Costing initiated #5
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@ -289,6 +289,18 @@ class NonPvGenerationSystem(GenerationSystem):
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self.distribution_systems] if self.distribution_systems is not None else None
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_energy_storage_systems = [_energy_storage_system.to_dictionary() for _energy_storage_system in
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self.energy_storage_systems] if self.energy_storage_systems is not None else None
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_heat_output_curve = self.heat_output_curve.to_dictionary() if (
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self.heat_output_curve is not None) else None
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_heat_fuel_consumption_curve = self.heat_fuel_consumption_curve.to_dictionary() if (
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self.heat_fuel_consumption_curve is not None) else None
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_heat_efficiency_curve = self.heat_efficiency_curve.to_dictionary() if (
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self.heat_efficiency_curve is not None) else None
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_cooling_output_curve = self.cooling_output_curve.to_dictionary() if (
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self.cooling_output_curve is not None) else None
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_cooling_fuel_consumption_curve = self.cooling_fuel_consumption_curve.to_dictionary() if (
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self.cooling_fuel_consumption_curve is not None) else None
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_cooling_efficiency_curve = self.cooling_efficiency_curve.to_dictionary() if (
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self.cooling_efficiency_curve is not None) else None
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content = {
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'Energy Generation component':
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@ -318,7 +330,7 @@ class NonPvGenerationSystem(GenerationSystem):
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'minimum cooling supply temperature [Celsius]': self.minimum_cooling_supply_temperature,
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'heat output curve': self.heat_output_curve,
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'heat fuel consumption curve': self.heat_fuel_consumption_curve,
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'heat efficiency curve': self.heat_efficiency_curve,
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'heat efficiency curve': _heat_efficiency_curve,
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'cooling output curve': self.cooling_output_curve,
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'cooling fuel consumption curve': self.cooling_fuel_consumption_curve,
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'cooling efficiency curve': self.cooling_efficiency_curve,
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@ -24,13 +24,13 @@ class PerformanceCurves:
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def curve_type(self):
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"""
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The type of the fit function from the following
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Linear =>>> y = a*x + b
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Linear =>>> y = a + b*x
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Exponential =>>> y = a*(b**x)
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Polynomial =>>> y = a*(x**2) + b*x + c
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Second degree polynomial =>>> y = a + b*x + c*(x**2)
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Power =>>> y = a*(x**b)
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Second degree multivariable =>>> y = a*(x**2) + b*x + c*x*z + d*z + e*(z**2) + f
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Bi-Quadratic =>>> y = a + b*x + c*(x**2) + d*z + e*(z**2) + f*x*z
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Get the type of function from ['linear', 'exponential', 'polynomial', 'power', 'second degree multivariable']
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Get the type of function from ['linear', 'exponential', 'second degree polynomial', 'power', 'bi-quadratic']
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:return: string
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"""
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return self._curve_type
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@ -132,7 +132,7 @@
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</fuel>
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<fuel fuel_type="Gas">
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<fixed_monthly cost_unit="currency/month"> 17.71 </fixed_monthly>
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<variable cost_unit="currency/kWh"> 0.0640 </variable>
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<variable cost_unit="currency/m3"> 0.4 </variable>
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<density density_unit="kg/m3"> 0.777 </density>
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<lower_heating_value lhv_unit="MJ/kg"> 47.1 </lower_heating_value>
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</fuel>
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@ -493,7 +493,7 @@
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<heat_output_curve/>
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<heat_fuel_consumption_curve/>
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<heat_efficiency_curve>
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<curve_type>second degree multivariable function</curve_type>
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<curve_type>bi-quadratic</curve_type>
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<dependant_variable>COP</dependant_variable>
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<parameters>source_temperature</parameters>
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<parameters>supply_temperature</parameters>
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@ -538,7 +538,7 @@
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<heat_output_curve/>
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<heat_fuel_consumption_curve/>
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<heat_efficiency_curve>
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<curve_type>second degree multivariable function</curve_type>
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<curve_type>bi-quadratic</curve_type>
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<dependant_variable>COP</dependant_variable>
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<parameters>source_temperature</parameters>
