Cloud- Edge Integrated State Identification Framework and Algorithm

Abstract

With the ubiquitous construction of the Internet of Things (IoT) and a large number of distributed new energy resources (DER) equipment connected to the power grid, massive and heterogeneous information needs to be collected, which will bring insufficient transmission bandwidth, the in-sufficient processing capacity of the primary station, and insufficient storage capacity. Concurrently, the really important information is submerged in the ineffectiveness of the mass and even the wrong information, which makes it difficult to accurately and timely identify the operating state of the power grid. Cloud computing and Edge computing are important to support calculations in the field of IoT. To address the problems, firstly, this paper proposes a new "cloud edge" fusion state-aware architecture and adopts corresponding technologies to realize online and fast information processing. Secondly, a perception algorithm based on edge computing is proposed to realize that the measurement model can be time-varying in the case of heterogeneous measurement data. The corresponding measurement equation is established according to the type and quantity of the measurement data at the current moment and is based on the maximum a posteriori estimation criterion. The calculation formula is deduced. Finally, the IEEE14 calculation example verifies the validity of the framework and method in this paper and maintains a high degree of accuracy and stability even when the measurement changes.