Curtailment results from SWITCH post-processing

[YifanLi86]

Post-calculate curtailment data from SWITCH results, summarize by type.

• Extract DispatchGen variable value from the pickle file. In .pickle file, the decision variable to use to get generation output level is DispatchGen. Same pickle file data extraction with: #39 (comment). All solution information stored in the same location.
• Get all unit's maximum capacity. For existing unit, it is available in gen_build_predetermined.csv in input processing. For expansion unit, it is described (here)[https://github.com/Breakthrough-Energy/SwitchWrapper/issues/39#issuecomment-840920303]
• Get capacity factors defined in variable_capacity_factors.csv for each generation unit and timepoint, and calculate EnergyAvailable using capacity factors multiplied by Maximum Generation Capacity.
• Calculate curtailment using equation "curtailment = EnergyAvailable - DispatchGen" for each renewable generation unit and timestamp.
• Summarize curtailment by zone/state and type

[kasparm]

@YifanLi86 can you please provide more details:

1. Input: DispatchGen form pkl, EnergyAvailable column ? in variable_capacity_factors.csv
2. Process: Curtailment = EnergyAvailable - DispatchGen for each unit(?) and timepoint.
3. Output value, table: ? (Provide column and row description (Ex. Generator output per hour: row: hour, column: Generator Index))

[danielolsen]

>>> from postreise.analyze.generation.curtailment import calculate_curtailment_time_series
>>> from switchwrapper.switch_extract import get_output_scenarios
>>>
>>> # Extract grid and time-series data from outputs
>>> scenarios = get_output_scenarios(path_to_switch_project_folder)
>>> output_scenario = scenarios[2030]
>>> output_grid = output_scenario.get_grid()
>>> output_plant = output_grid.plant
>>>
>>> # Calculate curtailment by zone/type
>>> curtailment = calculate_curtailment_time_series(output_scenario)
>>> zone_id_curtailment = curtailment.sum().groupby([output_plant.zone_id, output_plant.type]).sum().unstack().fillna(0)
>>> zone_id_curtailment
type           solar         wind  wind_offshore
zone_id
201         35.81604      0.00000            0.0
202       2315.51442      0.00000            0.0
203      20546.51868      0.00000            0.0
204          0.00000      0.00000            0.0
205        480.85956      0.00000            0.0
206       3931.54614  11496.16980            0.0
207       8394.61788   4455.54738            0.0
208       1722.01086      0.00000            0.0
209       4602.52710   5357.79054            0.0
210          0.00000      0.00000            0.0
211          0.00000      0.00000            0.0
212          0.00000      0.00000            0.0
213          0.00000      0.00000            0.0
214          0.00000   9980.40132            0.0
215          0.00000    173.53098            0.0
216          0.00000      0.00000            0.0
>>>
>>> # Calculate curtailment by state/type
>>> zone_name_curtailment = zone_id_curtailment.rename(output_grid.id2zone)
>>> zone_states = zone_name_curtailment.index.map(output_grid.model_immutables.zones["loadzone2state"])
>>> state_curtailment = zone_id_curtailment.groupby(zone_states).sum()
>>> state_curtailment
type              solar         wind  wind_offshore
zone_id
Arizona      4602.52710   5357.79054            0.0
California  33353.54226  15951.71718            0.0
Colorado        0.00000      0.00000            0.0
Idaho           0.00000   9980.40132            0.0
Montana         0.00000    173.53098            0.0
Nevada       1722.01086      0.00000            0.0
New Mexico      0.00000      0.00000            0.0
Oregon       2315.51442      0.00000            0.0
Texas           0.00000      0.00000            0.0
Utah            0.00000      0.00000            0.0
Washington     35.81604      0.00000            0.0
Wyoming         0.00000      0.00000            0.0