A Filter-Trust Region Interior Point Method For Optimal Power Flow

Optimal power flow (OPF) is an indispensable network analysis and optimization tool for electric power system's operation. It's vital to the system's economy, safety and power quality. There are several ways to solve OPF, such as nonlinear programming, quadratic programming, linear programming, and interior point method and so on.Modern interior point method is one of important algorithms for the OPF, which has some advantages like good convergence and polynomial time complexity. It is extremely be an outstanding algorithm. But when to solve non-convex optimization or when the restrictions of OPF beyond the bound, the convergence of interior point method is challenged. So looking for ways to solve large-scale OPF in quickly and effectively has become a hot research.In recent years, there is a new way called filter method can solve above problems. World-famous mathematician R. Fletcher introduced the concept of dominate and the ideological about filtrate of the filter. Since then, combining the filter method and other methods to solve nonlinear programming problems has become a new hotspot.This paper presents a filter-trust region interior point algorithm, solving the problem that interior point method can't convergence when restrictions beyond the bound in OPF. In this algorithm, the SQP sub model is solved by the modern interior point method, and the trying step is controlled by the trust region, whether to accept it or not is decided by the filter. Numerical tests on five standard IEEE systems are very encouraging. Compare with the primal-dual interior point method, this new algorithm convergence when some restriction beyond the bound. This result is suitable to practical applications.