def addPV(self, area): self.hasPV = True self.pvArea = area self.pvEfficiency = random.randint(external_inputs.PVEfficiencyMin, external_inputs.PVEfficiencyMax) self.pvAzimuth = profilegentools.gaussMinMax(external_inputs.PVAzimuthMean, external_inputs.PVAzimuthSigma) if(self.pvAzimuth < 0): self.pvAzimuth = self.pvAzimuth + 360 self.pvElevation = profilegentools.gaussMinMax(external_inputs.PVAngleMean, external_inputs.PVAngleSigma)
def __init__(self, age):
self.generate(age)
self.generateWorkdays(0)
self.WeekendWakeUp_Avg = profilegentools.gaussMinMax(8.5 * 60, 1 * 60)
self.WeekendActivities = 0.7 - (0.03 * (age - 65))
self.WorkdayBedTime_Avg = profilegentools.gaussMinMax(
(23 - (age - 65) * 0.15) * 60, 30)
self.WeekendBedTime_Avg = profilegentools.gaussMinMax(
(23 - (age - 65) * 0.15) * 60, 30)
def __init__(self, age):
self.generate(age)
self.WorkdayArrival_Avg = self.WorkdayLeave_Avg + profilegentools.gaussMinMax(
7 * 60, 30)
if (age < 16):
self.WorkdayBedTime_Avg = profilegentools.gaussMinMax(
(23 - (16 - age) * 0.25) * 60, 30)
self.WeekendBedTime_Avg = profilegentools.gaussMinMax(
(23 - (16 - age) * 0.25) * 60, 30)
self.WorkdaySport_Avg = profilegentools.gaussMinMax(19 * 60, 1 * 60)
def generate(self, consumption):
self.Runtime = profilegentools.gaussMinMax(15, 5)
self.Offtime = profilegentools.gaussMinMax(40, 10)
self.Consumption = consumption
self.State = 0
self.RuntimeCycle = self.Runtime
self.OfftimeCycle = self.Offtime
self.CycleProgress = random.randint(0, self.Runtime + self.Offtime)
if (self.CycleProgress < (self.Runtime + self.Offtime)):
self.State = 1
def __init__(self):
self.generate()
self.ConsumptionYearly = profilegentools.gaussMinMax(external_inputs.yearlyConsumption,
400) * external_inputs.consumptionFactor # kWh http://www.nibud.nl/uitgaven/huishouden/gas-elektriciteit-en-water.html
age = random.triangular(65, 85, 70)
self.Persons = [persons.PersonRetired(age)]
if (random.randint(1, 2) == 1):
self.Fridges = [
devices.DeviceFridge(random.randint(external_inputs.ConsumptionFridgeBigMin, external_inputs.ConsumptionFridgeBigMax))]
else:
self.Fridges = [devices.DeviceFridge(
random.randint(external_inputs.ConsumptionFridgeSmallMin, external_inputs.ConsumptionFridgeSmallMax)),
devices.DeviceFridge(
random.randint(external_inputs.ConsumptionFridgeSmallMin, external_inputs.ConsumptionFridgeSmallMax))]
self.hasDishwasher = random.randint(0, 5) < 3 # 40%
# Determine washing days
self.generateWashingdays(random.randint(2, 3))
# Dermine Dishwasher times
if self.hasDishwasher:
self.generateDishwashdays(3)
def __init__(self, parttime=False, jobless=False):
self.generate()
# http://www.cbs.nl/nl-NL/menu/themas/bevolking/faq/specifiek/faq-hoeveel-kinderen.htm
self.ConsumptionYearly = profilegentools.gaussMinMax(external_inputs.yearlyConsumption + (700 * external_inputs.numKids), 500 + (
external_inputs.numKids * 100)) * external_inputs.consumptionFactor # kWh http://www.nibud.nl/uitgaven/huishouden/gas-elektriciteit-en-water.html
ageParents = random.randint(40, 55)
if parttime == True:
self.Persons = [persons.PersonParttimeWorker(ageParents)]
elif jobless == True:
self.Persons = [persons.PersonJobless(ageParents)]
else:
self.Persons = [persons.PersonWorker(ageParents)]
if not jobless:
# To make life easy, only one persons.Person will use the electric vehicle, so only the main persons.Person will receive a driving distance
self.Persons[0].setDistanceToWork(external_inputs.distancetoWork)
# now add the kids
for i in range(0, external_inputs.numKids):
self.Persons.append(persons.PersonStudent(random.randint(ageParents - 3, ageParents + 3) - 30))
self.Fridges = [
devices.DeviceFridge(random.randint(external_inputs.ConsumptionFridgeSmallMin, external_inputs.ConsumptionFridgeSmallMax)),
devices.DeviceFridge(random.randint(external_inputs.ConsumptionFridgeSmallMin, external_inputs.ConsumptionFridgeSmallMax))]
self.hasDishwasher = random.randint(0, 5) < 4 # 60%
# Determine washing days
self.generateWashingdays(min(5 + external_inputs.numKids, 7))
# Dermine Dishwasher times
if self.hasDishwasher:
self.generateDishwashdays(min(5 + external_inputs.numKids, 7))
