EV, 'charging_type')['value']
k = gridlabd_functions.get(EV, 'k')['value']
mysql_functions.set_values(
'market_EV',
'(house_name,appliance_name,appliance_id,SOC_max,u_max,eff,charging_type,k)',
(
house_name,
EV,
int(EV.split('_')[-1]),
SOC_max,
u_max,
eff,
charging_type,
k,
))
#Fills TABLE market_appliance_meter
mysql_functions.set_values(
'market_EV_meter', '(connected,SOC,active,timedate,appliance_id)',
(
0,
0,
0,
prev_timedate,
int(EV.split('_')[-1]),
))
#Set all cars offline/disconnected in the beginning
gridlabd_functions.set(EV, 'generator_status', 'OFFLINE')
df_events = pandas.read_csv('EV_events.csv', index_col=[0])
df_events.to_csv('EV_events_pop.csv')
# PVs = gridlabd_functions.find('class=solar')
for pv in pvlist:
house_name = 'GLD_' + pv[3:]
#Fills TABLE market_appliances
inverter_name = 'PV_inverter_' + pv[3:]
rated_power = float(
gridlabd_functions.get(inverter_name,
'rated_power')['value'][:-3]) / 1000
mysql_functions.set_values(
'market_pv',
'(house_name,appliance_name,inverter_name,appliance_id,rated_power)',
(
house_name,
pv,
inverter_name,
int(pv.split('_')[-1]),
rated_power,
))
#Fills TABLE market_appliance_meter
production = float(
gridlabd_functions.get(inverter_name,
'P_Out')['value'][:-3]) / 1000
mysql_functions.set_values('market_pv_meter',
'(P_Out,timedate,appliance_id)', (
production,
prev_timedate,
int(pv.split('_')[-1]),
))
return dt
import os
import gridlabd_functions
import random
import pandas
import pycurl
import json
from StringIO import StringIO
#Get list of house objects in GLM file and assign to global GLD variable "houselist"
houses = gridlabd_functions.find('class=house')
houselist = []
for house in houses:
name = house['name']
houselist.append(name)
gridlabd_functions.set('houselist', ';'.join(houselist))
print(houselist)
soc_setpoint = 0.7 # Baterry SOC target
#Get state of charge of Battery object
soc_read = gridlabd_functions.get('node1_batt', 'state_of_charge')
soc = float(soc_read['value'][1:-3])
#Get power in the mains object
p_hApp_read = gridlabd_functions.get('meter1', 'measured_real_power')
p_hApp = float(p_hApp_read['value'][1:-2])
#Print out timestep and state of charge
sim_time = os.getenv("clock")
print soc
# print sim_time
print p_hApp
k = 20000 # Controller gain
p_control = -(soc_setpoint - soc) * k
gridlabd_functions.set('node1_batt_inv', 'P_Out',
p_control) # Write p_control to battery
#batt_delta = -(p_cc - p_hApp)
#gridlabd_functions.set('node1_batt_inv','P_Out',batt_delta) #Write P_Out to battery object
'''
if sim_time[14] != "4":
set_P_out=1000
gridlabd_functions.set('node1_batt_inv','P_Out',set_P_out) #Write P_Out to battery object
else:
gridlabd_functions.set('node1_batt_inv','P_Out',set_P_out)
# print "P_OUT:", set_P_out'''
#Get power in the mains object
p_hApp_read = gridlabd_functions.get('meter1','measured_real_power')
print "p_hApp_read: ", p_hApp_read
p_hApp = float(p_hApp_read['value'][1:-2])
'''
#Print out timestep and state of charge
sim_time = os.getenv("clock")
#print soc
# print sim_time
#print p_hApp
#k = 20000 # Controller gain
#p_control = -(soc_setpoint - soc)*k
#gridlabd_functions.set('node1_batt_inv','P_Out',p_control) # Write p_control to battery
#batt_delta = -(p_cc - p_hApp)
#gridlabd_functions.set('node1_batt_inv','P_Out',batt_delta) #Write P_Out to battery object
set_P_out = 0.099
if sim_time[14] != "4":
set_P_out = 1000
gridlabd_functions.set('node1_batt_inv_H1', 'P_Out',
set_P_out) #Write P_Out to battery object
else:
gridlabd_functions.set('node1_batt_inv_H1', 'P_Out', set_P_out)
# print "P_OUT:", set_P_out
prices = DataPreLoaded_Prices("pricesCurrent.csv", 0)
Q, U, boundsFlag = LC_Combined_No_Bounds_MultiHome(
NLweight, prices, sellFactor, q0, LCscens, GCtime, umaxo, umino,
qmaxo, qmino, number_of_houses)
U = -U
print 'U: ', U
#u = 1000*U[0][0]
#houses_dict[1]['Battery_LC_U'] = u
u = BatteryProfiles(U, batt_solar_houses)
print 'Battery Profile: ', u
#houses_dict[1]['Battery_LC_U'] = u[0]
#houses_dict[3]['Battery_LC_U'] = u[1]
print 'GLD set u: ', u
for idx, b in enumerate(battery_GLD):
gridlabd_functions.set(b, 'P_Out', u[idx])
#print 'House number: ', b
#print 'Power value: ', u[idx]
#gridlabd_functions.set('node1_batt_inv_H1','P_Out',u[0])
