A Portable Power Quality Monitoring Approach in Microgrid with Electromagnetic Sensing and Computational Intelligence

Qi Xu, Wenchao Miao, Philip W.T. Pong, Chunhua Liu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Monitoring power quality (PQ) in microgrids is gaining increasing attention in recent years due to the popularity of microgrids and PQ disturbances caused by renewable energies. Many techniques based on artificial neural networks (ANNs) are proposed for monitoring the PQ with no need to pre-set thresholds. However, the necessity of retraining the ANN is a big problem when the electrical parameters vary. This article proposes a new approach to detect and classify the PQ disturbances accurately in multimicrogrids based on electromagnetic sensing and portability-enhanced ANN. The proposed ANN-based approach avoids the retraining of weights, when the voltage, current, and frequency varies with microgrids. Two steps are critical for achieving the portability of the ANN in various microgrids, which are pre-normalization and using the same maximum and minimum feature vectors for feature matrix normalization. Meanwhile, the electromagnetic sensing facilitates non-intrusive monitoring and easy installation. The high accuracy of simulation and experimental results in various scenarios validate the effectiveness and efficiency of this portable and non-invasive approach for monitoring PQ in multimicrogrids without retraining ANN.

Original languageEnglish (US)
Article number9157953
JournalIEEE Transactions on Magnetics
Volume57
Issue number2
DOIs
StatePublished - Feb 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Keywords

  • Artificial neural network (ANN)
  • electromagnetic sensing
  • magnetic sensor
  • microgrid
  • power quality (PQ)

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