Application of Genetic Algorithm in Power System Optimization

The application of system optimization is critical in the power system, however it has an issue with erroneous performance positioning. The typical Neural network algorithms is unable to address the optimization positioning issue in the power system, and the result is insufficient. As a result, a Genetic algorithm-based application of power system optimization is provided, and the application of power system optimization is assessed. To begin, the simulation biology theory is used to discover the influencing elements, and the indicators are split based on the application of system optimization’s needs to decrease interference factors in the application of system optimization. The simulation biology theory is then used to create a Genetic algorithm application of system optimization scheme, and the outcomes of the application of system optimization are thoroughly examined. The MATLAB simulation results reveal that, under particular evaluation conditions, the Genetic algorithm outperforms the standard Neural network algorithms in terms of application of system optimization accuracy and time of influencing variables.