MHK Wave Plant

MHK Wave Generator class

class hopp.simulation.technologies.wave.mhk_wave_plant.MHKWavePlant(site: SiteInfo, config: MHKConfig, cost_model_inputs: MHKCostModelInputs | None = None, config_name: str = 'MhkWave')

Bases: PowerSource

Marine Hydrokinetic (MHK) Wave Plant.

Parameters:

  • site – Site information

  • config – MHK system configuration parameters

  • cost_model_inputs – An optional dictionary containing input parameters for cost modeling.

site: SiteInfo
config: MHKConfig
cost_model_inputs: MHKCostModelInputs | None
config_name: str
mhk_costs: MHKCosts | None
create_mhk_cost_calculator(cost_model_inputs: dict | MHKCostModelInputs)

Instantiates MHKCosts, cost calculator for MHKWavePlant.

Parameters:

cost_model_inputs – Input parameters for cost modeling.

calculate_total_installed_cost() → float
system_capacity_by_num_devices(wave_size_kw: float)

Sets the system capacity by adjusting the number of devices

simulate(interconnect_kw: float, project_life: int = 25, lifetime_sim=False)

Run the system and financial model

Parameters:

  • interconnect_kw – grid interconnect

  • project_life – Number of years in the analysis period (expected project lifetime)

  • lifetime_sim –

    For simulation modules which support simulating each year of the

    project_life, whether or not to do so; otherwise the first year data is repeated

property device_rated_power: float
property number_devices: int
property wave_power_matrix: List[List[float]]
__init__(site: SiteInfo, config: MHKConfig, cost_model_inputs: MHKCostModelInputs | None = None, config_name: str = 'MhkWave') → None

Method generated by attrs for class MHKWavePlant.

_get_model_dict() → dict

Convenience method that wraps the attrs.asdict method. Returns the object’s parameters as a dictionary.

Returns:

The provided or default, if no input provided, model settings as a dictionary.

Return type:

dict

as_dict() → dict

Creates a JSON and YAML friendly dictionary that can be save for future reloading. This dictionary will contain only Python types that can later be converted to their proper Turbine formats.

Returns:

All key, vaue pais required for class recreation.

Return type:

dict

assign(input_dict: dict)

Sets input variables in the PowerSource class or any of its subclasses (system or financial models)

property benefit_cost_ratio: float

Benefit cost ratio [-] = Benefits / Costs

Benefits include (using present values):

  1. PPA, capacity payment, and curtailment revenues

  2. Federal, state, utility, and other production-based incentive income

  3. Salvage value

Costs: uses the present value of annual costs

calc_capacity_credit_percent(interconnect_kw: float) → float

Calculates the capacity credit (value) using the last simulated year’s max feasible generation profile.

Parameters:

interconnect_kw – Interconnection limit [kW]

Returns:

capacity value [%]

calc_gen_max_feasible_kwh(interconnect_kw: float) → list

Calculates the maximum feasible generation profile that could have occurred (year 1)

Parameters:

interconnect_kw – Interconnection limit [kW]

Returns:

maximum feasible generation [kWh]

calc_nominal_capacity(interconnect_kw: float)

Calculates the nominal AC net system capacity based on specific technology.

Parameters:

interconnect_kw – Interconnection limit [kW]

Returns:

system’s nominal AC net capacity [kW]

property capacity_credit_percent: float

Capacity credit (eligible portion of nameplate) [%]

property capacity_payment: list

Capacity payment revenue [$]

property capacity_price: list

Capacity payment price [$/MW]

property construction_financing_cost: float
copy()
Returns:

new instance

property cost_installed: float

Net capital cost [$]

property debt_payment: tuple

Debt total payment [$]

property degradation: tuple

Annual energy degradation [%/year]

property dispatch

Dispatch object

property dispatch_factors: tuple

Time-series dispatch factors normalized by PPA price [-]

property energy_purchases: tuple

Energy purchases from grid [$]

property energy_sales: tuple

PPA revenue gross [$]

property energy_value: tuple

PPA revenue net [$]

export()
Returns:

dictionary of variables for system and financial

property federal_depreciation_total: tuple

Total federal tax depreciation [$]

property federal_taxes: tuple

Federal tax benefit (liability) [$]

classmethod from_dict(data: dict)

Maps a data dictionary to an attr-defined class.

TODO: Add an error to ensure that either none or all the parameters are passed in

Parameters:

data – dict The data dictionary to be mapped.

Returns:

cls

The attr-defined class.

property gen_max_feasible: list

Maximum feasible generation profile that could have occurred (year 1)

property generation_profile: list

System power generated [kW]

classmethod get_model_defaults() → Dict[str, Any]

Produces a dictionary of the keyword arguments and their defaults.

Returns:

Dictionary of keyword argument: default.