#gridlabd_functions.set('node1_batt_inv_H3','P_Out',u[1])
# Creating file with new data
#rwText.create_file_json('TestGLD.json', houses_dict)
###############################################
# Old Functions
'''
######## LC Controller House 1 #########
try:
with open('home_U.json') as file:
pass
import gridlabd_functions
import os
#Get state of charge of Battery object
SOC = gridlabd_functions.get('node1_batt', 'state_of_charge')
print(SOC['value'])
print(os.getenv("clock"))
#Write P_Out to battery object
gridlabd_functions.set('node1_batt_inv', 'P_Out', -1000)
def set_HVAC_setpoint(house,control_type,bid_price,Pd):
#Set state: Load is active in that period
if bid_price >= Pd:
gridlabd_functions.set(house,'state',True)
else:
gridlabd_functions.set(house,'state',False)
if 'deadband' in control_type:
if bid_price >= Pd and bid_price > 0: #to exclude consumption when price is zero
#switch on HVAC
if 'COOL' in gridlabd_functions.get(house,'bid_mode')['value']:
gridlabd_functions.set(house,'system_mode','COOL')
elif 'HEAT' in gridlabd_functions.get(house,'bid_mode')['value']:
gridlabd_functions.set(house,'system_mode','HEAT')
else:
print('Check bid mode - there might be an inconsistency in bidding and actual behavior')
return
else:
#turn off HVAC
gridlabd_functions.set(house,'system_mode','OFF')
#gridlabd_functions.set('control_1','control','OFF')
return
elif ('trans' in control_type):
m = float(gridlabd_functions.get(house,'m')['value'])
n = float(gridlabd_functions.get(house,'n')['value'])
T_max = float(gridlabd_functions.get(house,'T_max')['value'][1:])
T_min = float(gridlabd_functions.get(house,'T_min')['value'][1:])
#change setpoint on HVAC
if 'COOL' in gridlabd_functions.get(house,'bid_mode')['value']:
gridlabd_functions.set(house,'system_mode','COOL')
# calculate new setpoint
T_c_set_new = (Pd - n)/m
if T_c_set_new > T_max:
gridlabd_functions.set(house,'cooling_setpoint',T_max)
else:
gridlabd_functions.set(house,'cooling_setpoint',T_c_set_new)
elif 'HEAT' in gridlabd_functions.get(house,'bid_mode')['value']:
gridlabd_functions.set(house,'system_mode','HEAT')
#calculate new setpoint
T_h_set_new = (Pd - n)/m
if T_h_set_new < T_min:
gridlabd_functions.set(house,'heating_setpoint',T_min)
else:
gridlabd_functions.set(house,'heating_setpoint',T_h_set_new)
else:
gridlabd_functions.set(house,'system_mode','OFF')
return
else:
print('HVAC could not be set')
return
def bid_rule_HVAC(house, mean_p, var_p, interval):
control_type = gridlabd_functions.get(house,'control_type')['value']
k = float(gridlabd_functions.get(house,'k')['value'][1:])
T_c_set = float(gridlabd_functions.get(house,'T_c_set_0')['value'][1:])
T_h_set = float(gridlabd_functions.get(house,'T_h_set_0')['value'][1:])
#T_curr = float(gridlabd_functions.get(house,'air_temperature')['value'][1:-5])
#calculate energy
hvac_q = float(gridlabd_functions.get(house,'cooling_demand')['value'][1:-3]) * interval / (60*60)
heat_q = float(gridlabd_functions.get(house,'heating_demand')['value'][1:-3]) * interval / (60*60)
#State of appliance in previous period
status = int(gridlabd_functions.get(house,'state')['value'])
if 'deadband' in control_type:
# cooling
if T_curr > T_c_set + k:
bid_price = 1
bid_quantity = hvac_q
gridlabd_functions.set(house,'bid_mode','COOL')
return bid_quantity, bid_price, status
# heating
elif T_curr < T_h_set - k:
bid_price = 1
bid_quantity = heat_q
gridlabd_functions.set(house,'bid_mode','HEAT')
return bid_quantity, bid_price, status
# no activity
else:
bid_price = 0
bid_quantity = 0
gridlabd_functions.set(house,'bid_mode','NONE')
return bid_quantity, bid_price, status
elif 'trans' in control_type:
# Non-bid region size between cooling and heating [F]
epsilon = 2
bid_price = transactive_price(house, T_curr, T_c_set, T_h_set, mean_p, var_p, epsilon)
if T_curr > T_c_set - (T_c_set - T_h_set)/2 + epsilon/2: #above T_c_zero
bid_quantity = hvac_q
gridlabd_functions.set(house,'bid_mode','COOL')
elif T_curr < T_h_set + (T_c_set - T_h_set)/2 - epsilon/2: #below T_h_zero
bid_quantity = heat_q
gridlabd_functions.set(house,'bid_mode','HEAT')
else:
bid_quantity = 0
gridlabd_functions.set(house,'bid_mode','NONE')
return bid_quantity, bid_price, status
else:
print('Bid reserve price could not be calculated')
return 0,0,0
