reV.SAM.generation.Geothermal

class Geothermal(resource, meta, sam_sys_inputs, site_sys_inputs=None, output_request=None, drop_leap=False)[source]

Bases: AbstractSamGenerationFromWeatherFile

reV-SAM geothermal generation.

As of 12/20/2022, the resource potential input in SAM is only used to calculate the number of well replacements during the lifetime of a geothermal plant. It was decided that reV would not model well replacements. Therefore, reV sets the resource potential to match (or be just above) the gross potential so that SAM does not throw any errors.

Also as of 12/20/2022, the SAM GETEM module requires a weather file, but does not actually require any weather data to run. Therefore, reV currently generates an empty weather file to pass to SAM. This behavior can be easily updated in the future should the SAM GETEM module start using weather data.

See the PySAM Geothermal documentation for the configuration keys required in the sam_sys_inputs config. Some notable keys include (non-exhaustive):

resource_type : Integer flag representing either Hydrothermal (0) or EGS (1) resource. Only values of 0 or 1 allowed.

resource_potential : Total resource potential at location (in MW).

Important

reV automatically sets the resource potential to match the gross potential (see documentation above), so this key should be left out of the config (it will be overridden in any case).

resource_temp : Temperature of resource (in C).

Important

This value is set by reV based on the user’s geothermal resource data input. To override this behavior, users may specify their own resource_temp value (either a single value for all sites in the SAM geothermal config or a site-dependent value in the project points CSV). In this case, the resource temperature from the input data will be ignored completely, and the temperature at each location will be determined solely from this input.

resource_depth : Depth to geothermal resource (in m).

analysis_type : Integer flag representing the plant configuration. If the nameplate input is to be used to specify the plant capacity, then this flag should be set to 0 (this is the default reV assumption). Otherwise, if the num_wells input is to be used to specify the plant site, then this flag should be set to 1. Only values of 0 or 1 allowed.

nameplate : Geothermal plant size (in kW). Only affects the output if analysis_type=0.

Important

Unlike wind or solar, reV geothermal dynamically sets the size of a geothermal plant. In particular, the plant capacity is set to match the resource potential (obtained from the input data) for each site. For this to work, users must leave out the nameplate key from the SAM config.

Alternatively, users may specify their own nameplate capacity value (either a single value for all sites in the SAM geothermal config or a site-dependent value in the project points CSV). In this case, the resource potential from the input data will be ignored completely, and the capacity at each location will be determined solely from this input.

num_wells : Number of wells at each plant. This value is used to determined plant capacity if analysis_type=1. Otherwise this input has no effect.

num_wells_getem : Number of wells assumed at each plant for power block calculations. Only affects power block outputs if analysis_type=0 (otherwise the num_wells input is used in power block calculations).

Note

reV does not currently adjust this value based on the resource input (as it probably should). If any power block outputs are required in the future, there may need to be extra development to set this value based on the dynamically calculated plant size.

conversion_type : Integer flag representing the conversion plant type. Either Binary (0) or Flash (1). Only values of 0 or 1 allowed.

geotherm.cost.inj_prod_well_ratio : Fraction representing the injection to production well ratio (0-1). SAM GUI defaults to 0.5 for this value, but it is recommended to set this to the GETEM default of 0.75.

You may also include the following reV-specific keys:

num_confirmation_wells : Number of confirmation wells that can also be used as production wells. This number is used to determined to total number of wells required at each plant, and therefore the total drilling costs. This value defaults to 2 (to match the SAM GUI as of 8/1/2023). However, the default value can lead to negative costs if the plant size is small (e.g. only 1 production well is needed, so the costs equal -1 * drill_cost_per_well). This is a limitation of the SAM calculations (as of 8/1/2023), and it is therefore useful to set num_confirmation_wells=0 when performing reV runs for small plant sizes.

capital_cost_per_kw : Capital cost values in $/kW. If this value is specified in the config, reV calculates and overrides the total capital_cost value based on the geothermal plant size (capacity) at each location.

fixed_operating_cost : Fixed operating cost values in $/kW. If this value is specified in the config, reV calculates and overrides the total fixed_operating_cost value based on the geothermal plant size (capacity) at each location.

drill_cost_per_well : Drilling cost per well, in $. If this value is specified in the config, reV calculates the total drilling costs based on the number of wells that need to be drilled at each location. The drilling costs are added to the total capital_cost at each location.
reV_outages : Specification for reV-scheduled stochastic outage losses. For example:
outage_info = [
    {
        'count': 6,
        'duration': 24,
        'percentage_of_capacity_lost': 100,
        'allowed_months': ['January', 'March'],
        'allow_outage_overlap': True
    },
    {
        'count': 10,
        'duration': 1,
        'percentage_of_capacity_lost': 10,
        'allowed_months': ['January'],
        'allow_outage_overlap': False
    },
    ...
]
See the description of add_scheduled_losses() or the reV losses demo notebook for detailed instructions on how to specify this input.
reV_outages_seed : Integer value used to seed the RNG used to compute stochastic outage losses.

time_index_step : Integer representing the step size used to sample the time_index in the resource data. This can be used to reduce temporal resolution (i.e. for 30 minute NSRDB input data, time_index_step=1 yields the full 30 minute time series as output, while time_index_step=2 yields hourly output, and so forth).

Initialize a SAM generation object.