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<parameters>supply_temperature</parameters>
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@ -583,7 +583,7 @@
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<heat_output_curve/>
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<heat_fuel_consumption_curve/>
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<heat_efficiency_curve>
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<curve_type>second degree multivariable function</curve_type>
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<curve_type>bi-quadratic</curve_type>
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<dependant_variable>COP</dependant_variable>
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<parameters>source_temperature</parameters>
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<parameters>supply_temperature</parameters>
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@ -690,7 +690,7 @@
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<nominal_heat_output/>
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<minimum_heat_output/>
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<maximum_heat_output/>
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<heat_efficiency>3</heat_efficiency>
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<heat_efficiency>2</heat_efficiency>
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<reversible>True</reversible>
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<fuel_type>electricity</fuel_type>
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<source_medium>Air</source_medium>
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@ -709,10 +709,22 @@
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<minimum_cooling_supply_temperature/>
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<heat_output_curve/>
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<heat_fuel_consumption_curve/>
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<heat_efficiency_curve/>
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<heat_efficiency_curve>
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<curve_type>bi-quadratic</curve_type>
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<dependant_variable>COP</dependant_variable>
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<parameters>source_temperature</parameters>
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<parameters>supply_temperature</parameters>
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<coefficients a="0.132733" b="0.012322" c="0.000032" d="-0.011109" e="-0.000125" f="-0.000123"/>
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</heat_efficiency_curve>
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<cooling_output_curve/>
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<cooling_fuel_consumption_curve/>
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<cooling_efficiency_curve/>
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<cooling_efficiency_curve>
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<curve_type>bi-quadratic</curve_type>
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<dependant_variable>COP</dependant_variable>
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<parameters>source_temperature</parameters>
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<parameters>supply_temperature</parameters>
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<coefficients a="0.951894" b="-0.010518" c="0.000126" d="-0.003399" e="0.000183" f="-0.000206"/>
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</cooling_efficiency_curve>
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<distribution_systems/>
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<energy_storage_systems>
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<storage_id>6</storage_id>
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@ -910,7 +922,13 @@
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<minimum_cooling_supply_temperature/>
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<heat_output_curve/>
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<heat_fuel_consumption_curve/>
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<heat_efficiency_curve/>
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<heat_efficiency_curve>
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<curve_type>bi-quadratic</curve_type>
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<dependant_variable>COP</dependant_variable>
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<parameters>source_temperature</parameters>
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<parameters>supply_temperature</parameters>
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<coefficients a="-0.000277" b="0.019639" c="0.000004" d="0.012190" e="-0.00010" f="-0.000277"/>
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</heat_efficiency_curve>
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<cooling_output_curve/>
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<cooling_fuel_consumption_curve/>
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<cooling_efficiency_curve/>
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@ -66,7 +66,7 @@ class SimplifiedRadiosityAlgorithm:
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else:
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i = (total_days + day - 1) * 24 + hour - 1
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representative_building = self._city.buildings[0]
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_global = representative_building.global_horizontal[cte.HOUR][i] * cte.WATTS_HOUR_TO_JULES
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_global = representative_building.diffuse[cte.HOUR][i] * cte.WATTS_HOUR_TO_JULES
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_beam = representative_building.beam[cte.HOUR][i] * cte.WATTS_HOUR_TO_JULES
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content += f'{day} {month} {hour} {_global} {_beam}\n'
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with open(file, 'w', encoding='utf-8') as file:
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@ -34,7 +34,7 @@ class SimplifiedRadiosityAlgorithm:
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for key in self._results:
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_irradiance = {}
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header_name = key.split(':')
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result = [x / cte.WATTS_HOUR_TO_JULES for x in self._results[key]]
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result = [x for x in self._results[key]]
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city_object_name = header_name[1]
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building = self._city.city_object(city_object_name)
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surface_id = header_name[2]
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@ -1,7 +0,0 @@
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{
