Composite system well-being evaluation based on non-sequential Monte Carlo simulation

The reliability evaluation of composite power systems has historically been assessed using deterministic and probabilistic criteria and methods. The well-being approach was recently proposed in order to combine deterministic criteria with probabilistic methods and evaluates the system by healthy, marginal and risky states. This paper presents an efficient method for composite system well-being evaluation based on non-sequential Monte Carlo simulation. It is assumed that the system is coherent, and the frequency and duration indices are calculated by the conditional probability method. The system adequacy is evaluated by a non-linear power flow solved by the Newton-Raphson method and by an optimal power flow solved by the Interior Points method. Results are presented for the IEEE-RTS system with a constant load and with a variable load curve. It is demonstrated that the proposed method, as well as the assumed hypothesis, are valid and provide an efficient alternative for the well-being analysis of large scale power systems.