Event-trigger particle filter for smart grids with limited communication bandwidth infrastructure

Accurate real-time state estimation plays an important role in distributed generation (DG) networks. In order to establish a reliable communication link for estimation, an information-centric networking (ICN) was employed with the development of smart grids technology. However, the widespread adoption of DG network boosts the amount of data transmitted through ICN, which is now the real-time performance bottleneck of estimation. By fully considering the nonlinearity of DG system, this paper develops an event-trigger particle filter (ET-PF) to relieve the communication burden and achieve an appropriate estimation accuracy. An arrival rate guaranteed event-trigger strategy is established for saving the bandwidth at first, which selects only the observations containing innovational information for the purpose of filtering. When the observation is not triggered, an ET-PF filtering algorithm is further proposed, making full use of the information from the prior event-trigger strategy, to enhance the performance of estimation. The design-oriented guaranteed arrival rate, specifically designed by ET-PF in statistical sense, is beneficial to design ICN infrastructure. Finally, its feasibility and performance is demonstrated using the standard IEEE 39-bus system with phasor measurement units.