Representation of Wind and Load Correlation in Non-Sequential Monte Carlo Reliability Evaluation

Representation of Wind and Load Correlation in Non-Sequential Monte Carlo Reliability Evaluation

Reliability and Risk Evaluation of Wind Integrated Power Systems, 2013

Probabilistic reliability evaluation of power systems can be performed by two distinct representations of the system: state space and chronological simulation. In the state space representation, the system states are randomly sampled by nonsequential Monte Carlo simulation (MCS). In the chronological representation, the states are sequentially sampled to simulate system operation by sequential MCS. Sequential MCS tends to produce more accurate results in the presence of time-varying elements, such as load curves and wind generation, because the time series are explicitly represented, and therefore, the correlation and statistical dependency between them are preserved. Some papers are based on this approach [1–3]. However, sequential MCS has a high computational cost and can become prohibitive for practical large systems.