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Application of chaos cuckoo search algorithm in harmonic estimation
NIU Haifan, SONG Weiping, NING Aiping, MA Yiyuan
Journal of Computer Applications
2017, 37 (1):
239-243.
DOI: 10.11772/j.issn.1001-9081.2017.01.0239
Concerning slow convergence speed in the later stage, low calculation accuracy and easily falling into the local optimum of basic Cuckoo Search (CS) algorithm, a Cuckoo Search based on Chaos theory (CCS) algorithm was proposed. Firstly, the chaos initialization was used to increase population diversity. Secondly, the chaos disturbance operator was introduced to the local optimal value to jump out of the premature convergence and improve the calculation accuracy. Finally, the global optimization was improved. Four single objective benchmark functions were tested. The simulation results in the best, the worst, average, median and standard deviation value show that CCS algorithm has faster convergence speed and higher convergence precision than CS algorithm. Harmonic is the vital cause of the distortion of current waveform and voltage instability. The analysis of harmonics in power quality analysis is a very important part in power system. The CCS algorithm was applied to harmonic estimation. The experimental results show that the CCS algorithm has better performance compared with the Particle Swarm Optimization (PSO) according to the analysis of harmonic current in mean value and standard deviation.
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