By Topic

A Combined GA-ANN Strategy for Solving Optimal Power Flow with Voltage Security Constraint

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Worawat Nakawiro ; Inst. of Electr. Power Syst. (EAN), Univ. of Duisburg Essen, Duisburg ; Istvan Erlich

This paper presents an strategy approach to solve the optimal power flow (OPF) problem for reactive power dispatch which generally requires many power flow calculations. Artificial neural networks are employed to learn in an offline mode and substitute the role of power flow in the OPF which is formulated as a mix integer nonlinear optimization with network loss minimization as the objective. This strategy is shown later in this paper that it helps improve the computational efficiency while slightly deteriorating the quality of solution. Simulation results reveal that the proposed method can speedup the computing procedure for 5 time faster than the conventional OPF while sacrificing a little accuracy. The line (L) indicator is taken into account as the constraint to ensure feasibility of optimal control variables in terms of voltage security margin. Genetic algorithm (GA) is employed as the optimization tool. The effectiveness of the method is verified on IEEE 30-bus system and compared with the conventional OPF solution where power flow is used.

Published in:

2009 Asia-Pacific Power and Energy Engineering Conference

Date of Conference:

27-31 March 2009