Data‐driven partition control strategy for harmonic distortion and voltage unbalance. Issue 9 (28th February 2018)

• Record Type: Journal Article
• Authors: Yu, Hao; Jia, Qingquan; Sun, Haidong; Dong, Haiyan
• Is Part Of: IET generation, transmission & distribution. Volume 12:Issue 9(2018)
• Page Start: 2038
• Page End: 2045
• Publication Date: 2018-02-28
• Subjects: harmonic distortion -- power harmonic filters -- power distribution faults -- power distribution control -- active filters -- piecewise linear techniques -- feature extraction -- time series -- matrix algebra -- pattern matching; data‐driven partition control strategy -- harmonic distortion -- voltage unbalance -- disturbance source decentralisation -- disturbance source penetration -- distribution networks expansion -- global optimisation controls -- node disturbance data -- active power filter allocation -- harmonic distortion suppression -- multidimensional piecewise linear representation -- local extreme points -- univariate disturbance time series -- UDTS -- multivariate DTS -- MDTS -- parameter matrix -- DTS pattern representation -- feature distance method -- FD method -- pattern matching -- APF allocation -- 14‐bus distribution system; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2017.1297
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Local controls for harmonic distortion and voltage unbalance have become inapplicable due to the increasing penetration and decentralisation of disturbance sources. The complication and expansion of distribution networks cause difficulties in measuring certain system parameters, which reduce the practicability of global optimisation controls. Accordingly, this study introduces a partition control strategy driven by the disturbance data of nodes, which is used to allocate active power filters (APFs) to individually or simultaneously suppress harmonic distortion and voltage unbalance in distribution networks. A multidimensional piecewise linear representation based on local extreme points is proposed to extract the trend features of univariate disturbance time series (UDTS) and multivariate DTS (MDTS). Trend features, disturbance severities, and subsection lengths are used to establish a parameter matrix as the pattern representation of DTS. A feature distance (FD) method is developed to implement pattern matching on UDTS or MDTS to measure the coupling degrees of single or integrated disturbance among nodes. Area division and APF allocation are performed based on the coupling degrees. Case studies on a 14‐bus distribution system are conducted to verify the rationality of the partition control strategy and the accuracy of the FD method.