ABSTRACT
This chapter summarizes recent developments in data-centric monitoring of wind farms. We present methodologies which share information from multiple sources. Problems include inter-turbine modeling of wind speed and wake effects; methods for combining multiple emulators; spatially distributed virtual sensing, for the estimation of dynamic loads; hierarchical Bayesian modeling of power relationships at the systems level. We demonstrate how an increasingly holistic approach to wind farm monitoring brings a series of advantages.