Parameters:

resource (pd.DataFrame) – Timeseries solar or wind resource data for a single location with a pandas DatetimeIndex. There must be columns for all the required variables to run the respective SAM simulation. Remapping will be done to convert typical NSRDB/WTK names into SAM names (e.g. DNI -> dn and wind_speed -> windspeed)
meta (pd.DataFrame | pd.Series) – Meta data corresponding to the resource input for the single location. Should include values for latitude, longitude, elevation, and timezone.
sam_sys_inputs (dict) – Site-agnostic SAM system model inputs arguments.
site_sys_inputs (dict) – Optional set of site-specific SAM system inputs to complement the site-agnostic inputs.
output_request (list) – Requested SAM outputs (e.g., ‘cf_mean’, ‘annual_energy’, ‘cf_profile’, ‘gen_profile’, ‘energy_yield’, ‘ppa_price’, ‘lcoe_fcr’).
drop_leap (bool) – Drops February 29th from the resource data. If False, December 31st is dropped from leap years.

Methods

`add_scheduled_losses`([resource])	Add stochastically scheduled losses to SAM config file.
`annual_energy`()	Get annual energy generation value in kWh from SAM.
`assign_inputs`()	Assign the self.sam_sys_inputs attribute to the PySAM object.
`cf_mean`()	Get mean capacity factor (fractional) from SAM.
`cf_profile`()	Get hourly capacity factor (frac) profile in local timezone.
`check_resource_data`(resource)	Check resource dataframe for NaN values
`collect_outputs`([output_lookup])	Collect SAM output_request, convert timeseries outputs to UTC, and save outputs to self.outputs property.
`default`()	Get the executed default PySAM Geothermal object.
`drop_leap`(resource)	Drop Feb 29th from resource df with time index.
`energy_yield`()	Get annual energy yield value in kwh/kw from SAM.
`ensure_res_len`(arr, time_index)	Ensure time_index has a constant time-step and only covers 365 days (no leap days).
`execute`()	Call the PySAM execute method.
`gen_profile`()	Get power generation profile (local timezone) in kW.
`get_sam_res`(args, *kwargs)	Get the SAM resource iterator object (single year, single file).
`get_time_interval`(time_index)	Get the time interval.
`make_datetime`(series)	Ensure that pd series is a datetime series with dt accessor
`outputs_to_utc_arr`()	Convert array-like SAM outputs to UTC np.ndarrays
`reV_run`(points_control, res_file, site_df[, ...])	Execute SAM generation based on a reV points control instance.
`run`()	Run a reV-SAM generation object by assigning inputs, executing the SAM simulation, collecting outputs, and converting all arrays to UTC.
`run_gen_and_econ`()	Run SAM generation and possibility follow-on econ analysis.
`set_resource_data`(resource, meta)	Generate the weather file and set the path as an input.
`tz_elev_check`(sam_sys_inputs, ...)	Check timezone+elevation input and use json config timezone+elevation if not in resource meta.

Attributes

`DIR`
`IGNORE_ATTRS`
`MODULE`
`OUTAGE_CONFIG_KEY`	Specify outage information in the config file using this key.
`OUTAGE_SEED_CONFIG_KEY`	Specify a randomizer seed in the config file using this key.
`PYSAM_WEATHER_TAG`
`WF_META_DROP_COLS`
`attr_dict`	Get the heirarchical PySAM object attribute dictionary.
`has_timezone`	Returns true if instance has a timezone set
`input_list`	Get the list of lowest level input attribute/variable names.
`meta`	Get meta data property.
`module`	Get module property.
`outage_seed`	A value to use as the seed for the outage losses.
`pysam`	Get the pysam object.
`site`	Get the site number for this SAM simulation.

PYSAM = <module 'PySAM.Geothermal' from '/opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/PySAM/Geothermal.cpython-38-x86_64-linux-gnu.so'>

static default()[source]

Get the executed default PySAM Geothermal object.

Returns:: PySAM.Geothermal

cf_profile()[source]

Get hourly capacity factor (frac) profile in local timezone. See self.outputs attribute for collected output data in UTC.

Returns:: cf_profile (np.ndarray) – 1D numpy array of capacity factor profile. Datatype is float32 and array length is 8760*time_interval.

assign_inputs()[source]: Assign the self.sam_sys_inputs attribute to the PySAM object.

set_resource_data(resource, meta)[source]

Generate the weather file and set the path as an input.

The Geothermal PySAM model requires a data file, not raw data. This method generates the weather data, writes it to a file on disk, and then sets the file as an input to the Geothermal generation module. The function run_gen_and_econ() deletes the file on disk after a run is complete.

Parameters:

resource (pd.DataFrame) – Time series resource data for a single location with a pandas DatetimeIndex. There must be columns for all the required variables to run the respective SAM simulation.
meta (pd.Series) – Meta data corresponding to the resource input for the single location. Should include values for latitude, longitude, elevation, and timezone.

run_gen_and_econ()[source]: Run SAM generation and possibility follow-on econ analysis.

OUTAGE_CONFIG_KEY = 'reV_outages': Specify outage information in the config file using this key.

OUTAGE_SEED_CONFIG_KEY = 'reV_outages_seed': Specify a randomizer seed in the config file using this key.

add_scheduled_losses(resource=None)

Add stochastically scheduled losses to SAM config file.

This function reads the information in the reV_outages key of the sam_sys_inputs dictionary and computes stochastically scheduled losses from that input. If the value for reV_outages is a string, it must have been generated by calling json.dumps() on the list of dictionaries containing outage specifications. Otherwise, the outage information is expected to be a list of dictionaries containing outage specifications. See Outage for a description of the specifications allowed for each outage. The scheduled losses are passed to SAM via the hourly key to signify which hourly capacity factors should be adjusted with outage losses. If no outage info is specified in sam_sys_inputs, no scheduled losses are added.

Parameters:: resource (pd.DataFrame, optional) – Time series resource data for a single location with a pandas DatetimeIndex. The year value of the index will be used to seed the stochastically scheduled losses. If None, no yearly seed will be used.