API Reference

calculate_performance_of_single_location(mask, depth, thickness, porosity, ntg, temperature, transmissivity, transmissivity_with_ntg, rng_seed, utc_properties=None, mask_value=0.0)

Calculate the performance of a doublet at a single location.

Parameters:

Name	Type	Description	Default
utc_properties	dict	Dictionary containing UTC (Underground Thermal Capacity) properties.	None
mask	float	Mask value; if not NaN, all output values will be set to mask_value.	required
depth	float	Depth of the aquifer in meters.	required
thickness	float	Thickness of the aquifer in meters.	required
porosity	float	Porosity of the aquifer (fraction).	required
ntg	float	Net-to-gross ratio of the aquifer (fraction).	required
temperature	float	Temperature of the aquifer in degrees Celsius.	required
transmissivity	float	Transmissivity of the aquifer.	required
transmissivity_with_ntg	float	Product of transmissivity and net-to-gross.	required
mask_value	float	0.0 by default, Any cell that results in a failed simulation or corresponds to a non-nan value in the mask parameter will be assigned the mask value	0.0

Returns:

Name	Type	Description
power	float geothermal power [MW]
heat_pump_power	float power after heat pump [MW]
capex	float Capital expenditure [M€]
opex	float for first production year [M€]
utc	float unit technical costs/levelized cost of geothermal heat [€/kWh]
npv	float (net-present-value) [M€]
hprod	float total energy production for firstyear [kWh]
cop	float system cop [-]
cophp	float heat pump cop[-]
pres	float for driving loop [bar]
flow_rate	float[m3 / h]
welld	float[m]
inj_temp	float[C]
prd_temp	float[C]

Source code in src/pythermogis/thermogis_classes/doublet.py

def calculate_performance_of_single_location(mask: float, depth: float, thickness: float, porosity: float, ntg: float, temperature: float, transmissivity: float, transmissivity_with_ntg: float, rng_seed: int, utc_properties: JClass = None, mask_value: float = 0.0) -> float:
    """
    Calculate the performance of a doublet at a single location.

    Parameters
    ----------
    utc_properties : dict
        Dictionary containing UTC (Underground Thermal Capacity) properties.
    mask : float
        Mask value; if not NaN, all output values will be set to mask_value.
    depth : float
        Depth of the aquifer in meters.
    thickness : float
        Thickness of the aquifer in meters.
    porosity : float
        Porosity of the aquifer (fraction).
    ntg : float
        Net-to-gross ratio of the aquifer (fraction).
    temperature : float
        Temperature of the aquifer in degrees Celsius.
    transmissivity : float
        Transmissivity of the aquifer.
    transmissivity_with_ntg : float
        Product of transmissivity and net-to-gross.
    mask_value : float
        0.0 by default, Any cell that results in a failed simulation or corresponds to a
        non-nan value in the mask parameter will be assigned the mask value

    Returns
    -------
    power: float  geothermal power [MW]
    heat_pump_power: float  power after heat pump [MW]
    capex: float Capital expenditure  [M€]
    opex: float for first production year [M€]
    utc: float unit technical costs/levelized cost of geothermal heat [€/kWh]
    npv: float (net-present-value) [M€]
    hprod: float total energy production for firstyear [kWh]
    cop: float  system cop [-]
    cophp: float  heat pump cop[-]
    pres: float for driving loop [bar]
    flow_rate: float [m3/h]
    welld: float [m]
    inj_temp: float [C]
    prd_temp: float [C]
    """
    if not validate_input(depth, ntg, porosity, temperature, thickness, transmissivity,
                   transmissivity_with_ntg):
        return (np.nan,) * 14

    if not np.isnan(mask) or temperature < utc_properties.minProdTemp():
        return (mask_value,) * 14

    # Instantiate ThermoGIS doublet
    doublet = instantiate_thermogis_doublet(utc_properties, rng_seed)

    DoubletInput = JClass("thermogis.calc.utc.doublet.records.DoubletInput")
    input = DoubletInput(
            -9999.0, # unknowninput
            thickness,
            transmissivity,
            transmissivity_with_ntg,
            ntg,
            depth,
            porosity,
            temperature,
            None, # ates input
        )

