Fundamental Active Current Adaptive Linear Neural Networks for Photovoltaic Shunt Active Power Filters

Muhammad Ammirrul Atiqi Mohd Zainuri, Mohd Amran Mohd Radzi, Azura Che Soh, Norman Mariun, Nasrudin Abd Rahim and Shahrooz Hajighorbani
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Muhammad Ammirrul Atiqi Mohd Zainuri: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Mohd Amran Mohd Radzi: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Azura Che Soh: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Norman Mariun: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Nasrudin Abd Rahim: University of Malaya Power Energy Dedicated Advanced Centre (UMPEDAC), University of Malaya, Kuala Lumpur 59990, Malaysia
Shahrooz Hajighorbani: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia

Energies, 2016, vol. 9, issue 6, 1-20

Abstract: This paper presents improvement of a harmonics extraction algorithm, known as the fundamental active current (FAC) adaptive linear element (ADALINE) neural network with the integration of photovoltaic (PV) to shunt active power filters (SAPFs) as active current source. Active PV injection in SAPFs should reduce dependency on grid supply current to supply the system. In addition, with a better and faster harmonics extraction algorithm, the SAPF should perform well, especially under dynamic PV and load conditions. The role of the actual injection current from SAPF after connecting PVs will be evaluated, and the better effect of using FAC ADALINE will be confirmed. The proposed SAPF was simulated and evaluated in MATLAB/Simulink first. Then, an experimental laboratory prototype was also developed to be tested with a PV simulator (CHROMA 62100H-600S), and the algorithm was implemented using a TMS320F28335 Digital Signal Processor (DSP). From simulation and experimental results, significant improvements in terms of total harmonic distortion (THD), time response and reduction of source power from grid have successfully been verified and achieved.

Keywords: shunt active power filter (SAPF); photovoltaic (PV); current harmonic; artificial neural network (ANN); total harmonic distortion (THD); digital signal processor (DSP); Simulink/MATLAB (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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