Introduction to rare event probability estimation
Crude Monte Carlo methods are well suited to characterize events of which associated probabilities are not too low with respect to a given simulation budget. For very seldom observed events, such as the collision probability between two aircraft in airspace, Monte Carlo based approaches do not lead to accurate results. Indeed, the number of available samples is often insufficient to estimate such low probabilities (at least 10 6 samples are needed to estimate a probability of order 10 −4 with 10 % relative error with Monte Carlo simulations). The objective of this book is to propose some guidelines to determine the most efficient estimation techniques for a given problem.
Abstract Wind is one of the fastest-growing renewable sources of electricity. As with most renewables, the economic viability relies on public subsidies. Even among renewables, the economic evaluation of wind projects is particularly challenging due to the unpredictability of the energy source, wind, and the high sensitivity of the project profitability to changes in a number of parameters. This makes the uncertainty analysis an important topic of research in the wind power sector. This study presents a method of combining two uncertainty analysis methods, sensitivity study and the Monte Carlo method, together with a technical and economic model of a wind farm, in an effort to improve the understanding of the practical effects of the uncertainties, and how they affect the financial risks of wind projects.