Adaptive Power System Stabilizers Using Artificial Immune System
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Abstract
Power system stabilizers (PSSs) are used to damp intra-area and inter-area oscillations in a power network. They provide effective supplementary control by supplying auxiliary control signals to the excitation system of the generators. The proper tuning of PSSs has a significant influence on its effectiveness in providing the required damping under different operating conditions and disturbances. Various algorithms have been successfully implemented to simultaneously design multiple optimal PSSs in power systems. As the power network's operating conditions change, the performance of PSSs degrade. Optimal PSS parameters obtained using bacteria foraging algorithm (BFA) have shown to successfully damp out system oscillations during disturbances for various operating conditions. This paper presents an artificial immune system based PSS design to adapt the optimal parameters of the PSSs. The innate immunity to system oscillations is provided by the optimal PSS parameters while the adaptive immunity is provided by adapting the PSS parameters during transients. The effectiveness of the 'adaptive' optimal PSSs (APSSs) is evaluated on the two-area four-machine benchmark power system
