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Solves a DC optimal power flow.
Inputs are an OPF model object, a PYPOWER options dict and a dict
containing fields (can be empty) for each of the desired optional output
fields.
Outputs are a results dict, success flag and
raw output dict.
results is a PYPOWER case dict (ppc) with the usual
baseMVA, bus branch, gen, gencost fields, along with the following
additional fields:
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order see 'help ext2int' for details of this field
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x final value of optimization variables
(internal order)
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f final objective function value
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mu shadow prices on ...
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var
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l lower bounds on variables
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u upper bounds on variables
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lin
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l lower bounds on linear constraints
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u upper bounds on linear constraints
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g (optional) constraint values
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dg (optional) constraint 1st derivatives
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df (optional) obj fun 1st derivatives (not yet
implemented)
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d2f (optional) obj fun 2nd derivatives (not yet
implemented)
success is True if solver converged
successfully, False otherwise.
raw is a raw output dict in form returned by MINOS
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xr final value of optimization variables
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pimul constraint multipliers
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info solver specific termination code
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output solver specific output information
See Also:
opf, qps_pypower
- Authors:
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Ray Zimmerman (PSERC Cornell),
Carlos E. Murillo-Sanchez (PSERC Cornell & Universidad
Autonoma de Manizales),
Richard Lincoln
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