Renewable Generator
The epl.RenewableGenerator asset is suitable for modelling wind or solar generation.
Use
import energypylinear as epl
asset = epl.RenewableGenerator(
electricity_prices=[1.0, -0.5],
electric_generation_mwh=[100, 100],
electric_generation_lower_bound_pct=0.5,
name="wind",
)
simulation = asset.optimize(objective="price")
assert all(
simulation.results.columns
== [
"site-import_power_mwh",
"site-export_power_mwh",
"site-electricity_prices",
"site-electricity_carbon_intensities",
"site-high_temperature_load_mwh",
"site-low_temperature_load_mwh",
"site-low_temperature_generation_mwh",
"site-gas_prices",
"site-electric_load_mwh",
"wind-electric_generation_mwh",
"total-electric_generation_mwh",
"total-electric_load_mwh",
"total-high_temperature_generation_mwh",
"total-low_temperature_generation_mwh",
"total-high_temperature_load_mwh",
"total-low_temperature_load_mwh",
"total-gas_consumption_mwh",
"total-electric_charge_mwh",
"total-electric_discharge_mwh",
"total-spills_mwh",
"total-electric_loss_mwh",
"site-electricity_balance_mwh",
]
)
This renewable generator will turn down when electricity prices are negative.
Validation
A natural response when you get access to something someone else built is to wonder - does this work correctly?
This section will give you confidence in the implementation of the renewable generator asset.
Carbon Dispatch Behaviour
Let's optimize the renewable generator asset in two intervals:
- a positive import electricity carbon intensity of
1.0 tC/MWh, - a negative import electricity carbon intensity of
-0.5 tC/MWh.
If we optimize our epl.RenewableGenerator asset with a lower bound on the electricity generation of 1.0, we generate the full 100 MW in each interval:
import energypylinear as epl
electricity_carbon_intensities = [1.0, -0.5]
electric_generation_mwh=[100, 100]
electric_generation_lower_bound_pct=1.0
asset = epl.RenewableGenerator(
electricity_carbon_intensities=electricity_carbon_intensities,
electric_generation_mwh=electric_generation_mwh,
name="wind",
electric_generation_lower_bound_pct=electric_generation_lower_bound_pct
)
simulation = asset.optimize(objective="carbon", verbose=3)
print(simulation.results[
[
"site-electricity_carbon_intensities",
"site-export_power_mwh",
"wind-electric_generation_mwh",
]
])
site-electricity_carbon_intensities site-export_power_mwh wind-electric_generation_mwh
0 1.0 100.0 100.0
1 -0.5 100.0 100.0
If we change our lower bound to 0.5, our renewable generator asset will generate less electricity during the second, negative carbon intensity interval:
import energypylinear as epl
electricity_carbon_intensities = [1.0, -0.5]
electric_generation_mwh=[100, 100]
electric_generation_lower_bound_pct=0.5
asset = epl.RenewableGenerator(
electricity_carbon_intensities=electricity_carbon_intensities,
electric_generation_mwh=electric_generation_mwh,
name="wind",
electric_generation_lower_bound_pct=electric_generation_lower_bound_pct
)
simulation = asset.optimize(objective="carbon", verbose=3)
print(simulation.results[
[
"site-electricity_carbon_intensities",
"site-export_power_mwh",
"wind-electric_generation_mwh",
]
])