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Adaptive current control based on combination of statistical signal processing and Partial swarm optimization for single phase PV grid connected inverter

Lookup NU author(s): hamza Khalfalla, Dr Salaheddine Ethni, Dr Maher Al-Greer, Professor Volker Pickert

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Abstract

This chapter presents a novel adaptive proportional resonant (PR) controller for single phase PV grid connected inverter using statistical signal processing method and Particle swarm optimization (PSO) technique. PR coefficients are adaptively tuned in accordance to the grid impedance variations. Forth order digital band bass filter is designed and integrated with the adaptive scheme for on-line detection of any variations in the resonance frequency of the grid impedance. The output signal obtained from the filter is then processed by a statistical signal processing operation to identify the variations in the grid impedance. PSO algorithm is deployed to optimally tune the parameters of the PR controller. For online tuning of the PR coefficients, the generated parameters by the PSO are then stored in a two-dimensional look up table (LUT). Selecting the optimal values from the LUT are based on the estimated impedance values. Results from the adaptive scheme show the effectiveness of the proposed structure for 2 kW grid-connected inverter system.


Publication metadata

Author(s): Khalfalla H, Ethni S, Al-Greer M, Pickert V

Series Editor(s): power systems Springer Nature

Publication type: Book Chapter

Publication status: Submitted

Book Title: power systems / Springer

Year: 2018

Series Title: power systems


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