Interval Data
Interval data is a key input to an energypylinear simulation.
By default, energypylinear accepts interval data for things like electricity prices, carbon intensities and site electricity and heat consumption:
class Site:
"""
The Site asset can optimize many assets together in a single linear program.
All assets are connected to the same site electricity, high and low temperature networks.
"""
def __init__(
self,
assets: list,
electricity_prices: np.ndarray | list[float] | float | None = None,
export_electricity_prices: np.ndarray | list[float] | float | None = None,
electricity_carbon_intensities: np.ndarray | list[float] | float | None = None,
gas_prices: np.ndarray | list[float] | float | None = None,
electric_load_mwh: np.ndarray | list[float] | float | None = None,
high_temperature_load_mwh: np.ndarray | list[float] | float | None = None,
low_temperature_load_mwh: np.ndarray | list[float] | float | None = None,
low_temperature_generation_mwh: np.ndarray | list[float] | float | None = None,
name: typing.Literal["site"] = "site",
freq_mins: int = defaults.freq_mins,
import_limit_mw: float = 10000,
export_limit_mw: float = 10000,
constraints: "list[epl.Constraint] | list[dict] | None" = None,
**kwargs: typing.Any,
):
"""
Initialize a Site.
Args:
assets: Assets to optimize together.
electricity_prices: The price of import electricity in each interval.
Will define both import and export prices if `export_electricity_prices` is None.
export_electricity_prices: The price of export electricity in each interval.
electricity_carbon_intensities: Carbon intensity of electricity in each interval.
electric_load_mwh: Electricity demand consumed by the site.
gas_prices: Price of natural gas, used in CHP and boilers in each interval.
high_temperature_load_mwh: High temperature load of the site.
low_temperature_load_mwh: Low temperature load of the site.
name: The site name.
freq_mins: Size of an interval in minutes.
import_limit_mw: Maximum import power of the site.
export_limit_mw: Minimum import power of the site.
constraints: Additional custom constraints to apply to the linear program.
kwargs: Keyword arguments attempted to be used as extra interval data.
"""
These arguments are passed to the SiteIntervalData object, which is responsible for managing interval data for a site:
import energypylinear as epl
asset = epl.Battery(electricity_prices=[100, 50, 200])
print(asset.site.cfg.interval_data)
electricity_prices=array([100., 50., 200.]) export_electricity_prices=array([100., 50., 200.]) electricity_carbon_intensities=array([0.1, 0.1, 0.1]) gas_prices=array([20, 20, 20]) electric_load_mwh=array([0, 0, 0]) high_temperature_load_mwh=array([0, 0, 0]) low_temperature_load_mwh=array([0, 0, 0]) low_temperature_generation_mwh=array([0, 0, 0]) idx=array([0, 1, 2])
Custom Interval Data
Often you will want to use different interval data for your simulation - for example modelling site network charges.
Additional keyword arguments passed into a site or asset __init__ are attempted to be parsed into interval data. These will be parsed into site interval data, even if passed into an asset.
For example, when we pass in a network_charge argument, we end up with a network_charge attribute on our asset.site.cfg.interval_data object:
import energypylinear as epl
electricity_prices = [100, 50, 200]
asset = epl.Battery(electricity_prices=[100, 50, 200], network_charges=[10, 20, 30])
print(asset.site.cfg.interval_data)
electricity_prices=array([100., 50., 200.]) export_electricity_prices=array([100., 50., 200.]) electricity_carbon_intensities=array([0.1, 0.1, 0.1]) gas_prices=array([20, 20, 20]) electric_load_mwh=array([0, 0, 0]) high_temperature_load_mwh=array([0, 0, 0]) low_temperature_load_mwh=array([0, 0, 0]) low_temperature_generation_mwh=array([0, 0, 0]) idx=array([0, 1, 2]) network_charges=array([10., 20., 30.])
Custom Interval Data in Simulation Results
All custom interval data will appear in the simulation results:
import energypylinear as epl
asset = epl.Battery(electricity_prices=[100, 50, 200], network_charges=[10, 20, 30])
simulation = asset.optimize(verbose=3)
print(simulation.results["site-network_charges"])
Custom Interval Data in Custom Objective Functions
Custom interval data can be used in a custom objective function:
import energypylinear as epl
asset = epl.Battery(electricity_prices=[100, 50, 200], network_charges=[10, 20, 30])
simulation = asset.optimize(
objective={
"terms": [
{
"asset_type": "site",
"variable": "import_power_mwh",
"interval_data": "electricity_prices",
},
{
"asset_type": "site",
"variable": "export_power_mwh",
"interval_data": "electricity_prices",
"coefficient": -1,
},
]
},
verbose=3
)