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"type": "FeatureCollection",
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"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
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"features": [
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{ "type": "Feature", "properties": { "OBJECTID_12": 142, "gml_id": "1341088", "gml_parent": "fme-gen-57964590-baa9-48a7-99b0-fa11ca012d7c", "citygml_ta": "http://www.opengis.net/citygml/building/2.0", "citygml_fe": "cityObjectMember", "citygml__1": " ", "citygml__2": " ", "gml_descri": " ", "gml_name": " ", "citygml_cr": " ", "citygml_te": " ", "externalRe": " ", "external_1": " ", "external_2": " ", "citygml_ge": " ", "citygml_re": " ", "citygml__3": " ", "citygml_ap": " ", "citygml_cl": " ", "citygml__4": " ", "citygml_fu": " ", "citygml__5": " ", "citygml_us": " ", "citygml__6": " ", "citygml_ye": " ", "citygml__7": " ", "citygml_ro": " ", "citygml__8": " ", "citygml_me": 16.095, "citygml__9": "#m", "citygml_st": " ", "citygml_10": " ", "citygml_11": " ", "citygml_12": " ", "citygml_13": " ", "citygml_14": " ", "citygml_ou": " ", "citygml_in": " ", "citygml_bo": " ", "citygml_le": " ", "citygml_15": " ", "citygml_co": " ", "citygml_ad": " ", "Volume": "2218.190", "parcelle": " ", "OBJECTID": 7562, "gml_id_1": "66b4f621-39d0-4f51-a8e0-1fb7fbf114f8", "gml_pare_1": "1341088", "citygml_16": "http://www.opengis.net/citygml/building/2.0", "citygml_17": "boundedBy", "citygml_18": " ", "citygml_19": " ", "gml_desc_1": " ", "gml_name_1": " ", "citygml_20": " ", "citygml_21": " ", "external_3": " ", "external_4": " ", "external_5": " ", "citygml_22": " ", "citygml_23": " ", "citygml_24": " ", "citygml_25": " ", "citygml_26": " ", "citygml_op": " ", "Area": "161.344", "FID_": 0, "Join_Count": 2, "TARGET_FID": 7567, "gml_id_12": "1341088", "gml_pare_2": "fme-gen-57964590-baa9-48a7-99b0-fa11ca012d7c", "citygml_27": "http://www.opengis.net/citygml/building/2.0", "citygml_28": "cityObjectMember", "citygml_29": " ", "citygml_30": " ", "gml_desc_2": " ", "gml_name_2": " ", "citygml_31": " ", "citygml_32": " ", "external_6": " ", "external_7": " ", "external_8": " ", "citygml_33": " ", "citygml_34": " ", "citygml_35": " ", "citygml_36": " ", "citygml_37": " ", "citygml_38": " ", "citygml_39": " ", "citygml_40": " ", "citygml_41": " ", "citygml_42": " ", "citygml_43": " ", "citygml_44": " ", "citygml_45": " ", "citygml_46": " ", "citygml_47": 16.095, "citygml_48": "#m", "citygml_49": " ", "citygml_50": " ", "citygml_51": " ", "citygml_52": " ", "citygml_53": " ", "citygml_54": " ", "citygml_55": " ", "citygml_56": " ", "citygml_57": " ", "citygml_58": " ", "citygml_59": " ", "citygml_60": " ", "citygml_61": " ", "Volume_1": "2218.190", "Field": 0, "Field1": 0, "OBJECTID_1": 7562, "gml_id_12_": "66b4f621-39d0-4f51-a8e0-1fb7fbf114f8", "gml_pare_3": "1341088", "citygml_62": "http://www.opengis.net/citygml/building/2.0", "citygml_63": "boundedBy", "citygml_64": " ", "citygml_65": " ", "gml_desc_3": " ", "gml_name_3": " ", "citygml_66": " ", "citygml_67": " ", "external_9": " ", "externa_10": " ", "externa_11": " ", "citygml_68": " ", "citygml_69": " ", "citygml_70": " ", "citygml_71": " ", "citygml_72": " ", "citygml_73": " ", "Area_1": "161.344", "cityGML_hi": 0, "Z_Min": 38.4478, "Z_Max": 54.543, "Shape_Leng": 69.646646889099998, "ID_UEV": "01036772", "CIVIQUE_DE": " 1238", "CIVIQUE_FI": " 1238", "NOM_RUE": "rue Bishop (MTL)", "MUNICIPALI": "50", "ETAGE_HORS": 3, "NOMBRE_LOG": 1, "ANNEE_CONS": 1885, "CODE_UTILI": "5010", "LIBELLE_UT": "Immeuble commercial", "CATEGORIE_": "Régulier", "MATRICULE8": "9839-85-7864-5-000-0000", "SUPERFICIE": 281, "SUPERFIC_1": 412, "NO_ARROND_": "REM19", "Shape_Le_1": 0.00096806745949799995, "Shape_Ar_1": 3.2334086871599998e-08, "Z_Min_1": null, "Z_Max_1": null, "Shape_Length": 69.646646889118685, "Shape_Area": 160.22851198241219 }, "geometry": { "type": "Polygon", "coordinates": [ [ [ -73.575671624082659, 45.496112824080043 ], [ -73.575681777019426, 45.496117685511202 ], [ -73.575687462912001, 45.496111805760563 ], [ -73.575689793092337, 45.496112920023506 ], [ -73.575780754475915, 45.496018888973346 ], [ -73.575792190109638, 45.496007066430288 ], [ -73.575812608138278, 45.495985960529921 ], [ -73.575776823258522, 45.49596883324228 ], [ -73.575802901600994, 45.495941883598753 ], [ -73.57583958499842, 45.495903966804626 ], [ -73.575799779972698, 45.495884916526173 ], [ -73.57578777576957, 45.495897319847018 ], [ -73.575775771561226, 45.495909723166633 ], [ -73.575763096560905, 45.495922833307645 ], [ -73.575711834246746, 45.495975814136678 ], [ -73.575705164522105, 45.495982711364753 ], [ -73.575614190275871, 45.496076742363833 ], [ -73.575622832419342, 45.496080875926495 ], [ -73.575614897715738, 45.496089078760853 ], [ -73.575634678641578, 45.496098550023554 ], [ -73.575653153643159, 45.496107392256711 ], [ -73.575657120993768, 45.496103290838278 ], [ -73.575661088343765, 45.496099189419709 ], [ -73.57566769477971, 45.496102343497014 ], [ -73.575662008886027, 45.496108223246658 ], [ -73.575671624082659, 45.496112824080043 ] ] ] } }
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||||
]
|
||||
}
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@ -1,7 +0,0 @@
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{
|
||||
"type": "FeatureCollection",
|
||||
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
|
||||
"features": [
|
||||
{ "type": "Feature", "properties": { "OBJECTID_12": 78, "gml_id": "1341084", "gml_parent": "fme-gen-57964590-baa9-48a7-99b0-fa11ca012d7c", "citygml_ta": "http://www.opengis.net/citygml/building/2.0", "citygml_fe": "cityObjectMember", "citygml__1": " ", "citygml__2": " ", "gml_descri": " ", "gml_name": " ", "citygml_cr": " ", "citygml_te": " ", "externalRe": " ", "external_1": " ", "external_2": " ", "citygml_ge": " ", "citygml_re": " ", "citygml__3": " ", "citygml_ap": " ", "citygml_cl": " ", "citygml__4": " ", "citygml_fu": " ", "citygml__5": " ", "citygml_us": " ", "citygml__6": " ", "citygml_ye": " ", "citygml__7": " ", "citygml_ro": " ", "citygml__8": " ", "citygml_me": 28.164, "citygml__9": "#m", "citygml_st": " ", "citygml_10": " ", "citygml_11": " ", "citygml_12": " ", "citygml_13": " ", "citygml_14": " ", "citygml_ou": " ", "citygml_in": " ", "citygml_bo": " ", "citygml_le": " ", "citygml_15": " ", "citygml_co": " ", "citygml_ad": " ", "Volume": "20172.450", "parcelle": " ", "OBJECTID": 7115, "gml_id_1": "25a2efa0-4d04-4eeb-b04c-7ceb338b062c", "gml_pare_1": "1341084", "citygml_16": "http://www.opengis.net/citygml/building/2.0", "citygml_17": "boundedBy", "citygml_18": " ", "citygml_19": " ", "gml_desc_1": " ", "gml_name_1": " ", "citygml_20": " ", "citygml_21": " ", "external_3": " ", "external_4": " ", "external_5": " ", "citygml_22": " ", "citygml_23": " ", "citygml_24": " ", "citygml_25": " ", "citygml_26": " ", "citygml_op": " ", "Area": "716.259", "FID_": 0, "Join_Count": 3, "TARGET_FID": 