الفهرس 
chapter 1Only 14 pages are availabe for public view
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Abstract
Real-time transient instability preventive control in power systems is applied to enable the system to withstand future uncertain events in a secure way and keeping its stability. Therefore, transient stability must be assessed as fast as possible in real-time to adequately be improved. Requiring accurate and fast evaluation, catastrophe theory (CT) is applied for assessing the transient stability directly without any assumptions and provide online visualized monitoring for the operating points. A proposed technique is based on contingency scanning and recording in a lookup table as a database for all possible stresses and congestions in the system under study. Stresses are represented by a three-phase fault, as the most severe fault, located frequently in each line of the power system, whereas congestions are considered as a sudden increase of loads.
In order to determine which generators being rescheduled at each fault location, classification and regression tree (CART) technique is used. Then, the required generated power for rescheduled units could be predicted online at any operating condition by using support vector regression machine (SVRM). For doing that, SVRM is trained offline with pre-optimized values that obtained by particle swarm optimization (PSO) technique to guarantee system’s stability. Simulation of New England 39-bus test system verifies the performance and effectiveness of the proposed strategy.