Reactive power optimization algorithm based on trust-region global SQP

In order to improve the convergence and calculate optimal results reliably and accurately, a trust-region algorithm based on global sequential quadratic programming (SQP) is presented for reactive power optimization. This method combines global SQP with trust-region method. The method of decomposed inaccurate direction component is adopted to compute trust-region sub problem to guarantee feasible region of this sub problem is not null. The penalty parameter is effectively regulated in merit function to avoid the Marotos effect. This example of the computation shows that this algorithm has global convergence and is fast, accurate and reliable