7120, "gml_id_12": "1341084", "gml_pare_2": "fme-gen-57964590-baa9-48a7-99b0-fa11ca012d7c", "citygml_27": "http://www.opengis.net/citygml/building/2.0", "citygml_28": "cityObjectMember", "citygml_29": " ", "citygml_30": " ", "gml_desc_2": " ", "gml_name_2": " ", "citygml_31": " ", "citygml_32": " ", "external_6": " ", "external_7": " ", "external_8": " ", "citygml_33": " ", "citygml_34": " ", "citygml_35": " ", "citygml_36": " ", "citygml_37": " ", "citygml_38": " ", "citygml_39": " ", "citygml_40": " ", "citygml_41": " ", "citygml_42": " ", "citygml_43": " ", "citygml_44": " ", "citygml_45": " ", "citygml_46": " ", "citygml_47": 28.164, "citygml_48": "#m", "citygml_49": " ", "citygml_50": " ", "citygml_51": " ", "citygml_52": " ", "citygml_53": " ", "citygml_54": " ", "citygml_55": " ", "citygml_56": " ", "citygml_57": " ", "citygml_58": " ", "citygml_59": " ", "citygml_60": " ", "citygml_61": " ", "Volume_1": "20172.450", "Field": 0, "Field1": 0, "OBJECTID_1": 7115, "gml_id_12_": "25a2efa0-4d04-4eeb-b04c-7ceb338b062c", "gml_pare_3": "1341084", "citygml_62": "http://www.opengis.net/citygml/building/2.0", "citygml_63": "boundedBy", "citygml_64": " ", "citygml_65": " ", "gml_desc_3": " ", "gml_name_3": " ", "citygml_66": " ", "citygml_67": " ", "external_9": " ", "externa_10": " ", "externa_11": " ", "citygml_68": " ", "citygml_69": " ", "citygml_70": " ", "citygml_71": " ", "citygml_72": " ", "citygml_73": " ", "Area_1": "716.259", "cityGML_hi": 0, "Z_Min": 39.2444, "Z_Max": 67.408, "Shape_Leng": 140.36783883300001, "ID_UEV": "01002600", "CIVIQUE_DE": " 1420", "CIVIQUE_FI": " 1420", "NOM_RUE": "rue Sainte-Catherine Ouest (MTL+WMT)", "MUNICIPALI": "50", "ETAGE_HORS": 4, "NOMBRE_LOG": 4, "ANNEE_CONS": 1914, "CODE_UTILI": "6000", "LIBELLE_UT": "Immeuble à bureaux", "CATEGORIE_": "Régulier", "MATRICULE8": "9839-85-4994-3-000-0000", "SUPERFICIE": 803, "SUPERFIC_1": 2953, "NO_ARROND_": "REM19", "Shape_Le_1": 0.0013155280635399999, "Shape_Ar_1": 9.24688109061e-08, "Z_Min_1": null, "Z_Max_1": null, "Shape_Length": 140.3678388326679, "Shape_Area": 716.25939654725767 }, "geometry": { "type": "Polygon", "coordinates": [ [ [ -73.576326707327183, 45.496116905446513 ], [ -73.576250734313831, 45.496195431606957 ], [ -73.57635494025277, 45.49624529435664 ], [ -73.57640388728268, 45.496268720567464 ], [ -73.576411543664449, 45.496272386810624 ], [ -73.576562645953913, 45.496116207640782 ], [ -73.576415293070468, 45.496045695530078 ], [ -73.576420653070528, 45.496040157901724 ], [ -73.576426013069508, 45.496034620273157 ], [ -73.576390874544217, 45.496017807691075 ], [ -73.576355736039815, 45.496000995098171 ], [ -73.576350382434597, 45.496006532719178 ], [ -73.576345028828328, 45.496012070339987 ], [ -73.576230158246304, 45.495957103581226 ], [ -73.576199840227886, 45.495942591324486 ], [ -73.57616952222503, 45.495928079059674 ], [ -73.57601853434798, 45.496084140658738 ], [ -73.576148538438346, 45.496146359284836 ], [ -73.576177140896519, 45.496160035843573 ], [ -73.576252998979967, 45.496081635786481 ], [ -73.576326707327183, 45.496116905446513 ] ] ] } }
|
||||
]
|
||||
}
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|
||||
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|
||||
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|
||||
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|
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
}
|
||||
}
|
||||
]
|
||||
}
|
|
@ -1,311 +0,0 @@
|
|||
{
|
||||
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|
||||
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||||
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||||
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||||
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|
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}
|
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}
|
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]
|
||||
}
|
21
main.py
21
main.py
|
@ -8,7 +8,6 @@ from hub.imports.construction_factory import ConstructionFactory
|
|||
from hub.imports.usage_factory import UsageFactory
|
||||
from hub.imports.weather_factory import WeatherFactory
|
||||
from hub.imports.results_factory import ResultFactory
|
||||
from hub.exports.exports_factory import ExportsFactory
|
||||
from scripts.energy_system_analysis_report import EnergySystemAnalysisReport
|
||||
from scripts import random_assignation
|
||||
from hub.imports.energy_systems_factory import EnergySystemsFactory
|
||||
|
@ -17,7 +16,7 @@ from scripts.energy_system_retrofit_results import system_results, new_system_re
|
|||
from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
|
||||
from scripts.costs.cost import Cost
|
||||
from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV
|
||||
|
||||
from hub.exports.exports_factory import ExportsFactory
|
||||
# Specify the GeoJSON file path
|
||||
geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.0001)
|
||||
file_path = (Path(__file__).parent.parent / 'input_files' / f'{geojson_file}')
|
||||
|
@ -32,6 +31,7 @@ city = GeometryFactory('geojson',
|
|||
function_to_hub=Dictionaries().montreal_function_to_hub_function).city
|
||||
# Enrich city data
|
||||
ConstructionFactory('nrcan', city).enrich()
|
||||
|
||||
UsageFactory('nrcan', city).enrich()
|
||||
WeatherFactory('epw', city).enrich()
|
||||
ExportsFactory('sra', city, output_path).export()
|
||||
|
@ -39,19 +39,24 @@ sra_path = (output_path / f'{city.name}_sra.xml').resolve()
|
|||
subprocess.run(['sra', str(sra_path)])
|
||||
ResultFactory('sra', city, output_path).enrich()
|
||||
energy_plus_workflow(city)
|
||||
ExportsFactory('obj', city, output_path).export()
|
||||
random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
|
||||
EnergySystemsFactory('montreal_custom', city).enrich()
|
||||
SystemSizing(city.buildings).montreal_custom()
|
||||
current_system = system_results(city.buildings)
|
||||
current_system = new_system_results(city.buildings)
|
||||
random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
|
||||
EnergySystemsFactory('montreal_future', city).enrich()
|
||||
for building in city.buildings:
|
||||
EnergySystemsSimulationFactory('archetype1', building=building, output_path=output_path).enrich()
|
||||
new_system = new_system_results(city.buildings)
|
||||
# EnergySystemAnalysisReport(city, output_path).create_report(current_system, new_system)
|
||||
# for building in city.buildings:
|
||||
# costs = Cost(building=building, retrofit_scenario=SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV).life_cycle
|
||||
# costs.loc['global_operational_costs', f'Scenario {SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV}'].to_csv(output_path / f'{building.name}_op.csv')
|
||||
new_system = system_results(city.buildings)
|
||||
EnergySystemAnalysisReport(city, output_path).create_report(current_system, new_system)
|
||||
for building in city.buildings:
|
||||
costs = Cost(building=building, retrofit_scenario=SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV).life_cycle
|
||||
costs.to_csv(output_path / f'{building.name}_lcc.csv')
|
||||
(costs.loc['global_operational_costs', f'Scenario {SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV}'].
