New Measurement Algorithm for Supraharmonic Real-time monitoring Based on Dynamic Compressed Sensing

With the popularity of advanced power electronic equipment, supraharmonic are emitted increasingly into the power systems, which are difficult to monitor accurately due to the high frequency and volatility. This paper proposes a new measurement algorithm for supraharmonic real-time monitoring based on dynamic compressed sensing. In the signal sensing node, the sliding time window is used for continuous sampling and compression of supraharmonic. At the recovery node, a dynamic reconstruction algorithm based on basis pursuit is designed, which quickly recovers the current compressed signal frame by using the recovery result of previous frame. Meanwhile, a variable-step sparse self-estimating subspace pursuit algorithm is adopted to improve the recovery accuracy. Several tests based on wind power grid connection model shows that, our method could effectively enhance the supraharmonic monitoring precision with lower computational complexity. Additionally, it also has the ability to analyze the dynamic time-varying characteristics of supraharmonic.