The reliability evaluation of composite power systems has been historically 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 the composite reliability evaluation by the well-being approach using the non-sequential Monte Carlo simulation. It is assumed that the system is coherent and the frequency and duration indices are calculated using the conditional probability method. The system adequacy is evaluated by the Newton-Raphson power flow method and the interior point optimal power flow method. Results are presented for the IEEE-RTS system with and without load curve. It is demonstrated that the evaluation method as well as the assumed hypothesis are valid and provides an efficient alternative for the well-being analysis of large scale power systems.
Composite Reliability; Well Being Analysis; Monte Carlo Simulation; Conditional Probability Method; Coherence