|
||||
to_csv(output_path / f'{building.name}_op.csv'))
|
||||
costs.loc['global_capital_costs', f'Scenario {SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV}'].to_csv(
|
||||
output_path / f'{building.name}_cc.csv')
|
||||
|
||||
|
||||
|
||||
|
|
|
@ -273,7 +273,7 @@ class CapitalCosts(CostBase):
|
|||
if generation_system.system_type != cte.PHOTOVOLTAIC:
|
||||
heating_capacity = generation_system.nominal_heat_output or 0
|
||||
cooling_capacity = generation_system.nominal_cooling_output or 0
|
||||
installed_capacity = max(heating_capacity, cooling_capacity)
|
||||
installed_capacity = max(heating_capacity, cooling_capacity) / 1000
|
||||
if cte.DOMESTIC_HOT_WATER in demand_types and cte.HEATING not in demand_types:
|
||||
component_categories.append('dhw')
|
||||
sizes.append(installed_capacity)
|
||||
|
|
|
@ -127,7 +127,7 @@ class Cost:
|
|||
life_cycle_costs_capital_skin = self._npv_from_list(df_capital_costs_skin.values.tolist())
|
||||
life_cycle_costs_capital_systems = self._npv_from_list(df_capital_costs_systems.values.tolist())
|
||||
life_cycle_costs_end_of_life_costs = self._npv_from_list(df_end_of_life_costs.values.tolist())
|
||||
life_cycle_operational_costs = self._npv_from_list([df_operational_costs])
|
||||
life_cycle_operational_costs = self._npv_from_list(df_operational_costs)
|
||||
life_cycle_maintenance_costs = self._npv_from_list(df_maintenance_costs.values.tolist())
|
||||
life_cycle_operational_incomes = self._npv_from_list(df_operational_incomes.values.tolist())
|
||||
life_cycle_capital_incomes = self._npv_from_list(df_capital_incomes.values.tolist())
|
||||
|
|
|
@ -45,7 +45,7 @@ class PeakLoad:
|
|||
conditioning_peak[i] = self._building.heating_peak_load[cte.MONTH][i] * heating
|
||||
else:
|
||||
conditioning_peak[i] = self._building.cooling_peak_load[cte.MONTH][i] * cooling
|
||||
monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]
|
||||
monthly_electricity_peak[i] += 0.8 * conditioning_peak[i] / 3600
|
||||
|
||||
electricity_peak_load_results = pd.DataFrame(
|
||||
monthly_electricity_peak,
|
||||
|
|
|
@ -51,7 +51,7 @@ class TotalOperationalCosts(CostBase):
|
|||
if fuel.type in fuel_consumption_breakdown.keys():
|
||||
if fuel.type == cte.ELECTRICITY:
|
||||
variable_electricity_cost_year_0 = (
|
||||
total_electricity_consumption / cte.WATTS_HOUR_TO_JULES * fuel.variable[0]
|
||||
total_electricity_consumption * fuel.variable[0] / 1000
|
||||
)
|
||||
peak_electricity_cost_year_0 = peak_electricity_demand * fuel.fixed_power * 12
|
||||
monthly_electricity_cost_year_0 = fuel.fixed_monthly * 12 * factor
|
||||
|
|
|
@ -197,9 +197,9 @@ class EnergySystemAnalysisReport:
|
|||
|
||||
def building_system_retrofit_results(self, building_name, current_system, new_system):
|
||||
current_system_archetype = current_system[f'{building_name}']['Energy System Archetype']
|
||||
current_system_heating = current_system[f'{building_name}']['Heating System']
|
||||
current_system_cooling = current_system[f'{building_name}']['Cooling System']
|
||||
current_system_dhw = current_system[f'{building_name}']['DHW System']
|
||||
current_system_heating = current_system[f'{building_name}']['Heating Equipments']
|
||||
current_system_cooling = current_system[f'{building_name}']['Cooling Equipments']
|
||||
current_system_dhw = current_system[f'{building_name}']['DHW Equipments']
|
||||
current_system_pv = current_system[f'{building_name}']['Photovoltaic System Capacity']
|
||||
current_system_heating_fuel = current_system[f'{building_name}']['Heating Fuel']
|
||||
current_system_hvac_consumption = current_system[f'{building_name}']['Yearly HVAC Energy Consumption (MWh)']
|
||||
|
@ -209,9 +209,9 @@ class EnergySystemAnalysisReport:
|
|||
current_operational = current_system[f'{building_name}']['Energy System Average Yearly Operational Cost (CAD)']
|
||||
current_lcc = current_system[f'{building_name}']['Energy System Life Cycle Cost (CAD)']
|
||||
new_system_archetype = new_system[f'{building_name}']['Energy System Archetype']
|
||||
new_system_heating = new_system[f'{building_name}']['Heating System']
|
||||
new_system_cooling = new_system[f'{building_name}']['Cooling System']
|
||||
new_system_dhw = new_system[f'{building_name}']['DHW System']
|
||||
new_system_heating = new_system[f'{building_name}']['Heating Equipments']
|
||||
new_system_cooling = new_system[f'{building_name}']['Cooling Equipments']
|
||||
new_system_dhw = new_system[f'{building_name}']['DHW Equipments']
|
||||
new_system_pv = new_system[f'{building_name}']['Photovoltaic System Capacity']
|
||||
new_system_heating_fuel = new_system[f'{building_name}']['Heating Fuel']
|
||||
new_system_hvac_consumption = new_system[f'{building_name}']['Yearly HVAC Energy Consumption (MWh)']
|
||||
|
@ -224,9 +224,9 @@ class EnergySystemAnalysisReport:
|
|||
energy_system_table_data = [
|
||||
["Detail", "Existing System", "Proposed System"],
|
||||
["Energy System Archetype", current_system_archetype, new_system_archetype],
|
||||
["Heating System", current_system_heating, new_system_heating],
|
||||
["Cooling System", current_system_cooling, new_system_cooling],
|
||||
["DHW System", current_system_dhw, new_system_dhw],
|
||||
["Heating Equipments", current_system_heating, new_system_heating],
|
||||
["Cooling Equipments", current_system_cooling, new_system_cooling],
|
||||
["DHW Equipments", current_system_dhw, new_system_dhw],
|
||||
["Photovoltaic System Capacity", current_system_pv, new_system_pv],
|
||||
["Heating Fuel", current_system_heating_fuel, new_system_heating_fuel],
|
||||
["Yearly HVAC Energy Consumption (MWh)", current_system_hvac_consumption, new_system_hvac_consumption],
|
||||
|
|
|
@ -3,9 +3,9 @@ import hub.helpers.constants as cte
|
|||
|
||||
def system_results(buildings):
|
||||
system_performance_summary = {}
|
||||
fields = ["Energy System Archetype", "Heating System", "Cooling System", "DHW System",
|
||||
fields = ["Energy System Archetype", "Heating Equipments", "Cooling Equipments", "DHW Equipments",
|
||||
"Photovoltaic System Capacity", "Heating Fuel", "Yearly HVAC Energy Consumption (MWh)",
|
||||
"DHW Energy Consumption (MWH)", "PV Yearly Production (kWh)",
|
||||
"DHW Energy Consumption (MWH)", "PV Yearly Production (kWh)", "LCC Analysis Duration (Years)",
|
||||
"Energy System Capital Cost (CAD)", "Energy System Average Yearly Operational Cost (CAD)",
|
||||
"Energy System Life Cycle Cost (CAD)"]
|
||||
for building in buildings:
|
||||
|
@ -19,19 +19,28 @@ def system_results(buildings):
|
|||
energy_systems = building.energy_systems
|
||||
for energy_system in energy_systems:
|
||||
demand_types = energy_system.demand_types
|
||||
if cte.HEATING and cte.DOMESTIC_HOT_WATER in demand_types:
|
||||
system_performance_summary[f'{building.name}']['Heating System'] = energy_system.name
|
||||
system_performance_summary[f'{building.name}']['DHW System'] = energy_system.name
|
||||
for generation_system in energy_system.generation_systems:
|
||||
fuels.append(generation_system.fuel_type)
|
||||
elif cte.DOMESTIC_HOT_WATER in energy_system.demand_types:
|
||||
system_performance_summary[f'{building.name}']['DHW System'] = energy_system.name
|
||||
elif cte.HEATING in energy_system.demand_types:
|
||||
system_performance_summary[f'{building.name}']['Heating System'] = energy_system.name
|
||||
for generation_system in energy_system.generation_systems:
|
||||
fuels.append(generation_system.fuel_type)
|
||||
elif cte.COOLING in energy_system.demand_types:
|
||||
system_performance_summary[f'{building.name}']['Cooling System'] = energy_system.name
|
||||
for demand_type in demand_types:
|
||||
if demand_type == cte.COOLING:
|
||||
equipments = []
|
||||
for generation_system in energy_system.generation_systems:
|
||||
if generation_system.fuel_type == cte.ELECTRICITY:
|
||||
equipments.append(generation_system.name or generation_system.system_type)
|
||||
cooling_equipments = ", ".join(equipments)
|
||||
system_performance_summary[f'{building.name}']['Cooling Equipments'] = cooling_equipments
|
||||
elif demand_type == cte.HEATING:
|
||||
equipments = []
|
||||
for generation_system in energy_system.generation_systems:
|
||||
if generation_system.nominal_heat_output is not None:
|
||||
equipments.append(generation_system.name or generation_system.system_type)
|
||||
fuels.append(generation_system.fuel_type)
|
||||
heating_equipments = ", ".join(equipments)
|
||||
system_performance_summary[f'{building.name}']['Heating Equipments'] = heating_equipments
|
||||
elif demand_type == cte.DOMESTIC_HOT_WATER:
|
||||
equipments = []
|
||||
for generation_system in energy_system.generation_systems:
|
||||
equipments.append(generation_system.name or generation_system.system_type)
|
||||
dhw_equipments = ", ".join(equipments)
|
||||
system_performance_summary[f'{building.name}']['DHW Equipments'] = dhw_equipments
|
||||
for generation_system in energy_system.generation_systems:
|
||||
if generation_system.system_type == cte.PHOTOVOLTAIC:
|
||||
system_performance_summary[f'{building.name}'][
|
||||
|
@ -47,9 +56,9 @@ def system_results(buildings):
|
|||
|
||||
def new_system_results(buildings):
|
||||
new_system_performance_summary = {}
|
||||
fields = ["Energy System Archetype", "Heating System", "Cooling System", "DHW System",
|
||||
fields = ["Energy System Archetype", "Heating Equipments", "Cooling Equipments", "DHW Equipments",
|
||||
"Photovoltaic System Capacity", "Heating Fuel", "Yearly HVAC Energy Consumption (MWh)",
|
||||
"DHW Energy Consumption (MWH)", "PV Yearly Production (kWh)",
|
||||
"DHW Energy Consumption (MWH)", "PV Yearly Production (kWh)", "LCC Analysis Duration (Years)",
|
||||
"Energy System Capital Cost (CAD)", "Energy System Average Yearly Operational Cost (CAD)",
|
||||
"Energy System Life Cycle Cost (CAD)"]
|
||||
for building in buildings:
|
||||
|
|
|
@ -15,8 +15,8 @@ from hub.city_model_structure.building import Building
|
|||
energy_systems_format = 'montreal_custom'
|
||||
|
||||
# parameters:
|
||||
residential_systems_percentage = {'system 1 gas': 100,
|
||||
'system 1 electricity': 0,
|
||||
residential_systems_percentage = {'system 1 gas': 44,
|
||||
'system 1 electricity': 6,
|
||||
'system 2 gas': 0,
|
||||
'system 2 electricity': 0,
|
||||
'system 3 and 4 gas': 0,
|
||||
|
@ -25,8 +25,8 @@ residential_systems_percentage = {'system 1 gas': 100,
|
|||
'system 5 electricity': 0,
|
||||
'system 6 gas': 0,
|
||||
'system 6 electricity': 0,
|
||||
'system 8 gas': 0,
|
||||
'system 8 electricity': 0}
|
||||
'system 8 gas': 44,
|
||||
'system 8 electricity': 6}
|
||||
|
||||
residential_new_systems_percentage = {'PV+ASHP+GasBoiler+TES': 100,
|
||||
'PV+4Pipe+DHW': 0,
|
||||
|
|
|
@ -1,9 +1,4 @@
|
|||
import subprocess
|
||||
import hub.helpers.constants as cte
|
||||
import matplotlib.pyplot as plt
|
||||
import random
|
||||
import matplotlib.colors as mcolors
|
||||
from matplotlib import cm
|
||||
import datetime
|
||||
|
||||
class LatexReport:
|
||||
|
|
|
@ -18,7 +18,7 @@ class Archetype1:
|
|||
self._hourly_cooling_demand = [demand / 3600 for demand in building.cooling_demand[cte.HOUR]]
|
||||
self._hourly_dhw_demand = building.domestic_hot_water_heat_demand[cte.HOUR]
|
||||
self._output_path = output_path
|
||||
self._t_out = building.external_temperature[cte.HOUR]
|
||||
self._t_out = [0] + building.external_temperature[cte.HOUR]
|
||||
|
||||
def hvac_sizing(self):
|
||||
storage_factor = 3
|
||||
|
@ -32,11 +32,11 @@ class Archetype1:
|
|||
(self._heating_peak_load * storage_factor) / (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 30))
|
||||
return heat_pump, boiler, thermal_storage
|
||||
|
||||
def hvac_simulation(self):
|
||||
def heating_system_simulation(self):
|
||||
hp, boiler, tes = self.hvac_sizing()
|
||||
cop_curve_coefficients = [float(coefficient) for coefficient in hp.heat_efficiency_curve.coefficients]
|
||||
demand = self._hourly_heating_demand
|
||||
if hp.source_medium == cte.AIR:
|
||||
hp.source_temperature = self._t_out
|
||||
hp.source_temperature = self._t_out
|
||||
# Heating System Simulation
|
||||
variable_names = ["t_sup_hp", "t_tank", "t_ret", "m_ch", "m_dis", "q_hp", "q_boiler", "hp_cop",
|
||||
"hp_electricity", "boiler_gas", "boiler_consumption", "t_sup_boiler", "heating_consumption"]
|
||||
|
@ -45,7 +45,6 @@ class Archetype1:
|
|||
(t_sup_hp, t_tank, t_ret, m_ch, m_dis, q_hp, q_boiler, hp_cop,
|
||||
hp_electricity, boiler_gas, boiler_consumption, t_sup_boiler, heating_consumption) = [variables[name] for name in
|
||||
variable_names]
|
||||
|
||||
t_tank[0] = 30
|
||||
dt = 3600
|
||||
hp_heating_cap = hp.nominal_heat_output
|
||||
|
@ -66,7 +65,7 @@ class Archetype1:
|
|||
m_dis[i] * (t_tank[i] - t_ret[i])) * (dt / (cte.WATER_DENSITY * v)))
|
||||
if t_tank[i + 1] < 40:
|
||||
q_hp[i + 1] = hp_heating_cap
|
||||
m_ch[i + 1] = q_hp[i + 1] / (cte.WATER_HEAT_CAPACITY * 7)
|
||||
m_ch[i + 1] = q_hp[i + 1] / (cte.WATER_HEAT_CAPACITY * 5)
|
||||
t_sup_hp[i + 1] = (q_hp[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY)) + t_tank[i + 1]
|
||||
elif 40 <= t_tank[i + 1] < 55 and q_hp[i] == 0:
|
||||
q_hp[i + 1] = 0
|
||||
|
@ -78,54 +77,116 @@ class Archetype1:
|
|||
t_sup_hp[i + 1] = (q_hp[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY)) + t_tank[i + 1]
|
||||
else:
|
||||
q_hp[i + 1], m_ch[i + 1], t_sup_hp[i + 1] = 0, 0, t_tank[i + 1]
|
||||
|
||||
hp_electricity[i + 1] = q_hp[i + 1] / hp_efficiency
|
||||
t_sup_hp_fahrenheit = 1.8 * t_sup_hp[i + 1] + 32
|
||||
t_out_fahrenheit = 1.8 * self._t_out[i + 1] + 32
|
||||
if q_hp[i + 1] > 0:
|
||||
hp_cop[i + 1] = (cop_curve_coefficients[0] +
|
||||
cop_curve_coefficients[1] * t_sup_hp_fahrenheit +
|
||||
cop_curve_coefficients[2] * t_sup_hp_fahrenheit ** 2 +
|
||||
cop_curve_coefficients[3] * t_out_fahrenheit +
|
||||
cop_curve_coefficients[4] * t_out_fahrenheit ** 2 +
|
||||
cop_curve_coefficients[5] * t_sup_hp_fahrenheit * t_out_fahrenheit)
|
||||
hp_electricity[i + 1] = q_hp[i + 1] / hp_cop[i + 1]
|
||||
else:
|
||||
hp_cop[i + 1] = 0
|
||||
hp_electricity[i + 1] = 0
|
||||
if demand[i + 1] == 0:
|
||||
m_dis[i + 1], t_return, t_ret[i + 1] = 0, t_tank[i + 1], t_tank[i + 1]
|
||||
else:
|
||||
if demand[i + 1] > 0.5 * self._heating_peak_load:
|
||||
if demand[i + 1] > 0.5 * self._heating_peak_load / dt:
|
||||
factor = 8
|
||||
else:
|
||||
factor = 4
|
||||
m_dis[i + 1] = self._heating_peak_load / (cte.WATER_HEAT_CAPACITY * factor * dt)
|
||||
t_return = t_tank[i + 1] - demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY * dt)
|
||||
if m_dis[i + 1] == 0 or (m_dis[i + 1] > 0 and t_return < 25):
|
||||
t_ret[i + 1] = max(25, t_tank[i + 1])
|
||||
else:
|
||||
t_ret[i + 1] = t_tank[i + 1] - demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY * dt)
|
||||
tes_output = m_dis[i + 1] * cte.WATER_HEAT_CAPACITY * (t_tank[i + 1] - t_ret[i + 1])
|
||||
if tes_output < (demand[i + 1] / dt):
|
||||
q_boiler[i + 1] = (demand[i + 1] / dt) - tes_output
|
||||
boiler_gas[i + 1] = (q_boiler[i + 1] * dt) / cte.NATURAL_GAS_LHV
|
||||
if q_boiler[i + 1] > 0:
|
||||
t_sup_boiler[i + 1] = q_boiler[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY) + t_tank[i + 1]
|
||||
else:
|
||||
t_sup_boiler[i + 1] = t_tank[i + 1]
|
||||
t_return = t_tank[i + 1] - demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY)
|
||||
if t_return >= 25:
|
||||
t_ret[i + 1] = t_tank[i + 1] - demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY)
|
||||
q_boiler[i + 1] = 0
|
||||
t_sup_boiler[i + 1] = t_tank[i + 1]
|
||||
else:
|
||||
t_ret[i + 1] = 25
|
||||
t_sup_boiler[i + 1] = t_ret[i + 1] + (demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY))
|
||||
q_boiler[i + 1] = m_dis[i + 1] * cte.WATER_HEAT_CAPACITY * (t_sup_boiler[i + 1] - t_tank[i + 1])
|
||||
boiler_gas[i + 1] = (q_boiler[i + 1] * dt) / cte.NATURAL_GAS_LHV
|
||||
boiler_consumption[i + 1] = q_boiler[i + 1] / boiler_efficiency
|
||||
heating_consumption[i + 1] = boiler_consumption[i + 1] + hp_electricity[i + 1]
|
||||
data = list(zip(q_hp, hp_electricity, hp_cop, m_ch, t_sup_hp, t_tank, m_dis, q_boiler,
|
||||
data = list(zip(self._t_out, q_hp, hp_electricity, hp_cop, m_ch, t_sup_hp, t_tank, m_dis, q_boiler,
|
||||
boiler_gas, t_sup_boiler, t_ret, demand))
|
||||
file_name = f'simulation_results_{self._name}.csv'
|
||||
file_name = f'heating_system_simulation_results_{self._name}.csv'
|
||||
with open(self._output_path / file_name, 'w', newline='') as csvfile:
|
||||
output_file = csv.writer(csvfile)
|
||||
# Write header
|
||||
output_file.writerow(['HP_heat_output(W)', 'HP_electricity_consumption(W)', 'HP_COP',
|
||||
'TES_charge_flow_rate(kg/s)', 'TES_supply_temperature(C)', 'TES_temperature(C)',
|
||||
output_file.writerow(['Outside_air_temperature', 'HP_heat_output(W)', 'HP_heating_electricity_consumption(W)',
|
||||
