Abstract

The growing concern about wide area power system disturbances and their impact on power systems have reinforced interest in the new generation of power system modelling. In recent years economical and environmental reasons have forced the transmission systems to be operated closer to their security limits. This has increased the importance of implementing suitable and efficient techniques for online monitoring and prediction of possible voltage collapse in the system prior to its occurrence. During large scale power system disturbance the last line of defense is the load shedding at the stations where the stability margin becomes dangerously low. To do this there is need to use automatic devices which process local signals, detect the decreased margin and activate the load shedding. In this paper a novel method for determination of voltage stability margin in power systems is presented. This method calculates the derivative of apparent power against the admittance. The application of artificial neural network for voltage stability evaluation is also proposed that could be used as early warning system to the power system operator so that necessary action could be taken in order to avoid occurrence of voltage collapse. The developed system has been tested using IEEE-14 bus reliability test system. The proposed technique is able to predict the voltage stability condition of a power system and therefore could be a valuable tool for fast real time voltage stability assessment. (5 pages)

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call