def __init__(self, parttime=False, jobless=False):
self.generate()
self.ConsumptionYearly = profilegentools.gaussMinMax(external_inputs.yearlyConsumption,
700) * external_inputs.consumptionFactor # kWh http://www.nibud.nl/uitgaven/huishouden/gas-elektriciteit-en-water.html
assert (parttime == False or jobless == False) # ONLY one van be active
age = random.randint(26, 65)
if parttime:
self.Persons = [persons.PersonWorker(age), persons.PersonParttimeWorker(age)]
elif jobless:
self.Persons = [persons.PersonWorker(age), persons.PersonJobless(age)]
else:
self.Persons = [persons.PersonWorker(age), persons.PersonWorker(age)]
# To make life easy, only one persons.Person will use the electric vehicle, so only the main persons.Person will receive a driving distance
self.Persons[0].setDistanceToWork(external_inputs.distancetoWork)
if (random.randint(1, 2) == 1):
self.Fridges = [
devices.DeviceFridge(random.randint(external_inputs.ConsumptionFridgeBigMin, external_inputs.ConsumptionFridgeBigMax))]
else:
self.Fridges = [devices.DeviceFridge(
random.randint(external_inputs.ConsumptionFridgeSmallMin, external_inputs.ConsumptionFridgeSmallMax)),
devices.DeviceFridge(
random.randint(external_inputs.ConsumptionFridgeSmallMin,external_inputs.ConsumptionFridgeSmallMax))]
self.hasDishwasher = random.randint(0, 5) < 2 # 40%
# Determine washing days
self.generateWashingdays(random.randint(3, 4))
# Dermine Dishwasher times
if self.hasDishwasher:
self.generateDishwashdays(3)
def __init__(self):
self.generate()
self.ConsumptionYearly = profilegentools.gaussMinMax(external_inputs.yearlyConsumption,
400) * external_inputs.consumptionFactor # kWh http://www.nibud.nl/uitgaven/huishouden/gas-elektriciteit-en-water.html
self.Persons = [persons.PersonParttimeWorker(random.randint(26, 65))]
# For information about commuters, see this:
# http://www.kimnet.nl/publicatie/mobiliteitsbalans-2013
# Approx 50% uses the car to commute, which is our interrest as this part can be replaced by (PH)EV
# http://www.cbs.nl/NR/rdonlyres/13516DAC-36E1-47B7-9918-2364EF7D0B48/0/2011k2v4p34art.pdf
# 3 out of 5 working people don't work in town. Fair to assume that these people commute by car
# Average commute distance is not too clear from multiple sources, such as the once above. Something around 20km seems to be average in most sources
# However 30 is also mentioned: http://www.nederlandheeftwerk.nl/index.php/cms_categorie/58707/bb/1/id/58707
# Depends also on the region and work in vicinity.
if (random.randint(1, 2) == 1):
self.Fridges = [
devices.DeviceFridge(random.randint(external_inputs.ConsumptionFridgeBigMin, external_inputs.ConsumptionFridgeBigMax))]
else:
self.Fridges = [devices.DeviceFridge(
random.randint(external_inputs.ConsumptionFridgeSmallMin, external_inputs.ConsumptionFridgeSmallMax)),
devices.DeviceFridge(
random.randint(external_inputs.ConsumptionFridgeSmallMin, external_inputs.ConsumptionFridgeSmallMax))]
# We synchronize the dishwasher and dryer based on the annual consumption. Furthermore, this also influences the number of washes.
self.hasDishwasher = random.randint(0, 5) == 0 # 20%
# Determine washing days
self.generateWashingdays(random.randint(2, 3))
# Dermine Dishwasher times
if self.hasDishwasher:
self.generateDishwashdays(3)
def generate(self, age):
# Variates could also use a gauss distribution, some persons are more predictable than others ;)
self.Age = age
# Routine of people
# 7*60= 420 min --> mean is 420/60= 7:00 wake up with 1,5h deviation
self.WorkdayWakeUp_Avg = profilegentools.gaussMinMax(7 * 60, 1.5 * 60)
self.WorkdayWakeUp_Variate = 10
self.WorkdayLeave_Avg = self.WorkdayWakeUp_Avg + profilegentools.gaussMinMax(
45, 15)
self.WorkdayLeave_Variate = 10
self.WorkdayArrival_Avg = self.WorkdayLeave_Avg + profilegentools.gaussMinMax(
8.5 * 60, 30)
self.WorkdayArrival_Variate = 15
self.WorkdaySport_Avg = self.WorkdayArrival_Avg + profilegentools.gaussMinMax(
2.5 * 60, 2 * 60)
self.WorkdaySport_Variate = 15
self.WorkdaySportDuration_Avg = profilegentools.gaussMinMax(
1.5 * 60, 30)
self.WorkdaySportDuration_Variate = 10
self.WorkdayBedTime_Avg = self.WorkdayWakeUp_Avg + profilegentools.gaussMinMax(
