7. Forecasting-Aided State Estimation

This chapter deals with the problem of integrating forecasting techniques with power system state estimation (SE) algorithms. Forecasting-aided state estimation (FASE) has been proposed as an attractive alternative to overcome some issues in the traditional SE. Different strategies for creating a forecasting step in the SE process are devised. Modeling aspects regarding the establishment of a discrete-time state transition model are addressed. Concerning data validation, an innovation analysis is advocated. An example elucidates its application. The innovation is determined by the difference between a measurement just received and its forecasted value. The chapter can be seen as a guide to using a predictive database to enhance the estimation process, regarding, for instance, observability and extended WLS SE filtering. Throughout the chapter, main achievements of the FASE approach are addressed. The chapter ends with a section on advanced topics followed by proposed problems and a list of references.