A novel method is used for assessing the harmonic emission level, which is based on the partial least-squares (PLS) regression with data envelopment analysis (DEA). Based on measuring the harmonic voltage and current at the point of common coupling (PCC) and removing the inefficiency data with DEA, regression coefficients are worked out through partial least-squares algorithm. Consequently the harmonic emission level of customer is calculated.The proposed approach removes the effect of outlying data points and gets accurate estimation results. The simulation results prove that the proposed method is more effective than PLS.
Principal Component Regression and Its Application in Power Harmonic Emission Level Evaluation
