Load Feasible Region Determination by Using Adaptive Particle Swarm Optimization

Abstract

The proposed of a method for determination a space of feasible boundary points, by using adaptive particle swarm optimization in order to solve the boundary region which represented by particle swarm points. This paper present method supports the calculation for a large-scale power system. In case of contingency will illustrate the point on the plane x-axis and y-axis dimensional power flow space. In addition, This method not only demonstrates the optimal particle swarm through the boundary tracing method of the feasible region but also present the boundary points are obtained by optimization. Moreover, receding loss function and operational constraints simultaneously are considering. The formulation points of feasible region can also determine the boundary points which is the contingencies are taken into account and the stability of load demand that system allows to execute in the normal requirements. These feasible points defined the limit of control actions and the robustness of operating points. Finally, the test systems shown the impact of system parameters on the load shedding, generator voltage control, and load level.