Overload Alleviation With Preventive-Corrective Static Security Using Fuzzy Logic

Abstract

This paper presents a concept overview of an automatic operator of electrical networks (AOEN) for real-time alleviation of component overloads and increase of system static loadability, based on state-estimator data only. The control used for this purpose is real-power generation rescheduling, although any other control input could fit the new framework. The key performance metrics are the vulnerability index of a generation unit (VIGS) and its sensitivity (SVIGS), accurately computed using a realistic ac power flow incorporating the AGC model (AGC-PF). Transmission overloads, vulnerability indices and their sensitivities with respect to generation control are translated into fuzzy-set notations to formulate, transparently, the relationships between incremental line flows and the active power output of each controllable generator. A fuzzy-rule-based system is formed to select the best controllers, their movement and step-size, so as to minimize the overall vulnerability of the generating system while eliminating overflows. The controller performance is illustrated on the IEEE 39-bus (New England) network and the three-area IEEE-RTS96 network subjected to severe line outage contingencies. A key result is that minimizing the proposed vulnerability metric in real-time results in increased substantial loadability (prevention) in addition to overload elimination (correction).