Application and comparison of wind speed sampling methods for wind generation in reliability studies using non-sequential Monte Carlo simulations

Given the actual context of increased dispersed generation and highly loaded lines, probabilistic methods are more and more required to take into account the stochastic behavior of electrical network components (possible spate of outages by use of the electrical network near its physical limits) in reliability studies. To implement those probabilistic methods, numerical Monte Carlo simulations are typically used and can be divided in two categories: sequential and non-sequential techniques. This paper deals with two wind speed sampling methods adapted for non-sequential Monte Carlo simulations, among which an original approach based on the combination of a mean statistical law (for a large geographical area like a country) and Normal distributions (to characterize smaller wind speed zones inside the country). Both proposed techniques are then applied on a self-developed non-sequential Monte Carlo simulation only taking into account generation units outages and load changes (hierarchical level HL-1). Finally, the collected simulation results allow, not only, to evaluate the impact of sampling methods on the collected reliability indices but also to decide which proposed technique will lead to the most interesting situations (larger wind power fluctuations from one state to the other) for the electrical network operation management. Note that our simulations are applied to the Belgian production park. Copyright (C) 2008 John Wiley & Sons, Ltd.