Harmonic State Estimation for Distribution Networks Based on Multi-Measurement Data

Accurate harmonic state estimation (HSE) is necessary to mitigate harmonic issues in power distribution networks. However, existing HSE methods face difficulties in solution of state equation that the measured data is insufficient with limited monitors. Therefore, this study proposes a HSE algorithm for distribution networks based on multi-measurement data. Firstly, a harmonic source location method based on mutual information and distribution network partition is proposed to reduce the number of state variables and to solve the state equation. Thus, HSE with low resolution (15 min) is realized. Secondly, a HSE method with enhanced resolution is developed. This method establishes maximum entropy principle models for harmonic currents injected into buses, calculates the probability density function (PDF) of the harmonic current, and realizes optimal interpolation of the harmonic data to enhance the resolution of the HSE (3 min) according to the PDF. Finally, the applicability and effectiveness of the proposed method are verified using an IEEE-33 test system simulation and a real power system in South China.