| In recent years,distributed generation technology based on photovoltaics and wind power has been rapidly developed.As a large number of distributed generation sources are integrated into the power grid,power quality problems have also increased.It is very important to analyze the power quality problems of the distribution network with distributed generation sources,but the traditional power quality evaluation methods and power quality disturbance detection methods are no longer well applicable.Therefore,this paper proposes new methods for comprehensive evaluation and disturbance detection of power quality of distribution network with distributed generation.First,the mathematical model and the power generation principle of photovoltaic arrays and wind turbines are analyzed,the relevant knowledge of maximum power point tracking and grid-connected inverters are introduced.On this basis,a distributed generation grid-connected model based on the MATLAB/Simulink platform is built to verify that the model has Good performance,according to the actual situation,the light intensity and wind speed changes are simulated,and the waveforms of various power quality indicators under environmental changes are obtained.Secondly,in order to assess the power quality of distributed generation sources connected to the distribution network,this paper proposes a comprehensive evaluation method based on the improved analytic hierarchy process(AHP)and the CRITIC method.The D-S evidence theory and the complete consistency matrix are used to optimize the applicability of the algorithm and the calculation steps of AHP.Aiming at the influence of human factors that are difficult to circumvent by subjective weighting method,the CRITIC method is proposed for objective weighting,a comprehensive weighting method is proposed by combining the two methods.and the power quality indicator waveform is processed by the probability method.Probabilistic method is performed on the power quality indicator waveform,and the comprehensive evaluation result of power quality is obtained by using the probability matrix and comprehensive weight of the power quality indicator.Next,in order to assess the problem of power quality disturbance analysis of distributed generation sources,this paper introduces empirical wavelet transform(EWT)and Hilbert transform(HT),and proposes a power quality disturbance detection method based on EWT-HT.Referring to the mathematical model of common power quality disturbance signals,the power quality disturbance signals are generated.Based on this,the two proposed methods are analyzed,and the methods are verified by simulation data.Finally,for the problem of power quality disturbance classification of distributed power sources,this article introduces the multi-scale permutation entropy algorithm(MPE),BP neural network and particle swarm optimization(PSO),the power quality disturbance feature extraction method based on EWT-MPE and the power quality disturbance classification method based on PSO optimized BP neural network are proposed.The feature vector obtained by the EWT-MPE method is used as the input of the algorithm,and the effectiveness of the algorithm is verified through the sample test. |
