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Component failure simulation tool for optimal electrical configuration and repair strategy design of off-shore wind farms

Abstract:

Wind power is a renewable energy source increasingly attractive from an economic viewpoint and constitutes an alternative of growing relevance in current electric energy systems. The majority of operating wind farm turbines are on land, but it is expected that an important part of the future expansion of wind energy utilization, mainly in Europe, will come from offshore sites, where there are favorable wind conditions compared to sites on land. However, the higher energy yield has to compensate the additional installation and maintenance cost. For this reason, within any off-shore project planning and design process, it is very important to consider appropriately the effect of the electrical configuration, and the maintenance and repair strategy during lifetime. This work presents a methodological framework integrated within an informatic tool to help deciding which is the optimal between combinations of different i) electrical configurations, and ii) maintenance and repair strategies. The work was developed within the project Ocean Lider (www.oceanlider.org). The main objective is to evaluate the maximum potential energy that can be evacuated during lifetime for each combination. Since this problem has a stochastic nature, a number of lifetime simulations is performed. Each simulation has several stages: i) time of failure decision for each electrical component, ii) evaluation, based on graph theory, of generators out of service due to different component failures, iii) estimation of repair times considering available meteorological time windows, and finally iv) the estimation of the maximum energy which can be evacuated at any moment during lifetime. Results from simulations allow analysing the performance of different combinations of electrical configurations versus maintenance and repair strategies, and making informed decisions managing the risks due to uncertainty. This methodological framework would constitute a valuable decision tool for planners and designers. © 2011 IEEE.