Concerning that Cuckoo Search algorithm for Multi-objective Optimization (MOCS) has slow speed in the late iteration and being easy to fall into the local optimum, a new MOCS based on Chaos Cloud Model (CCMMOCS) was proposed. In the evolutionary process, chaos theory was used to optimize the positions of general nests in order to avoid falling into the local optimum; then the cloud model was used to optimize the position of some better nests to improve the accuracy; finally the better value of them was chosen as the best value for optimization. The simulation experiments on five general test functions in error estimated value and diversity index show that CCMMOCS is much better than MOCS, Particle Swarm Optimization algorithm for Multi-objective Optimization (MOPSO) and NSGA-Ⅱ. Its Pareto fronts are closer to the ideal curve than those of other algorithms and the distribution is more uniform.

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.