ams.routines.pypower.DCPF1#
- class ams.routines.pypower.DCPF1(system, config, **kwargs)[source]#
DC Power Flow using PYPOWER.
This routine provides a wrapper for running DC power flow analysis using the PYPOWER. It leverages PYPOWER's internal DC power flow solver and maps results back to the AMS system.
Notes
This class does not implement the AMS-style DC power flow formulation.
For detailed mathematical formulations and algorithmic details, refer to the MATPOWER User's Manual, section on Power Flow.
Added in version 1.0.10.
- __init__(system, config, **kwargs)[source]#
Initialize the routine.
- Parameters:
- systemOptional[Type]
The system object associated with the routine.
- configOptional[dict]
Configuration dictionary for the routine.
Methods
addConstrs(name, e_str[, info])Add a Constraint to the routine at runtime.
addRParam(name[, tex_name, info, src, unit, ...])Add RParam to the routine.
addService(name, value[, tex_name, unit, ...])Add ValueService to the routine.
addVars(name[, model, shape, tex_name, ...])Add a variable to the routine.
dc2ac([kloss])Convert the DC-based results with ACOPF.
disable(name)Disable a constraint by name.
doc([max_width, export])Retrieve routine documentation as a string.
enable(name)Enable a constraint by name.
export_csv([path])Export scheduling results to a csv file.
export_json([path])Export scheduling results to a json file.
formulation_summary([return_rows])Print (or return) a per-item table of the live formulation source.
get(src, idx[, attr, horizon])Get the value of a variable or parameter.
init(**kwargs)Initialize the routine.
load_json(path)Load scheduling results from a json file.
run(**kwargs)Run the DC power flow using PYPOWER.
set(src, idx[, attr, value])Set the value of an attribute of a routine parameter.
solve(**kwargs)Solve by PYPOWER.
summary(**kwargs)Summary interface
unpack(res, **kwargs)Unpack results from PYPOWER.
update([params, build_mats])Update the values of Parameters in the optimization model.
Attributes