Fault–Tolerant Control of Offshore Wind Farm Installations via Adaptive Nonlinear Filters

In order to improve the availability of offshore wind farms, thus avoiding unplanned operation and maintenance costs, which can be high for offshore installations, the accommodation of faults in their earlier occurrence is fundamental. Therefore, this paper addresses the design of an active fault tolerant control scheme that is applied to a small wind park benchmark of nine wind turbines, based on their nonlinear models, as well as the wind and interactions between the wind turbines in the wind farm. The controller accommodation scheme provides the on–line estimate of the fault signals generated by nonlinear filters exploiting the nonlinear geometric approach to obtain estimates decoupled from both model uncertainty and the interactions among the turbines. This paper proposes also a datadriven approach to provide these disturbance terms in analytical forms, which are subsequently used for designing the nonlinear filters for fault estimation. In general, purely analytic approaches, where the system nonlinearity and disturbance decoupling properties are explicitly considered, could require complex design strategies. This feature of the work, followed by the simpler solution relying on a data–driven approach, can represent the key point when on–line implementations are considered for a viable application of the proposed scheme. The wind farm benchmark is considered to validate the performances of the suggested scheme in the presence of different fault conditions, modelling and measurement errors.