Optimal Power Flow Using a Novel Metamodel Based Global Optimization Method

Abstract

Optimal power flow (OPF) is one of the important task in the operation and control of electric power system. In this paper, a novel metamodel-based global optimization approach has been proposed and applied to the OPF problems. The approach use limited “expensive” sample data points from the original, computationally expensive optimization model to introduce the surrogate models or metamodels, and to effectively use “cheaper” sample points from the metamodel to speed up the search of global optimum with much reduced computation time and limited number of original model simulations, thereby effectively reducing the calculation amount and greatly improving the efficiency of the optimization search. The simulation verification has been carried out on the IEEE 30-bus test system and by comparing with the conventional population based global optimization methods, the numerical results have shown the effectiveness and feasibility of the proposed method.