ABSTRACT
SVR parameters ....................................................................................... 173 7.3.2 Predicting power grid frequency using PMU data and AOLSVR ................. 175
7.4 Summary ............................................................................................................................. 176 Acknowledgment ........................................................................................................................ 177 References ..................................................................................................................................... 177
its services and infrastructure. They can also provide fast and accurate diagnosis/prognosis as well as operation resiliency upon contingencies and malicious attacks. In this chapter, we describe some of these measurement devices and their applications. While many utilities understand the business values in the data collected by these measuring devices, the real challenge lies in how to develop processes and systems to continuously convert data into actionable information. Consequently, we also present some computational approaches for eliminating some of the inherent measurement errors in the collected data and extracting insights and knowledge from data collected to enhance situational awareness and controllability of the power grids.
