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Keywords
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SSSC, Cuckoo Optimization Algorithm,
Particle Swarm Optimization, Single Machine Power
System, Low Frequency Oscillation Damping.
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Abstract
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In this study a linearized Heffron-Phillips model of a single machine power system installed with a static synchronous series compensator (SSSC) has been presented. The optimal selection of the parameters for the SSSC controller is converted to an optimization problem which is solved by recently developed cuckoo optimization algorithm (COA). COA, as a new evolutionary optimization algorithm, is used in multiple applications. This optimization algorithm has a strong ability to find the most optimistic results for dynamic stability improvement. The effectiveness of the proposed controller for damping low frequency oscillations (LFO) is tested to variations in system loading and results compared with particle swarm optimization (PSO). The results analysis reveals that COA minimized multi objective cost function and improved dynamic stability, better than PSO. Also, performance of proposed COA controller in 10 times run is the same as in 1 time run. In addition, designed COA based SSSC damping controller has an excellent capability in damping low frequency oscillations and enhances rapidly and greatly the dynamic stability of the power systems.
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