Exemple #1
0
 def dispatch(self, dt_sim_time, p_lem, alpha):
     inverter = self.name
     if (self.Q_bid > 0.0) and (self.P_bid > p_lem):
         gridlabd.set_value(inverter, 'P_Out', str(-self.Q_bid * 1000.))
         mode = 1.
     elif (self.Q_bid > 0.0) and (self.P_bid == p_lem):
         print('This HVAC is marginal; no partial implementation yet: ' +
               str(alpha))
         gridlabd.set_value(inverter, 'P_Out', str(-self.Q_bid * 1000.))
         mode = 1.
     else:
         gridlabd.set_value(inverter, 'P_Out', str(0.0))
         mode = 0.
     parameter_string = '(timedate, P_bid, Q_bid, mode, DeltaE)'  #DeltaE at beginning of period
     value_tuple = (
         dt_sim_time,
         float(self.P_bid),
         float(self.Q_bid),
         float(mode),
         float(self.DeltaE),
     )
     myfct.set_values('EV_' + self.ID + '_state_out', parameter_string,
                      value_tuple)
     self.P_bid = -100000.0
     self.Q_bid = 0.0
     return
Exemple #2
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 def dispatch(self, dt_sim_time, p_lem, alpha):
     #import pdb; pdb.set_trace()
     inverter = 'Bat_inverter_' + self.name.split('_')[-1]
     if (self.Q_buy_bid > 0.0) and (self.P_buy_bid > p_lem):
         gridlabd.set_value(inverter, 'P_Out', str(-self.Q_buy_bid * 1000.))
     elif (self.Q_buy_bid > 0.0) and (self.P_buy_bid == p_lem):
         print('This HVAC is marginal; no partial implementation yet: ' +
               str(alpha))
         gridlabd.set_value(inverter, 'P_Out', str(-self.Q_buy_bid * 1000.))
     elif (self.Q_sell_bid > 0.0) and (self.P_sell_bid < p_lem):
         gridlabd.set_value(inverter, 'P_Out', str(self.Q_sell_bid * 1000.))
     elif (self.Q_sell_bid > 0.0) and (self.P_sell_bid == p_lem):
         print('This HVAC is marginal; no partial implementation yet: ' +
               str(alpha))
         gridlabd.set_value(inverter, 'P_Out', str(self.Q_sell_bid * 1000.))
     else:
         gridlabd.set_value(inverter, 'P_Out', str(0.0))
     myfct.set_values(
         self.name + '_state_out',
         '(timedate, p_demand, p_supply, q_demand, q_supply)',
         (dt_sim_time, str(self.P_buy_bid), str(
             self.P_sell_bid), str(self.Q_buy_bid), str(self.Q_sell_bid)))
     self.P_sell_bid = 100000.0
     self.P_buy_bid = -100000.0
     self.Q_sell_bid = 0.0
     self.Q_buy_bid = 0.0
Exemple #3
0
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
Exemple #4
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
Exemple #5
0
	retail = Mfct.Market()
	retail.reset()
	retail.Pmin = 0.0
	retail.Pmax = 100.0
	retail.Pprec = prec

	#Get historical parameters from mysql database
	df_prices = mysql_functions.get_values('clearing_pq', dt_sim_time-datetime.timedelta(days=1))
	mean_p = df_prices['clearing_price'].iloc[-36:].mean() #last hour
	var_p = df_prices['clearing_price'].var()
	if math.isnan(mean_p):
		mean_p = (retail.Pmax - retail.Pmin)/2
	#print var_p
	if math.isnan(var_p) or var_p == 0.0:
		var_p = 0.10
	mysql_functions.set_values('market_prices', '(mean_price,var_price,timedate)',(float(mean_p),float(var_p),dt_sim_time-datetime.timedelta(seconds=interval),))

	###
	#Demand side
	###

	#HVAC
	df_bids_HVAC = HHfct.calc_bids_HVAC(dt_sim_time,df_house_state,retail,mean_p,var_p)
	retail = HHfct.submit_bids_HVAC(dt_sim_time,retail,df_bids_HVAC)
	print retail.D_active

	#Batteries
	df_bids_battery = HHfct.calc_bids_battery(dt_sim_time,df_battery_state,retail,mean_p,var_p)
	retail = HHfct.submit_bids_battery(dt_sim_time,retail,df_bids_battery)

	#PV
Exemple #6
0
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