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

Bin Li, Haoran Chen and Ke Hu ()
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Bin Li: Energy Research Institude, Nanjing Institute of Technology, Nanjing 211167, China
Haoran Chen: College of Information and Communication, National University of Defense Technology, Wuhan 430000, China
Ke Hu: College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Energies, 2022, vol. 15, issue 21, 1-8

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.

Keywords: power distribution network; parameter identification; data prepossessing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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