A Multi-Objective Genetic Algorithm for Voltage-Stability Reinforcement of Power Systems

J.S. Huang (Australia)


Multi-objective optimization, genetic algorithm, Lagrange multiplier method, fuzzy logic performance index


In the paper the author presents a genetic-algorithm-based optimization scheme for voltage stability enhancement of power systems under critical operation conditions. The placement of SVCs (static VAR (Volt-Ampere Reactive) compensators) in a power system has been posed as a multi-objective optimization in terms of maximum worst case reactive margin, highest load voltages at the critical operating points, minimum real power losses and lowest device costs. During the genetic algorithm search for the optimal solution, the most critical disturbance scenario is estimated with the configuration of the original power system and each candidate SVC placement. By using this estimation, the SVC placement can be greatly simplified. With a fuzzy performance index, the multi-objective optimization can be further transformed into a constrained problem with a single non-differentiable objective function containing both continuous and discrete variables.

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