Research On Summation Models For Harmonic Current With Identical Order From Multi-harmonic Sources

The accurate calculation of the summation of the identical order harmonics of the system of multi-harmonic sources,is an effective means for harmonic elimination.In this thesis,in order to improve the calculation method in international standards,the existing calculation methods of the identical order harmonic current from multi-harmonic sources are sorted and analyzed.Two novel summation models are proposed:a linear summation model based on power factor,and a nonlinear summation model based on BP neural network.Finally,the effectiveness of new models is verified based on field experiments and software simulations.The contents of the thesis are described as follows:(1)The Newton-Raphson algorithm is used to calculate the summation coefficient.First,the calculation method in the international standard IEC 61000-3-6 is introduced in details,and the accuracy of the summation coefficient in the calculation formula is discussed.Then,it is shown that the Newton's iteration method is fast convergent in calculating values by explaining its calculation principle.Finally,a multi-harmonic source system is built by test data,and the measured data are calculated to obtain the value,through the iteration process,the convergence and effectiveness of the method are verified.(2)A linear summation model based on the power factor is proposed.First,the definition of the power factor in different circuit systems is discussed,and the relationship between the power factor and the harmonic distortion is explained.Then,a linear superposition model with power factor as the weighting factor is proposed through circuit theory and mathematical derivation.Finally,the coincidence degree of the weighting factor and the power factor is verified through numerical analysis of the measured data.The calculation accuracy and applicability of the new model are verified through software simulation and test data.(3)A nonlinear summation model based on BP neural network for calculating the summation of the identical order harmonic currents from multi-harmonic sources is proposed.First,the basic principle of BP neural network algorithm is explained.It is considered that the nonlinear mapping ability of the algorithm can be apply to the random harmonic summation.Then,the measured data are sampled and a BP neural network model is obtained through training.Finally,the validity of the new model are verified by error analysis;the nonlinear characteristics of the multi-harmonic source system are verified by multiple linear regression analysis of test data.