In this study, an optimal Tree-Seed Algorithm (TSA) algorithm-based Proportional-Integral-Derivative (PID) controller is proposed for automatic voltage regulator (AVR) system terminal tracking problem. PID controller gains K p, K i, and K d are optimized with the proposed TSA algorithm based on different objective functions. The TSA-based optimal PID controller's performance is compared with numerous PID controllers, which were developed using different meta-hermetic optimization algorithms in the literature. Several analysis methods including root locus, bode analysis, robustness, and disturbance rejection are studied and compared with reported works in the literature. It is shown that there is still a research gap to improve the tracking performance of the AVR system due to its importance in electrical systems. According to the obtained comparison results, it has been revealed that the proposed TSA-based PID controller improves tracking properties under load change thus it can be effectively used for synchronous generator automatic voltage regulator terminal voltage stability.
Abstract:A genetic algorithm (GA)-based sliding mode controller is proposed to improve the voltage stability of a power system with a static var compensator. The proposed controller is examined for improving the load bus voltage, which changes under different demanding powers, and its performance for transient analysis is compared with the ZieglerNichols proportional-integral (ZNPI), Lyapunov-based sliding mode control (LASMC), and GA-based proportionalintegral-derivative (GAPID) controllers. The dynamic equations, consisting of a 2-bus nonlinear system, are converted to a mathematical description of sliding mode techniques. The optimum values of the sliding mode controller and proportional-integral-derivative (PID) coefficients that are required are calculated using the GA technique. Output voltage performances are obtained based on the demanding powers, which are at a constant variation. In this process, sliding mode, ZNPI, GAPID, and LASMC controllers are preferred in order to control the system. The results show that the GA sliding mode controller method is more effective than the ZNPI, GAPID, and LASMC controllers in voltage stability enhancement.
In this study, in order to control the voltage of the Western System Coordinating Council (WSCC) system, a sliding mode control has been used. First, the active and reactive power values, voltage and angle values of the loadbuses have been calculated. The load-buses which their voltage levels are lower than 1 pu has been identified. After that, by considering one of these load-buses, the system is transformed to the system with two load-buses and the sliding mode control model has been obtained. The sliding mode parameters have been obtained by using genetic algorithm (GA) optimization technique. From the results of simulations of this model, it is shown that the voltage of the load-buses reaches at 1 pu with a very low error.
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