Compressed Sensing Based Real-time Control in a Smart Grid

This paper develops areal-time control method which is a data transmission technique based on compressed sensing in smart grid. Different from traditional signal acquisition processing methods, compressed sensing is a promising method being widely used in emerging areas such as image processing, biotechnology, and communication, etc. This method significantly reduces the sampling rate at signal acquisition, and the compressed signals can be recovered in an accurate way. Numerous studies illustrate that conventional compressed sensing is effectively used in the static system. However, the delay of the static system is very large, which restricts its application in highly real-time control applications. With the continuous expansion of smart grid, electric power department needs to adjust the price and other controllable variables in real-time to accommodate the electric consumption of residents. Increasing demand of real-time control strategy with fast, reliable and stable properties becomes the core issue that need to be solved urgently. Simulation results verify that the proposed strategy can recover signal in real-time effectively using less amount of data through a dynamic sliding window.