Well-being analysis for composite generation and transmission systems

This paper presents a new approach to evaluating the health of composite generation and transmission systems. A well-being framework is used to classify the system states into healthy, marginal and at risk, according to a pre-defined deterministic criterion. In order to combine deterministic and probabilistic concepts, the proposed methodology uses a nonsequential Monte Carlo simulation, a multilevel nonaggregate Markov load model and new test functions to estimate the well-being indices. These test functions are based on an estimating process, designated as the one-step forward state transition, which is very flexible and efficient. Case studies on the IEEE-RTS (Reliability Test System) and on a modification of this system are presented and discussed.