This paper presents an adaptive proportional resonant (PR) controller for single phase grid connected inverter that adapts its control parameters to grid impedance variations. Forth order band bass filter is designed and then integrated with the adaptive scheme for on-line detection of any variations in the resonance frequency. The estimated frequency is then processed by statistical signal processing operation to identify the variations in the grid impedance. For the on-line tuning of the PR parameters, a look-up table technique is utilized and its parameters are linked with the estimated impedance values. Simulation results based on MATLAB environment clearly verify the effectiveness of the proposed control scheme for 2 kW grid connected inverter system.

This paper presents a novel condition monitoring scheme for sub-module (SM) capacitors in the modular multilevel converter (MMC), where the fast-affine projection (FAP) algorithm is cooperatively embedded in a dedicated range-based sorting scheme with reduced switching frequency to estimate the capacitor parameters. The proposed sorting scheme not only reduces the switching events of SMs, but also manages to maintain the capacitor ripple voltage within an acceptable range. Whilst the use of FAP achieves an on-line parametric estimation with superior speed and accuracy. Compared to previous studies, this proposed approach has significant advantages in terms of estimation accuracy and speed without the need for extra hardware. The effectiveness of the proposed approach is validated by a 5-level MMC model in MATLAB/Simulink. From simulation results, the estimation speed is less than 1.5 ms and the error is less than 3%.

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This paper investigates the performance of two Nature Inspired Optimization Algorithms (NIOA): Bacterial Foraging Optimization (BFO) and Particle Swarm Optimization (PSO), which are used for early fault detection on Induction Machine (IM) stator windings, to prevent sudden, catastrophic, breakdowns. An open-circuit stator winding fault is experimentally studied. This scheme uses time domain measurements obtained during transients to validate the capability of this technique, and in conjunction with the NIOA, estimates the parameters of the IM mathematical model, detects stator winding faults, and gives information about its type and location. Only stator voltages, currents, and rotor speed are evaluated using experimental data obtained from a wound rotor three-phase IM. The validity and effectiveness of the proposed method using the transient data is verified, showing its accuracy, prediction capability, and sensitivity without the need of prior knowledge of various fault signatures.

This paper presents an effective approach to detect the variation of the grid impedance for single phase PV grid connected inverter interfaced by LCL filter. The proposed technique entails the use of a digital Sallen-Key band pass filter placed at the point of common coupling (PCC) to filter out the harmonic components around the resonance frequency. Series of statistical signal processing steps are applied to the output signal of the band pass filter in order to identify the grid impedance variation. The techniques described in this paper can be deployed to tune the current controller gains using gain-scheduling method; it can also be utilized in islanding detection leading to power quality enhancement. MATLAB/Simulation results based on experimental data of PV grid inverter system subjected to wide range of impedance variation are presented to validate the proposed method.