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Dynamic error testing method of electricity meters by a pseudo random distorted test signal

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  • Wang, Xuewei
  • Wang, Jing
  • Yuan, Ruiming
  • Jiang, Zhenyu

Abstract

The complex random characteristics of dynamic loads in smart grid lead to the metering errors exceed the limits of electricity meters used in real field, these errors are called dynamic errors. By analyzing the typical intrinsic characteristics of large power dynamic loads and the nonadaptive linear modulation of compressive sensing (CS), this paper firstly constructs an orthogonal pseudo random measurement (OPRM) matrix to modulate distorted steady-state test signal (DSTS) and then proposes an orthogonal pseudo random measurement distorted dynamic test signal (OPRM-DDTS) with the intrinsic characteristics. In addition, an indirect likelihood function testing method is also proposed to solve the problems of both electricity meter dynamic error testing and dynamic reference electrical energy traceability. At last, a dynamic error testing system is built for verifying the indirect testing method under orthogonal pseudo random distorted dynamic test signal conditions, the dynamic errors of different electricity meters are given. Experimental results show that the orthogonal pseudo random distorted dynamic test signal and the indirect likelihood function testing method are effective for dynamic error testing of electricity meters, meanwhile, the measurement uncertainty of the dynamic error testing system is better than 0.042% (coverage factor k = 2).

Suggested Citation

  • Wang, Xuewei & Wang, Jing & Yuan, Ruiming & Jiang, Zhenyu, 2019. "Dynamic error testing method of electricity meters by a pseudo random distorted test signal," Applied Energy, Elsevier, vol. 249(C), pages 67-78.
    • Handle: RePEc:eee:appene:v:249:y:2019:i:c:p:67-78
    DOI: 10.1016/j.apenergy.2019.04.054
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    References listed on IDEAS

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    Cited by:

    1. Kong, Xiangyu & Zhang, Xiaopeng & Li, Gang & Dong, Delong & Li, Ye, 2020. "An estimation method of smart meter errors based on DREM and DRLS," Energy, Elsevier, vol. 204(C).

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