Return type:

Dict[str, Any]

static import_financial_model(financial_model, system_model, config_name)
initialize_financial_values()

These values are provided as default values from PySAM but should be customized by user

Debt, Reserve Account and Construction Financing Costs are initialized to 0 Federal Bonus Depreciation also initialized to 0

property insurance_expense: tuple

Insurance expense [$]

property internal_rate_of_return: float

Internal rate of return (after-tax) [%]

property levelized_cost_of_energy_nominal: float

Levelized cost (nominal) [cents/kWh]

property levelized_cost_of_energy_real: float

Levelized cost (real) [cents/kWh]

property logger
property net_present_value: float

After-tax cumulative NPV [$]

property om_capacity

Capacity-based O&M amount [$/kWcap]

property om_capacity_expense

O&M capacity-based expense [$]

property om_fixed

Fixed O&M annual amount [$/year]

property om_fixed_expense

O&M fixed expense [$]

property om_production

Production-based O&M amount [$/Mwh]

property om_total_expense

Total operating expenses [$]

property om_variable

Production-based O&M amount [$/kWh] For battery: production-based System Costs amount [$/kWh-discharged]

Type:

For non-battery technologies

property om_variable_expense

O&M production-based expense [$]

plot(figure=None, axes=None, color='b', site_border_color='k', site_alpha=0.95, linewidth=4.0)
property ppa_price: tuple

PPA price [$/kWh]

set_overnight_capital_cost(overnight_capital_cost)

Set overnight capital costs [$/kW].

setup_performance_model()

Sets up performance model to before simulating power production. Required by specific technologies

simulate_financials(interconnect_kw: float, project_life: int)

Runs the finanical model for individual sub-systems

Parameters:

  • interconnect_kw – float, Hybrid interconnect limit [kW]

  • project_life – int, Number of year in the analysis period (execepted project lifetime) [years]

Returns:

simulate_power(project_life, lifetime_sim=False)

Runs the system models for individual sub-systems

Parameters:

  • project_life – int, Number of year in the analysis period (execepted project lifetime) [years]

  • lifetime_sim – bool, For simulation modules which support simulating each year of the project_life, whether or not to do so; otherwise the first year data is repeated

Returns:

property system_capacity_kw: float

System’s nameplate capacity [kW]

property system_nameplate_mw: float

System nameplate [MW]

property tax_incentives: list

The sum of Federal and State PTC and ITC tax incentives [$]

property total_installed_cost: float

Installed cost [$]

property total_revenue: list

Total revenue [$]

value(var_name: str, var_value=None)

Gets or Sets a variable value within either the system or financial PySAM models. Method looks in system model first. If unsuccessful, then it looks in the financial model.

Note

If system and financial models contain a variable with the same name, only the system model variable will be set.

value(var_name) Gets variable value

value(var_name, var_value) Sets variable value

Parameters:

  • var_name – PySAM variable name

  • var_value – (optional) PySAM variable value

Returns:

Variable value (when getter)

property annual_energy_kwh: float

Annual energy [kWh]

property capacity_factor: float

System capacity factor [%]

property numberHours: float
class hopp.simulation.technologies.wave.mhk_wave_plant.MHKConfig(device_rating_kw: float, num_devices: int, wave_power_matrix: List[List[float]], fin_model: dict | CustomFinancialModel, loss_array_spacing: float = 0.0, loss_resource_overprediction: float = 0.0, loss_transmission: float = 0.0, loss_downtime: float = 0.0, loss_additional: float = 0.0)

Bases: BaseClass

Configuration class for MHKWavePlant.

Parameters:

  • device_rating_kw – Rated power of the MHK device in kilowatts

  • num_devices – Number of MHK devices in the system

  • wave_power_matrix – Wave power matrix

  • fin_model –

    Optional financial model. Can be any of the following:

    • a dict representing a CustomFinancialModel

    • an object representing a CustomFinancialModel instance

  • layout_mode – TODO

  • loss_array_spacing – Array spacing loss in % (default: 0)

  • loss_resource_overprediction – Resource overprediction loss in % (default: 0)

  • loss_transmission – Transmission loss in % (default: 0)

  • loss_downtime – Array/WEC downtime loss in % (default: 0)

  • loss_additional – Additional losses in % (default: 0)

device_rating_kw: float
num_devices: int
wave_power_matrix: List[List[float]]
fin_model: dict | CustomFinancialModel
loss_array_spacing: float
loss_resource_overprediction: float
loss_transmission: float
loss_downtime: float
loss_additional: float
__init__(device_rating_kw: float, num_devices: int, wave_power_matrix: List[List[float]], fin_model: dict | CustomFinancialModel, loss_array_spacing: float = 0.0, loss_resource_overprediction: float = 0.0, loss_transmission: float = 0.0, loss_downtime: float = 0.0, loss_additional: float = 0.0) → None

Method generated by attrs for class MHKConfig.

_get_model_dict() → dict

Convenience method that wraps the attrs.asdict method. Returns the object’s parameters as a dictionary.

Returns:

The provided or default, if no input provided, model settings as a dictionary.

Return type:

dict

as_dict() → dict

Creates a JSON and YAML friendly dictionary that can be save for future reloading. This dictionary will contain only Python types that can later be converted to their proper Turbine formats.

