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Summary This paper investigates the problem of how to quantify the harmonic impact of several known harmonic‐producing loads on a particular location of a power network. A multiple linear regression (MLR) analysis‐based technique is proposed to solve the problem. This technique overcomes a major limitation of the correlation‐based methods: the difficulty of finding valid data sets when the number of suspected loads increases. As a result of addressing this limitation, all measured data can be used for harmonic impact study with the proposed method. The proposed method has been verified through simulation and field case study. Additionally, sensitivity study is carried out to address some practical considerations. The results show that the proposed technique is a reliable tool to quantify the individual harmonic impact of several large harmonic‐producing loads. Copyright © 2015 John Wiley & Sons, Ltd.

Grochenig and Madych showed that a Haar-type wavelet basis of L 2 (R n ) can be constructed from the characteristic function xn of a compact set O if and only if fl is an integral self-affine tile of Lebesgue measure one. In this paper we generalize their result to the multiwavelet settings. We give a complete characterization of Haar-type scaling function vectors Xn(x) := [XQi ( x )i • • • J XQr ( X )] T i where ft = (fii, ..., ft r ) is an r-tuple of compact sets in R n . We call Q a self-affine multi-tile because Q^'s tile R n by translation and have the property that each affine image A(Qi) is the union of translates of some fij's. We also construct associated Haar-type multiwavelets , and present examples using various dilation matrices A.

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