def make_bldg_neighbor(self, name):
bldg_powers = self.building_powers[name]
# Create neighbor
bldg = Neighbor()
bldg.name = name
bldg.maximumPower = bldg_powers[
0] # Remember loads have negative power [avg.kW]
bldg.minimumPower = bldg_powers[1] # [avg.kW]
_log.debug("{} has minPower of {} and maxPower of {}".format(
bldg.name, bldg.minimumPower, bldg.maximumPower))
# Create neighbor model
bldg_model = NeighborModel()
bldg_model.name = name + '_Model'
bldg_model.location = self.name
bldg_model.convergenceThreshold = 0.02
bldg_model.friend = True
bldg_model.transactive = True
bldg_model.costParameters = [0, 0, 0]
# This is different building to building
bldg_model.defaultPower = bldg.minimumPower / 2 # bldg_powers[2] # [avg.kW]
bldg_model.defaultVertices = [
Vertex(float("inf"), 0, bldg_model.defaultPower, True)
]
# Cross reference object & model
bldg.model = bldg_model
bldg_model.object = bldg
return bldg
def init_objects(self):
# Add meter
meter = MeterPoint()
meter.measurementType = MeasurementType.PowerReal
meter.name = 'CampusElectricityMeter'
meter.measurementUnit = MeasurementUnit.kWh
self.meterPoints.append(meter)
# Add weather forecast service
weather_service = TemperatureForecastModel(self.config_path, self)
self.informationServiceModels.append(weather_service)
# Add inelastive asset
inelastive_load = LocalAsset()
inelastive_load.name = 'InelasticBuildings' # Campus buildings that are not responsive
inelastive_load.maximumPower = 0 # Remember that a load is a negative power [kW]
inelastive_load.minimumPower = -2 * 8200 # Assume twice the average PNNL load [kW]
# Add inelastive asset model
inelastive_load_model = OpenLoopPnnlLoadPredictor(weather_service)
inelastive_load_model.name = 'InelasticBuildingsModel'
inelastive_load_model.engagementCost = [
0, 0, 0
] # Transition costs irrelevant
inelastive_load_model.defaultPower = -6000 # [kW]
inelastive_load_model.defaultVertices = [Vertex(0, 0, -6000.0, 1)]
# Cross-reference asset & asset model
inelastive_load_model.object = inelastive_load
inelastive_load.model = inelastive_load_model
# Add solar PV asset
solar_pv = SolarPvResource()
solar_pv.maximumPower = self.PV_max_kW # [avg.kW]
solar_pv.minimumPower = 0.0 # [avg.kW]
solar_pv.name = 'SolarPv'
solar_pv.description = '120 kW solar PV site on the campus'
# Add solar PV asset model
solar_pv_model = SolarPvResourceModel()
solar_pv_model.cloudFactor = 1.0 # dimensionless
solar_pv_model.engagementCost = [0, 0, 0]
solar_pv_model.name = 'SolarPvModel'
solar_pv_model.defaultPower = 0.0 # [avg.kW]
solar_pv_model.defaultVertices = [Vertex(0, 0, 30.0, True)]
solar_pv_model.costParameters = [0, 0, 0]
solar_pv_model.inject(self, power_topic=self.solar_topic)
# Cross-reference asset & asset model
solar_pv.model = solar_pv_model
solar_pv_model.object = solar_pv
# Add inelastive and solar_pv as campus' assets
self.localAssets.extend([inelastive_load, solar_pv])
# Add Market
market = Market()
market.name = 'dayAhead'
market.commitment = False
market.converged = False
market.defaultPrice = 0.04 # [$/kWh]
market.dualityGapThreshold = self.duality_gap_threshold # [0.02 = 2#]
market.initialMarketState = MarketState.Inactive
market.marketOrder = 1 # This is first and only market
market.intervalsToClear = 1 # Only one interval at a time
market.futureHorizon = timedelta(
hours=24) # Projects 24 hourly future intervals
market.intervalDuration = timedelta(
hours=1) # [h] Intervals are 1 h long
market.marketClearingInterval = timedelta(hours=1) # [h]
market.marketClearingTime = Timer.get_cur_time().replace(
hour=0, minute=0, second=0,
microsecond=0) # Aligns with top of hour
market.nextMarketClearingTime = market.marketClearingTime + timedelta(
hours=1)
self.markets.append(market)
# City object
city = Neighbor()
city.name = 'CoR'
city.description = 'City of Richland (COR) electricity supplier node'
city.maximumPower = 20000 # Remember loads have negative power [avg.kW]
city.minimumPower = 0 # [avg.kW]
city.lossFactor = self.city_loss_factor
# City model
city_model = NeighborModel()
city_model.name = 'CoR_Model'
city_model.location = self.name
city_model.transactive = True
city_model.defaultPower = 10000 # [avg.kW]
city_model.defaultVertices = [
Vertex(0.046, 160, 0, True),
Vertex(0.048,
160 + city.maximumPower * (0.046 + 0.5 * (0.048 - 0.046)),
city.maximumPower, True)
]
city_model.costParameters = [0, 0, 0]
city_model.demand_threshold_coef = self.demand_threshold_coef
city_model.demandThreshold = self.monthly_peak_power
city_model.inject(self,
system_loss_topic=self.system_loss_topic,
dc_threshold_topic=self.dc_threshold_topic)
# Cross-reference object & model
city_model.object = city
city.model = city_model
self.city = city
# Add city as campus' neighbor
self.neighbors.append(city)
# Add buildings
for bldg_name in self.building_names:
bldg_neighbor = self.make_bldg_neighbor(bldg_name)
self.neighbors.append(bldg_neighbor)