Returns:

All key, vaue pais required for class recreation.

Return type:

dict

classmethod from_dict(data: dict)

Maps a data dictionary to an attr-defined class.

TODO: Add an error to ensure that either none or all the parameters are passed in

Parameters:

data – dict The data dictionary to be mapped.

Returns:

cls

The attr-defined class.

classmethod get_model_defaults() → Dict[str, Any]

Produces a dictionary of the keyword arguments and their defaults.

Returns:

Dictionary of keyword argument: default.

Return type:

Dict[str, Any]

property logger
class hopp.simulation.technologies.financial.mhk_cost_model.MHKCosts(mhk_config: MHKConfig, cost_model_inputs: MHKCostModelInputs)

Bases: BaseClass

A class for calculating the costs associated with Marine Hydrokinetic (MHK) energy systems.

This class initializes and configures cost calculations for MHK systems based on provided input parameters. It uses the PySAM library for cost modeling which is based on the [Sandia Reference Model Project](https://energy.sandia.gov/programs/renewable-energy/water-power/projects/reference-model-project-rmp/).

Args:

mhk_config: MHK system configuration parameters. cost_model_inputs: Input parameters for cost modeling.

Raises:
ValueError: If any of the required keys in mhk_config or

cost_model_inputs are missing.

mhk_config: MHKConfig
cost_model_inputs: MHKCostModelInputs
_device_rated_power: float
_number_devices: int
_water_depth: float
_distance_to_shore: float
_number_rows: int
_ref_model_num: str
_device_spacing: float
_row_spacing: float
_cable_sys_overbuild: float
initialize()
system_capacity_by_num_devices(wave_size_kw)

Sets the system capacity by adjusting the number of devices.

simulate_costs()
property device_rated_power
property number_devices
property system_capacity_kw
__init__(mhk_config: MHKConfig, cost_model_inputs: MHKCostModelInputs) → None

Method generated by attrs for class MHKCosts.

_get_model_dict() → dict

Convenience method that wraps the attrs.asdict method. Returns the object’s parameters as a dictionary.

Returns:

The provided or default, if no input provided, model settings as a dictionary.

Return type:

dict

as_dict() → dict

Creates a JSON and YAML friendly dictionary that can be save for future reloading. This dictionary will contain only Python types that can later be converted to their proper Turbine formats.

Returns:

All key, vaue pais required for class recreation.

Return type:

dict

classmethod from_dict(data: dict)

Maps a data dictionary to an attr-defined class.

TODO: Add an error to ensure that either none or all the parameters are passed in

Parameters:

data – dict The data dictionary to be mapped.

Returns:

cls

The attr-defined class.

classmethod get_model_defaults() → Dict[str, Any]

Produces a dictionary of the keyword arguments and their defaults.

Returns:

Dictionary of keyword argument: default.

Return type:

Dict[str, Any]

property logger
property ref_model_num
property library_or_input_wec
property cost_outputs: dict
class hopp.simulation.technologies.financial.mhk_cost_model.MHKCostModelInputs(reference_model_num: int, water_depth: float, distance_to_shore: float, number_rows: int, device_spacing: float, row_spacing: float | None = None, cable_system_overbuild: float = 10.0)

Bases: BaseClass

Configuration class for MHK Cost Model.

Parameters:

  • reference_model_num – Reference model number from Sandia Project (3, 5, or 6).

  • water_depth – Water depth in meters

  • distance_to_shore – Distance to shore in meters

  • number_rows – Number of rows in the device layout

  • row_spacing – Spacing between rows in meters (default ‘device_spacing’)

  • cable_system_overbuild – Cable system overbuild percentage (default 10%)

reference_model_num: int
water_depth: float
distance_to_shore: float
number_rows: int
device_spacing: float
row_spacing: float | None
cable_system_overbuild: float
__init__(reference_model_num: int, water_depth: float, distance_to_shore: float, number_rows: int, device_spacing: float, row_spacing: float | None = None, cable_system_overbuild: float = 10.0) → None

Method generated by attrs for class MHKCostModelInputs.

_get_model_dict() → dict

Convenience method that wraps the attrs.asdict method. Returns the object’s parameters as a dictionary.

Returns:

The provided or default, if no input provided, model settings as a dictionary.

Return type:

dict

as_dict() → dict

Creates a JSON and YAML friendly dictionary that can be save for future reloading. This dictionary will contain only Python types that can later be converted to their proper Turbine formats.

Returns:

All key, vaue pais required for class recreation.

Return type:

dict

classmethod from_dict(data: dict)

Maps a data dictionary to an attr-defined class.

TODO: Add an error to ensure that either none or all the parameters are passed in

Parameters:

data – dict The data dictionary to be mapped.

Returns:

cls

The attr-defined class.

classmethod get_model_defaults() → Dict[str, Any]

Produces a dictionary of the keyword arguments and their defaults.

Returns:

Dictionary of keyword argument: default.

Return type:

Dict[str, Any]

property logger