Sensitivity-based reliability coordination for power systems considering wind power reserve based on hybrid correlation control method for wind power forecast error

With the derated output, the wind farms provide the active power reserve and contribute to power system reliability. The impacts of the wind power forecast error (WPFE) on the capability of reserve provision and power system reliability may be quantified by the sensitivity model. For reliability and sensitivity analysis, the samples of the WPFE are usually manually generated instead of the historical data, thus the correlation control methods should be used to ensure that the samples have the same correlation with the historical data. The existing methods are either inaccurate or computationally expensive. In this article, a hybrid method for correlation control is proposed to reduce the calculation effort while ensuring the accuracy. The univariate nonstandard third-order polynomial normal transformation (NSTPNT) method is extended to multivariate one to produce the non-normal sample which is applied as the initial population of the genetic algorithm with local search to improve the initial fitness. The analytical sensitivity model of power system reliability with respect to the derated proportion of the wind farms and the reserve capacity provided by the conventional generators is proposed. The coordination model describing the relationship among the expected demand not served and the reserves of the wind power and the conventional generators is proposed. In numerical results, the computational effort of the proposed hybrid method is analyzed. The accuracies of the sensitivity model and the coordination model are validated. The contributions of the wind power deration and the conventional generator's reserve on the reliability are compared.