  Passive device installation on wind turbine generators (WTGs) can potentially
improve the power generation of WTGs. Yet, how much impact the installation
will make is unclear because conducting controlled experiments is impossible
due to ever-changing wind and weather that affect the power generation
significantly. In addition, the potential improvement is believed to be in a
small scale, such as 1-5%, which is less than a typical 3-8% variation level
observed in wind data. This article proposes an adaptive kernel-based method
and builds a surrogate model to reduce the level of unexplained variation in
wind data. In addition, to establish experimental environments that are similar
to a controlled situation, this article develops an analysis framework that
utilizes two other nearby WTGs without any passive device installation.
