Performance limits for the amplitude estimation of power system harmonics & interharmonics

被引:1
|
作者
Altintasi, Cagri [1 ,2 ]
Orguner, Umut [3 ]
Salor, Ozgul [1 ]
机构
[1] Gazi Univ, Dept Elect & Elect Engn, TR-06570 Ankara, Turkey
[2] Erzincan Binali Yildirim Univ, Dept Elect & Elect Engn, TR-24100 Erzincan, Turkey
[3] Middle East Tech Univ, Dept Elect & Elect Engn, TR-06800 Ankara, Turkey
关键词
power grids; amplitude estimation; frequency estimation; power system harmonics; frequency components; squared frequency differences; Cramer-Rao lower bound; unbiased amplitude estimation; power system interharmonics; CRLB; convergence-time concept; synthetic signals; power grid; TONE PARAMETER-ESTIMATION; KALMAN-FILTER; ALGORITHM; SUBGROUPS;
D O I
10.1049/iet-gtd.2020.0080
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this study, the problem of amplitude estimation of (inter)harmonics is investigated. Specifically performance limits are provided for the accuracy of unbiased amplitude estimation algorithms and for the analysis window size required by an algorithm for achieving and maintaining a desired accuracy. Cramer-Rao lower bound (CRLB) is used for the bounds on the accuracy. Unlike the existing literature concentrating on the asymptotic behaviour of the bounds, the behaviour of CRLBs for small window sizes and close frequency components is investigated. In particular, the (worst) amplitude CRLBs are shown to be inversely proportional to the squared frequency differences for small analysis window sizes and close frequency components. For the bounds on analysis window size, the concept of convergence-time is defined and illustrated. The convergence-times of unbiased amplitude estimation algorithms are then lower bounded by establishing its relationship with CRLBs. The results and ideas are illustrated using both synthetic signals and field data collected from a power grid. Numerical results show that the proposed performance limits are tight and have strong prediction capabilities for amplitude estimation algorithms having prior knowledge about the existing frequencies in the signal.
引用
收藏
页码:4108 / 4121
页数:14
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