Multi-harmonic source localization based on sparse component analysis and minimum conditional entropy

Abstract

Aiming at the fact that the independent component analysis algorithm requires more measurement points and cannot solve the problemof harmonic source location under underdetermined conditions, a new method based on sparse component analysis and minimum conditional entropy for identifying multiple harmonic source locations in a distribution system is proposed. Under the condition that the network impedance is unknown and the number of harmonic sources is undetermined, themeasurement node configuration algorithmselects the node position tomake the separated harmonic currentmore accurate. Then, using the harmonic voltage data of the selected node as the input, the sparse component analysis is used to solve the harmonic currentwaveformunder underdetermination. Finally, the conditional entropy between the harmonic current and the system node is calculated, and the node corresponding to the minimum condition entropy is the location of the harmonic source. In order to verify the effectiveness and accuracy of the proposed method, the simulation was performed in an IEEE 14-node system. Moreover, compared with the results of independent component analysis algorithms. Simulation results verify the correctness and effectiveness of the proposed algorithm.