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; Shahrooz Hajighorbani

LAPSE

Living Archive for Process Systems Engineering

LAPSE:2018.1110

Published Article

LAPSE:2018.1110

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, Shahrooz Hajighorbani

November 28, 2018

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.

Record ID

LAPSE:2018.1110

Keywords

artificial neural network (ANN), current harmonic, digital signal processor (DSP), photovoltaic (PV), shunt active power filter (SAPF), Simulink/MATLAB, total harmonic distortion (THD)

Subject

Process Operations

Suggested Citation

Mohd Zainuri MAA, Mohd Radzi MA, Che Soh A, Mariun N, Abd Rahim N, Hajighorbani S. Fundamental Active Current Adaptive Linear Neural Networks for Photovoltaic Shunt Active Power Filters. (2018). LAPSE:2018.1110

Author Affiliations

Mohd Zainuri MAA: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; