Convert Sources
- src.Source.simulation.Convert.convert_sources.convert_sources(in_var, kb)[source]
Design of technologies to connect sources to the DHN.
For each source are designed the conversion technologies needed. When performing the conversion, three design options may occur:
If the stream supply temperature > DHN supply temperature -> HX designed
If the stream supply temperature > ORC evaporator -> ORC cascaded designed
If the stream supply temperature < DHN supply temperature -> HX and heating technologies are designed to fulfill DHN temperature
- Parameters
in_var (dict) –
platform and CF module data, with the following keys:
- platform: dict
Platform data, with the following keys:
- existing_grid_data: list with dict [OPTIONAL]
Existent grid connection point data, with the following keys:
- id: int
Existent source or grid connection point ID
- location: list
Location [º]; [latitude,longitude]
- levelized_co2_emissions: float
Grid levelized CO2 emissions [CO2/kWh]
- levelized_om_var: float
Grid levelized OM var [€/kWh]
- levelized_om_fix: float
Grid levelized OM fix [€/kWh]
- group_of_sources: list with dict
Sources to be analyzed. Each source with the following keys:
- id: int:
Source ID
- location: list
Location [º]; [latitude,longitude]
- fuels_data: dict, optional
Fuels price and CO2 emission, with the following keys:
- natural_gas: dict
with the following keys:
- co2_emissions: float:
Fuel CO2 emission [kg CO2/kWh]
- price: float:
Fuel price [€/kWh]
- fuel_oildict
Similar to “natural_gas”
- electricitydict
Similar to “natural_gas”
- biomassdict
Similar to “natural_gas”
- streams: list with dict
Source’s streams to be analyzed. Each stream with the following keys:
- stream_id: int
Stream ID []
- object_type: str
DEFAULT=stream []
- stream_type: str
Stream designation []; inflow, outflow, excess_heat
- fluid: str
Stream’s fluid []
- capacity: float
Stream’s capacity [kW]
- supply_temperature: float
Stream’s supply/initial temperature [ºC]
- target_temperature: float
Stream’s target/final temperature [ºC]
- hourly_generation: list
Stream’s hourly capacity [kWh]
- cf_module: dict
CF module data, with the following keys:
- sink_group_grid_supply_temperature: float
Grid supply temperature (user input or defined by the “convert_sinks”) [ºC]
- sink_group_grid_return_temperature: float
Grid return temperature (user input or defined by the “convert_sinks”) [ºC]
kb (dict) – Knowledge Base data
- Returns
all_info –
Sources conversion data, with the following keys:
- all_sources_info: list
Sources dicts to be analyzed. Each source with the following keys:
- source_id: int:
Source ID
- location: list:
Location [º]; [latitude,longitude]
- source_grid_supply_temperature: float
Source-grid supply temperature [ºC]
- source_grid_return_temperature: float
Source-grid return temperature [ºC]
- streams_convertedlist
Streams conversion data dicts, with the following keys:
- stream_id: int
Stream ID
- teo_stream_id: str
TEO specific data; stream ID with source ID []
- input_fuel: str
TEO specific data; TEO input fuel name []
- output_fuel: str
TEO specific data; TEO output fuel name []
- output: int
TEO specific data; DEFAULT=1 []
- gis_capacity: float
GIS specific data; stream converted/provided capacity to the grid
- hourly_stream_capacity: list
Hourly stream capacity [kWh]
- teo_capacity_factor: list
TEO specific data
- max_stream_capacity: float
Max stream capacity [kW]
- conversion_technologies: list
Conversion solution data dicts (technologies implemented), with the following keys:
- teo_equipment_name: str
TEO specific data; TEO equipment name []
- output: int
TEO specific data; DEFAULT=1 []
- input_fuel: str
TEO specific data; TEO input fuel name []
- output_fuel: str
TEO specific data; TEO output fuel name []
- equipment: list
Conversion solution equipment names []
- max_capacity: float
Stream capacity maximum capacity convertible [kW]
- turnkey_a: float
Conversion solution turnkey a (ax+b) [€/kW]
- turnkey_b: float
Conversion solution turnkey b (ax+b) [€]
- conversion_efficiency: float
Conversion solution efficiency stream-to-grid []
- om_fix: float
Conversion solution OM fix [€/year.kW]
- om_var: float
Conversion solution OM var [€/kWh]
- emissions: float
Conversion solution CO2 emissions [kg.CO2/kWh]
- technologies: list
Each technologies info in detail dicts (check each technology routine for more details)
- ex_grid: dict, list
TEO specific data; existent grid data
- teo_equipment_name: str
DEFAULT=”ex_grid”
- output: int
DEFAULT=1
- input_fuel: None
DEFAULT=None
- output_fuel: str
DEFAULT=”dhnwatersupply”
- equipment: list
DEFAULT=[]
- max_capacity: float
DEFAULT=10**8
- turnkey_a: float
DEFAULT=0
- turnkey_b: float
DEFAULT=0
- conversion_efficiency: float
DEFAULT=1
- om_fix: int
Levelized OM Var [€/year]
- om_var: int
Levelized OM Var [€/kWh]
- emissions: float
Levelized CO2 emissions [kgCO2/kWh]
- technologies: list
DEFAULT=[]
- teo_string: str
TEO specific data. DEFAULT=”dhn”
- input_fuel: str
TEO specific data. DEFAULT=”dhnwatersupply”
- output_fuel: str
TEO specific data. DEFAULT=”dhnwaterdem”
- output: int
TEO specific data. DEFAULT=1
- input: int
TEO specific data. DEFAULT=1
- n_supply_list: list
GIS specific data. Sources location and capacity provided to the grid
- teo_capacity_factor_group: int
TEO specific data
- teo_dhn: dict
TEO specific data. Parameters TEO
- Return type
dict