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A Data Preprocessing Based on Cluster and Testing of Parameter Identification Method in Power Distribution Network

Author

Listed:
  • Bin Li

    (Energy Research Institude, Nanjing Institute of Technology, Nanjing 211167, China
    These authors contributed equally to this work.)

  • Haoran Chen

    (College of Information and Communication, National University of Defense Technology, Wuhan 430000, China
    These authors contributed equally to this work.)

  • Ke Hu

    (College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China)

Abstract

We present a data prepossessing method for parameter identification based on clustering and hypothesis testing in a power distribution network to successfully achieve a more accurate result. This method considers the similarities of data in both spatial relationship and statistical theory, then builds a sophisticated data processing method to improve the performance of dynamic model-based parameter identification models, i.e., Markov chain Monte Carlo and sequential model-based global optimization. We applied this data processing method to the actual feeder data with no adjustment of the other condition. The experiment shows that our method achieves a 4.8% improvement in accuracy at most.

Suggested Citation

  • Bin Li & Haoran Chen & Ke Hu, 2022. "A Data Preprocessing Based on Cluster and Testing of Parameter Identification Method in Power Distribution Network," Energies, MDPI, vol. 15(21), pages 1-8, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8007-:d:955824
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