Robust control of Multi Machine Power System Using Intelligent Control methods and their Performance Comparison
Journal Title: Saudi Journal of Engineering and Technology - Year 2017, Vol 2, Issue 11
Abstract
Abstract:This paper is deals with the robustness property of various intelligent control methods namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bacterial Foraging Algorithm (BFA), and Harmony Search Algorithm (HSA) for the design of Power system stabilizer for multi machine power system. The problem of robustly tuning of PID based stabilizer design is formulated as an optimization problem according to the time domain-based objective function with some performance indices which is solved by intelligent control methods that have a strong ability to find the most optimistic results. To demonstrate the effectiveness and robustness of the proposed stabilizers, the design process takes a wide range of operating conditions and system configuration into account. The comparison is carried out in terms of robustness, peak over shoot and settling time of the system dynamic response. For completeness, the performance of conventional controllers is also included. The results of these studies show that the proposed intelligent control methods based PID type stabilizers have an excellent capability in damping power system oscillations and enhance greatly the dynamic stability of the power system in addition to maintaining robustness for a wide range of loading conditions. Keywords:Intelligent Controllers, Power System Stabilizer, PID Controller, Power System Stability
Authors and Affiliations
Abdul Hameed Kalifullah, Sankaran Palani
Keywords
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