Interval Dynamic Harmonic High-Resolution State Estimation for Distribution Networks based on Multi-Source Measurement Data Fusion

An enormous challenge for the harmonic state estimation of distribution network is how to perceive the complex and varied dynamic harmonics in a higher resolution method. To solve this problem, this paper proposes an interval dynamic harmonic high-resolution state estimation method for distribution network based on multi-source measurement data fusion. Firstly, to obtain the typical high-resolution harmonic measurement information of distribution networks under the limited measurement devices, a selection method for the measurement sites of high-resolution power quality monitoring devices (PQMDs) is proposed based on the harmonic electrical distance. On this basis, a multi-source data fusion method based on the time period inclusion index is proposed to establish hybrid interval measurement datasets. Secondly, to improve the efficiency of interval dynamic harmonic state estimation, the interval intermediate variables are introduced to construct the three-stage hybrid interval harmonic measurement equations. Finally, an interval dynamic harmonic high-resolution state estimation method is proposed based on the predictor-corrector method, the IGG-III robust interval Kalman filter (IGGIII-RIKF) is used as the predictor stage, and the forward-backward interval constraint propagation algorithm (FBICP) is used as the corrector stage to realize interval dynamic harmonic high-resolution state estimation. The effectiveness and feasibility of the proposed method have been demonstrated on the IEEE 33-bus system and the IEEE 118-bus system.