Simultaneous Frequency and Amplitude Estimation for Grid Quality Monitoring: New Partitioning with Memory Based Newton-Schulz Corrections

High penetration level of renewable energy sources and introduction controllable loads will result in significant harmonic emissions sag swell events the future electricity networks. Development methods for high performance simultaneous estimation frequency amplitude is required stable operation networks since zero crossing detection method (which widely used nowadays industry) not accurate enough does allow events. The multiple model which suitable extended this paper with a new decomposition technique based on stepwise partitioning, allows construction computationally efficient inversion information matrix. Recursive calculations inverse introduce error accumulation general order memory Newton-Schulz iteration proposed correction reduction accumulated error. Moreover, parallel Richardson iterations are partitioning computational complexity. especially approximation signals large number harmonics. approaches were tested signatures one-phase synchronized voltage waveform measured at wall outlet. Simulation results show that provides more comparison to method. In addition, cascade multi-windowing (where components separated via proper choice window sizes) introduced significantly frequencies electrical signals. approach was problem using measurement record from electric vehicle on-board charger connected supply laboratory.