Power Measurement Using Adaptive Chirp Mode Decomposition for Electrical Vehicle Charging Load

Haili Ding, Rui Tian, Jinfei Wang and Xiaomei Yang ()
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Haili Ding: Marketing Service Center (Measurement Center), Ningxia Electric Power Co., Ltd., National Grid of China, Yinchuan 750001, China
Rui Tian: Marketing Service Center (Measurement Center), Ningxia Electric Power Co., Ltd., National Grid of China, Yinchuan 750001, China
Jinfei Wang: The College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Xiaomei Yang: The College of Electrical Engineering, Sichuan University, Chengdu 610065, China

Energies, 2023, vol. 16, issue 14, 1-13

Abstract: Due to nonlinear components in the charging piles of electric vehicles, harmonics and nonstationary signals in the electric vehicle charging load bring voltage and current distortion, seriously affecting the accuracy of the power-related calculation in nonsinusoidal environments. This paper proposed a new approach to calculate the active power and root mean square values from decomposed components using the adaptive chirp mode decomposition (ACMD) method on voltage and current. The advantage of the ACMD-based method is that it correctly provides the power-related quantities of harmonics or nonstationary components for the electric vehicle charging load. The performance of the proposed method was verified using synthetic signals and simulation tests. The experimental results presented better estimations for each quantity defined in IEEE Standard 1459-2010, compared with the discrete wavelet transform approach.

Keywords: electric vehicles; power calculation; harmonics; nonstationary; adaptive chirp mode decomposition (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: 2023
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