Using artificial neural networks for load shedding to alleviate overloaded lines

Previous work by the authors (see Proc. First Internat. Forum on Appls. of Neural Nets to Power Systs., Seattle, p.205-9, 1991) has shown the viability of using artificial neural networks (ANNs) for the early detection and control of overloaded lines. This paper focuses on the development of an artificial neural network based scheme for intelligent load shedding. The load shedding scheme consists of localized detectors that consider parameters of the power system during an emergency. The research was developed using the IEEE 30 bus test system which incorporates a design of net import and export regions. The approach is implemented in the import area of the system. The purpose of the scheme is to detect overloaded lines and make intelligent decisions about where within the topology of the system the load should be dropped and how much load to shed. The proposed scheme is designed to avoid unintentional separation of the system by fast, proactive, and adaptive control