Example 2¶
WEC Integration and Time Series Analysis¶
This notebook demonstrates WEC-Grid's core functionality for wave energy converter integration:
- Setting up a grid system with WEC devices
- Running time-domain simulations
- Analyzing WEC performance and grid impact
This example uses the IEEE 30 case system with RM3 wave energy converters.
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import wecgrid
example2 = wecgrid.Engine()
example2.case("grid_models/IEEE_30_bus.raw")
example2.load(["pypsa"])
example2
import wecgrid
example2 = wecgrid.Engine()
example2.case("grid_models/IEEE_30_bus.raw")
example2.load(["pypsa"])
example2
Out[1]:
Engine: ├─ Case: IEEE 30 bus ├─ PyPSA: Loaded ├─ PSS/E: Not Loaded ├─ WEC-Farms/WECs: 0 - 0 └─ Buses: 30 Sbase: 100.0 MVA
Create WEC-Farm with a WEC Devices¶
Lets create a WEC Farm with a ten RM3 devices. The RM3 simulation data was pulled from the pre-loaded WEC-Grid database found here. Specifics about the RM3 run can be found in the documentation.
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#Information about the wec-sim runs in database can accessed using
example2.database.wecsim_runs()
#Information about the wec-sim runs in database can accessed using
example2.database.wecsim_runs()
Out[2]:
| wec_sim_id | model_type | sim_duration_sec | delta_time | wave_height_m | wave_period_sec | wave_spectrum | wave_class | wave_seed | simulation_hash | created_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2 | LUPA | 86400.0 | 0.1 | 2.5 | 8.0 | PM | irregular | 8 | LUPA_2.5m_8.0s_8 | 2025-08-19 19:59:49 |
| 1 | 1 | RM3 | 86400.0 | 0.1 | 2.5 | 8.0 | PM | irregular | 94 | RM3_2.5m_8.0s_94 | 2025-08-19 19:45:01 |
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example2.apply_wec(
farm_name = "WEC-Farm-RM3",
size = 10, # ten RM3 in WEC farm
wec_sim_id = 1, # RM3 run id
bus_location=31, # create a new bus for farm
connecting_bus = 1, # Connect to bus 1 or swing bus
)
example2.apply_wec(
farm_name = "WEC-Farm-RM3",
size = 10, # ten RM3 in WEC farm
wec_sim_id = 1, # RM3 run id
bus_location=31, # create a new bus for farm
connecting_bus = 1, # Connect to bus 1 or swing bus
)
WEC Farm added: WEC-Farm-RM3
Review updated Grid¶
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grid = example2.pypsa.grid
grid
grid = example2.pypsa.grid
grid
Out[4]:
GridState: ├─ Components: │ ├─ bus: 31 components │ ├─ gen: 7 components │ ├─ line: 38 components │ └─ load: 21 components ├─ Case: IEEE 30 bus └─ Modeler: pypsa
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example2.plot.sld()
example2.plot.sld()
SLD Data Summary: Buses: 31 Lines: 38 Generators: 7 Loads: 21
Run Time Series Simulation¶
Execute a time-domain simulation to analyze WEC power injection and grid response over 24 hours.
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example2.simulate() # takes some time!
example2.pypsa.report
example2.simulate() # takes some time!
example2.pypsa.report
PyPSA Simulating: 100%|██████████| 288/288 [02:51<00:00, 1.68step/s]
Out[6]:
SolveReport: ├─ Converged: Successful ├─ Simulation Time: 171.54 s ├─ Num Steps: 288 ├─ Case: IEEE 30 bus └─ Modeler: pypsa
Analyze and Visualize Results¶
Create comprehensive plots to analyze WEC performance and grid impact over time.
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plot = example2.plot
plot.bus()
plot.bus(bus=['Bus_1']) # Swing Bus
plot.bus(bus=['Bus_31']) # WEC-Farm Bus
plot.bus(parameter='v_mag',bus=['Bus_31'])
plot = example2.plot
plot.bus()
plot.bus(bus=['Bus_1']) # Swing Bus
plot.bus(bus=['Bus_31']) # WEC-Farm Bus
plot.bus(parameter='v_mag',bus=['Bus_31'])
Out[7]:
(<Figure size 1200x600 with 1 Axes>,
<AxesSubplot:title={'center':'PYPSA: Bus Voltage Magnitude'}, xlabel='Time', ylabel='Voltage (pu)'>)
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plot.gen()
plot.gen(gen=['Gen_1']) # Swing Generator
plot.gen(gen=['Gen_7']) # WEC-Farm Generator
plot.gen()
plot.gen(gen=['Gen_1']) # Swing Generator
plot.gen(gen=['Gen_7']) # WEC-Farm Generator
Out[8]:
(<Figure size 1200x600 with 1 Axes>,
<AxesSubplot:title={'center':'PYPSA: Generator Active Power'}, xlabel='Time', ylabel='Active Power [pu]'>)
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plot.wec_analysis()
plot.wec_analysis()
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