15.5 * 60, 30)
self.WorkdayBedTime_Variate = 15
self.WorkdayActivities = random.randint(
external_inputs.personWeekdayActivityChanceMin,
external_inputs.personWeekdayActivityChanceMax
) / 100 # Chance to conduct random activities
self.WeekendWakeUp_Avg = profilegentools.gaussMinMax(9 * 60, 2 * 60)
self.WeekendWakeUp_Variate = 20
self.WeekendSport_Avg = profilegentools.gaussMinMax(14 * 60, 5 * 60)
self.WeekendSport_Variate = 60
self.WeekendSportDuration_Avg = profilegentools.gaussMinMax(
1.5 * 60, 30)
self.WeekendSportDuration_Variate = 30
self.WeekendBedTime_Avg = profilegentools.gaussMinMax(23 * 60, 30)
self.WeekendBedTime_Variate = 10
self.WeekendActivities = random.randint(
external_inputs.personWeekendActivityChanceMin,
external_inputs.personWeekendActivityChanceMax) / 100
# For a new deepcopy, the following values should be regenerated
self.WorkdaySportday = 1 + random.randint(1, 5)
self.WeekendSportday = 6 * random.randint(0, 1)
self.Workdays = range(1, 6)
self.DistanceToWork = 0
self.CookingTime = self.WorkdayArrival_Avg + 30
self.showerMorning = True
self.showerDays = list(range(0, 7))
self.showerDuration = profilegentools.gaussMinMax(8, 3)
# Generate Heat parameters
self.generateHeatParams()
def generate(self):
# The Yearly consumption is the normal consumption of domestic appliances as found for years in households. This excludes:
# (PH)EV, Heat Pump, PV
self.ConsumptionYearly = profilegentools.gaussMinMax(external_inputs.yearlyConsumption, 500) # kWh
# According to http://www.energie-nederland.nl/wp-content/uploads/2013/04/EnergieTrends2014.pdf, this is the distribution for devices we are interested in:
# yearly energy consumption
self.ConsumptionShare = {"Electronics": profilegentools.gaussMinMax(17, 3),
"Lighting": profilegentools.gaussMinMax(6, 2),
"Standby": profilegentools.gaussMinMax(35, 6)}
self.Persons = []
self.Consumption = {"Total": [],
"Other": [],
"Inductive": [],
"Fridges": [],
"Electronics": [],
"Lighting": [],
"Standby": []}
self.consumptionFactor = {"Other": [],
"Inductive": [],
"Fridges": [],
"Electronics": [],
"Lighting": [],
"Standby": []}
self.HeatGain = {"PersonGain": [],
"DeviceGain": [],
"SolarGain": [],
"VentFlow": [],
"Total": []}
self.HeatDemand = {"DHWDemand": [],
"Total": []}
# Heat gain factors from devices
self.HeatGainShare = {"Other": 0.3,
"Fridges": 0.5,
"Electronics": 1.0,
"Lighting": 0.8,
"Standby": 1.0}
self.ReactiveConsumption = {"Total": [],
"Other": [],
"Inductive": [],
"Fridges": [],
"Electronics": [],
"Lighting": [],
"Standby": []}
self.ReactiveFactor = {"Other": 1,
"Inductive": (random.randint(70, 90) / 100),
"Fridges": (random.randint(50, 65) / 100),
"Electronics": -(random.randint(99, 100) / 100),
"Lighting": -(random.randint(99, 100) / 100),
"Standby": -(random.randint(75, 85) / 100)}
self.PVProfile = []
self.Occupancy = []
self.hasDishwasher = False
self.hasInductionCooking = random.randint(1, 10) < 4
self.hasEV = False
self.hasHP = False
self.hasCHP = False
self.hasFloorHeating = True
self.numOfWashes = 0 # weekly
self.numOfDishwashes = 0 # Weekly
self.WashingDays = []
self.washingMoment = [-1] * 7
self.DishwashDays = []
self.DishwashMoment = [-1] * 7
# devices
self.Fridges = []
self.Devices = {"Kettle": devices.DeviceKettle(external_inputs.ConsumptionKettle),
"Lighting": devices.DeviceLighting(),
"Electronics": devices.DeviceElectronics(),
"Cooking": devices.DeviceCooking(),
"Ventilation": devices.DeviceVentilation(external_inputs.ConsumptionHouseVentilation),
"Ironing": devices.DeviceIroning(external_inputs.ConsumptionIron),
"Vacuumcleaner": devices.DeviceVacuumcleaner(external_inputs.ConsumptionVacuumcleaner),
"WashingMachine": devices.DeviceWashingMachine(),
"DishwashMachine": devices.DeviceDishwasher(),
"ElectricalVehicle": devices.DeviceElectricalVehicle(),
"PVPanel": devices.DeviceSolarPanel()}
self.HeatingDevices = {"PersonGain": heatdemand.PersonGain(),
"Thermostat": heatdemand.Thermostat(),
"VentFlow": heatdemand.Ventilation(),
"DHWDemand": heatdemand.DHWDemand()}
self.familyActivites = random.randint(external_inputs.familyOutingChanceMin, external_inputs.familyOutingChanceMax) / 100
