A primal-dual interior point method for optimal power flow dispatching
RA Jabr, AH Coonick, BJ Cory - IEEE Transactions on Power …, 2002 - ieeexplore.ieee.org
RA Jabr, AH Coonick, BJ Cory
IEEE Transactions on Power Systems, 2002•ieeexplore.ieee.orgIn this paper, the solution of the optimal power flow dispatching (OPFD) problem by a primal-
dual interior point method is considered. Several primal-dual methods for optimal power flow
(OPF) have been suggested, all of which are essentially direct extensions of primal-dual
methods for linear programming. The aim of the present work is to enhance convergence
through two modifications: a filter technique to guide the choice of the step length and an
altered search direction in order to avoid convergence to a nonminimizing stationary point. A …
dual interior point method is considered. Several primal-dual methods for optimal power flow
(OPF) have been suggested, all of which are essentially direct extensions of primal-dual
methods for linear programming. The aim of the present work is to enhance convergence
through two modifications: a filter technique to guide the choice of the step length and an
altered search direction in order to avoid convergence to a nonminimizing stationary point. A …
In this paper, the solution of the optimal power flow dispatching (OPFD) problem by a primal-dual interior point method is considered. Several primal-dual methods for optimal power flow (OPF) have been suggested, all of which are essentially direct extensions of primal-dual methods for linear programming. The aim of the present work is to enhance convergence through two modifications: a filter technique to guide the choice of the step length and an altered search direction in order to avoid convergence to a nonminimizing stationary point. A reduction in computational time is also gained through solving a positive definite matrix for the search direction. Numerical tests on standard IEEE systems and on a realistic network are very encouraging and show that the new algorithm converges where other algorithms fail.
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