A Parameter Measurement Method for Power System: Modeling and Its HGA-Based Solution

The automatic devices that are widely used in power systems impel a real need for reliable computational algorithms to improve the accuracy of electrical parameter measurement. This paper deals with a hybrid genetic algorithm (HGA)-based measurement method. According to the typical expression of fault signal in power systems, an extremum optimization model that involves electrical parameters and various error parameters is built up firstly in this paper. A HGA-based measurement method is worked out next, which embeds Quasi-Newton method into the process of global search of Genetic Algorithm (GA) and adopts nonuniform mutation strategy. This method takes full advantages of both GA and classical iterative algorithm, which is insensitive to the initial value and has high convergence rate and calculating accuracy. It can get the power system parameters such as amplitudes, phases, work frequency and harmonics with high precision. Some examples are given to demonstrate the feasibility and validity of the proposed method. With notable accurate parameter measurement, it makes a solid foundation of the power system´s further supervision, measurement and control.