Transmission congestion evaluation of power systems using non-sequential Monte Carlo simulation technique

Conventional transmission congestion evaluations are normally based on deterministic approaches. One of the major disadvantages associated with the deterministic approach is that it is unable to fully reflect the impacts of the random component failures. The deterministic approach can only answer whether a congestion occurs or not, but is unable to quantify the severity of the congestion. This paper presents a systematic congestion evaluation technique using a series of reliability indices including congestion probability, congestion frequency, expected congestion capacity, and energy. These indices can be used to characterize the severity of the congestion at both the transmission component and entire system levels. The proposed approach includes a probabilistic congestion evaluation model and a network solution algorithm taking into account the random failures of power system components, such as generating units, transmission lines, and transformers. The entire evaluation approach is based on the non-sequential Monte Carlo technique. The paper also presents study results on the change of congestion severity of transmission line and overall system using the proposed indices and the effect of some of the parameters on the system congestion. Case studies on the IEEE-RTS indicate that the proposed method is effective and feasible. Copyright (c) 2014 John Wiley & Sons, Ltd.