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)