Modeling and Control of Overloaded Transmission Networks

Abstract

This thesis presents methods for the on-line control and off-line study of power systems and other large-scale networks which are operated in an emergency state characterized by branch overloads. The control objective is to return the network to a normal operating state, that is, to return the branch flows to their normal limits without violating the overload capacity of any branch. A dynamic network model is developed which permits the passing of overloads among the branches during the control period. Multistage rescheduling for emergency state control of power systems is formulated which, in contract to previously proposed static rescheduling algorithms, accounts for the dynamic constraints of the system and takes advantage of the overload capacity of the transmission lines. To initiate an on-line response to overloads before the results of sophisticated rescheduling algorithms could be available, a short-term generation ramping algorithm is presented. A feedback control for clearing overloads is developed based on repeated short-term ramping solutions and it is demonstrated that this feedback control provides solutions similar to those obtained from the multistage formulation. Finally, network aggregation and decomposition concepts are introduced which suggest directions for future research relating the network structure to the controls required to remove overloads.