Using a Langevin model for the simulation of environmental conditions in an offshore wind farm

Abstract

For the planning of operations and maintenance in offshore wind farms, many simulation models exist. Many rely on artificially generated weather time series to test different strategies. In this paper, we present a novel approach to modeling both the significant wave height and wind speed based on measurements from the site. We use a stochastic process called the Langevin process. First, equations are fitted to the available data, which are then used to generate the artificial weather data. The properties of these artificial weather time series are very close to the properties of the actual weather. Mean and standard deviation as well as the overall distribution and seasonality can be captured by the new model. Additionally, the persistence of waves and winds is replicated. This is especially important, as the length of weather windows is an important factor in operation and maintenance planning.