A Novel Continuous Permutation Method for Wind Power Correlation Analysis

Wind speeds in geographically adjacent areas are highly correlated, which correspondingly leads to wind power correlation. It is essential to consider the wind power correlation for steady-state related calculations in the modern power system with high wind power penetration. This short article presents a novel continuous permutation method for wind power correlation analysis. With the novel eigen-permutation, the proposed method is applicable to tackle the correlation analysis even the correlation matrix of random variables is not positive definite. A continuous permutation is then proposed to reduce the permutation deviation and, hence, to reduce the error of steady-state related calculations. Simulation results show the effectiveness of the proposed method in dealing with the nonpositive definite correlation matrix of the wind speeds. Also, compared to the traditional methods, the proposed method achieves more than an 80% reduction of the general error in the correlation analysis, which also contributes to higher accuracy in the power flow calculation.