'HP_COP', 'TES_charge_flow_rate(kg/s)', 'TES_supply_temperature(C)', 'TES_temperature(C)',
|
||||
'TES_discharge_flow_rate(kg/s)', 'Boiler_heat_output(W)', 'Boiler_gas_consumption(m3)',
|
||||
'Boiler_supply_temperature(C)', 'Return_temperature(C)', 'heating_demand'])
|
||||
'Boiler_supply_temperature(C)', 'Heating_loop_return_temperature(C)', 'Heating_demand (W)'])
|
||||
# Write data
|
||||
output_file.writerows(data)
|
||||
return heating_consumption, hp_electricity, boiler_consumption, t_sup_hp, t_sup_boiler
|
||||
|
||||
def cooling_system_simulation(self):
|
||||
hp = self.hvac_sizing()[0]
|
||||
eer_curve_coefficients = [float(coefficient) for coefficient in hp.cooling_efficiency_curve.coefficients]
|
||||
demand = self._hourly_heating_demand
|
||||
hp.source_temperature = self._t_out
|
||||
variable_names = ["t_sup_hp", "t_ret", "m", "q_hp", "hp_electricity", "hp_eer"]
|
||||
num_hours = len(demand)
|
||||
variables = {name: [0] * num_hours for name in variable_names}
|
||||
(t_sup_hp, t_ret, m, q_hp, hp_electricity, hp_eer) = [variables[name] for name in variable_names]
|
||||
t_ret[0] = 13
|
||||
dt = 3600
|
||||
for i in range(len(demand) - 1):
|
||||
if demand[i] > 0:
|
||||
m[i] = self._cooling_peak_load / (cte.WATER_HEAT_CAPACITY * 5 * dt)
|
||||
if t_ret[i] > 13:
|
||||
q_hp[i] = hp.nominal_cooling_output
|
||||
t_sup_hp[i] = t_ret[i] - q_hp[i] / (m[i] * cte.WATER_HEAT_CAPACITY)
|
||||
else:
|
||||
q_hp[i] = 0
|
||||
t_sup_hp[i] = t_ret[i]
|
||||
t_ret[i + 1] = t_sup_hp[i] + demand[i] / (m[i] * cte.WATER_HEAT_CAPACITY)
|
||||
else:
|
||||
m[i] = 0
|
||||
q_hp[i] = 0
|
||||
t_sup_hp[i] = t_ret[i]
|
||||
t_ret[i + 1] = t_ret[i]
|
||||
t_sup_hp_fahrenheit = 1.8 * t_sup_hp[i] + 32
|
||||
t_out_fahrenheit = 1.8 * self._t_out[i] + 32
|
||||
if q_hp[i] > 0:
|
||||
hp_eer[i] = 1/((eer_curve_coefficients[0] +
|
||||
eer_curve_coefficients[1] * t_sup_hp_fahrenheit +
|
||||
eer_curve_coefficients[2] * t_sup_hp_fahrenheit ** 2 +
|
||||
eer_curve_coefficients[3] * t_out_fahrenheit +
|
||||
eer_curve_coefficients[4] * t_out_fahrenheit ** 2 +
|
||||
eer_curve_coefficients[5] * t_sup_hp_fahrenheit * t_out_fahrenheit))
|
||||
hp_electricity[i] = q_hp[i] / hp_eer[i]
|
||||
else:
|
||||
hp_eer[i] = 0
|
||||
hp_electricity[i] = 0
|
||||
|
||||
data = list(zip(q_hp, hp_electricity, hp_eer, m, t_sup_hp, t_ret, demand, self._t_out))
|
||||
file_name = f'cooling_system_simulation_results_{self._name}.csv'
|
||||
with open(self._output_path / file_name, 'w', newline='') as csvfile:
|
||||
output_file = csv.writer(csvfile)
|
||||
# Write header
|
||||
output_file.writerow(['HP_cooling_output (W)', 'HP_cooling_electricity_consumption (W)', 'HP_EER',
|
||||
'Cooling_loop_flow_rate(kg/s)', 'Cooling_supply_temperature(C)',
|
||||
'Cooling_loop_return_temperature(C)', 'Cooling_demand (W)', 'Outside_Air_Temperature'])
|
||||
# Write data
|
||||
output_file.writerows(data)
|
||||
return hp_electricity, t_sup_hp
|
||||
|
||||
|
||||
def enrich_buildings(self):
|
||||
(self._building.heating_consumption[cte.HOUR], hp_electricity,
|
||||
boiler_consumption, t_sup_hp, t_sup_boiler) = self.hvac_simulation()
|
||||
(self._building.heating_consumption[cte.HOUR], hp_electricity_heating,
|
||||
boiler_consumption, t_sup_hp, t_sup_boiler) = self.heating_system_simulation()
|
||||
hp_electricity_cooling, t_sup_hp_cooling = self.cooling_system_simulation()
|
||||
self._building.heating_consumption[cte.MONTH] = MonthlyValues.get_total_month(
|
||||
self._building.heating_consumption[cte.HOUR])
|
||||
self._building.heating_consumption[cte.YEAR] = [sum(self._building.heating_consumption[cte.MONTH])]
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.HEATING] = {}
|
||||
self._hvac_system.generation_systems[1].energy_consumption[cte.HEATING] = {}
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.HEATING][cte.HOUR] = hp_electricity
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.HEATING][cte.HOUR] = hp_electricity_heating
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.HEATING][cte.MONTH] = MonthlyValues.get_total_month(
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.HEATING][cte.HOUR])
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.HEATING][cte.YEAR] = \
|
||||
|
@ -137,5 +198,12 @@ class Archetype1:
|
|||
[sum(self._hvac_system.generation_systems[1].energy_consumption[cte.HEATING][cte.MONTH])]
|
||||
self._hvac_system.generation_systems[0].heat_supply_temperature = t_sup_hp
|
||||
self._hvac_system.generation_systems[1].heat_supply_temperature = t_sup_boiler
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.COOLING] = self._building.cooling_consumption
|
||||
self._dhw_system.generation_systems[0].energy_consumption[cte.DOMESTIC_HOT_WATER] = self._building.domestic_hot_water_consumption
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.COOLING] = {}
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.COOLING][cte.HOUR] = hp_electricity_cooling
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.COOLING][cte.MONTH] = MonthlyValues.get_total_month(
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.COOLING][cte.HOUR])
|
||||
self._hvac_system.generation_systems[0].energy_consumption[cte.COOLING][cte.YEAR] = \
|
||||
[sum(self._hvac_system.generation_systems[0].energy_consumption[cte.COOLING][cte.MONTH])]
|
||||
self._hvac_system.generation_systems[0].cooling_supply_temperature = t_sup_hp_cooling
|
||||
self._dhw_system.generation_systems[0].energy_consumption[cte.DOMESTIC_HOT_WATER] = (
|
||||
self._building.domestic_hot_water_consumption)
|
||||
|
|
Loading…
Reference in New Issue
Block a user