Optimal configuration method of distribution network harmonic estimation based on quantum genetic algorithm

With the continuous development of the "double-high" power system, a large number of power electronic devices are continuously connected to the distribution network. The harmonic pollution of the distribution network presents the characteristics of high density, decentralization and whole network. Since the distribution network has a radial weak topology, if the traditional method is used to estimate the harmonic state of the distribution network, the number and cost of power quality monitoring devices required will be huge. In order to ensure the accurate estimation of the harmonic state of the whole network and reduce the number of harmonic monitoring devices, this paper proposes an optimal distribution method for harmonic estimation of distribution network based on quantum genetic algorithm. Firstly, the probabilistic harmonic power flow calculation model is established and the probability distribution of each harmonic state is obtained, and the probability of distribution network harmonics is evaluated. Secondly, the calculation results of probabilistic harmonic power flow are corrected according to the data of a small number of harmonic monitoring points to ensure the accuracy of harmonic estimation. Thirdly, based on the quantum genetic algorithm, the optimal distribution results of harmonic monitoring are obtained with the goal of minimizing the average error of harmonic voltage estimation at all nodes of the distribution network. Finally, the MATLAB software is used to simulate the actual distribution network, and the effectiveness and superiority of the proposed method are verified.