    # The Java routine which calculates DoubletPerformance, for more detail on the simulation inspect the Java source code
    try:
        results = doublet.calculateDoubletPerformance(input)
    except:
        return (mask_value,) * 14

    # If calculation was not successful, return mask value
    if results is None or results.utc() == -9999.0:
        return (mask_value,) * 14

    # calculate net-present-value using the utc-cutoffs
    if depth > utc_properties.utcDeepDepth():
        utc_cut = utc_properties.utcCutoffDeep()
    else:
        utc_cut = utc_properties.utcCutoff()

    hprod = results.hprod()
    npv = 1e-6 * (utc_cut - results.utc()) * 3.6 * hprod * (1 - utc_properties.taxRate())

    # get values from doublet
    output_values = {"power": results.power(),
                     "heat_pump_power": results.hppower(),
                     "capex": results.capex(),
                     "opex": results.opex(),
                     "utc": results.utc(),
                     "npv": npv,
                     "hprod": hprod,
                     "cop": results.cop(),
                     "cophp": results.cophp(),
                     "pres": results.pres(),
                     "flow_rate": results.flow(),
                     "welld": results.welld(),
                     "inj_temp": results.injectionTemp(),
                     "prd_temp": results.productionTemp(),
                     }

    # Reset doublet variables for next calculation
    return output_values["power"], output_values["heat_pump_power"], output_values["capex"], output_values["opex"], output_values["utc"], output_values["npv"], output_values["hprod"], output_values["cop"], output_values[
        "cophp"], output_values["pres"], output_values["flow_rate"], output_values["welld"], output_values["inj_temp"], output_values["prd_temp"]

instantiate_thermogis_doublet(utc_properties, rng_seed=None)

Instantiate a ThermoGIS Doublet class, setting necessary parameters from utc_properties and optionally using a specified random seed.

Parameters:

Name	Type	Description	Default
utc_properties	UTCProperties	Instance containing the input parameters required for the doublet simulation.	required
rng_seed	int	Optional random seed for reproducibility.	None

Returns:

Name	Type	Description
doublet	object	A JPype-instantiated object of the ThermoGISDoublet class.

Source code in src/pythermogis/thermogis_classes/doublet.py

def instantiate_thermogis_doublet(utc_properties, rng_seed: int = None) -> JClass:
    """
    Instantiate a ThermoGIS Doublet class, setting necessary parameters from utc_properties and optionally using a specified random seed.

    Parameters
    ----------
    utc_properties : UTCProperties
        Instance containing the input parameters required for the doublet simulation.
    rng_seed : int
        Optional random seed for reproducibility.

    Returns
    -------
    doublet : object
        A JPype-instantiated object of the ThermoGISDoublet class.
    """

    # Instantiate doublet class
    Logger = JClass("logging.Logger")
    Mockito = JClass("org.mockito.Mockito")
    RNG = JClass("tno.geoenergy.stochastic.RandomNumberGenerator")
    ThermoGISDoublet = JClass("thermogis.calc.utc.doublet.ThermoGisDoublet")

    # Create an instance of a ThermoGISDoublet
    if rng_seed is not None:
        rng = RNG(rng_seed)
    else:
        rng = RNG()

    doublet = ThermoGISDoublet(Mockito.mock(Logger), rng, utc_properties)

    return doublet

validate_input(depth, ntg, porosity, temperature, thickness, transmissivity, transmissivity_with_ntg)

Check that none of the input is nan

Source code in src/pythermogis/thermogis_classes/doublet.py

def validate_input(depth: float,
    ntg: float,
    porosity: float,
    temperature: float,
    thickness: float,
    transmissivity: float,
    transmissivity_with_ntg: float,
) -> bool:
    """
    Check that none of the input is nan
    """
    return not np.any(np.isnan([depth, ntg, porosity, temperature, thickness, transmissivity, transmissivity_with_ntg]))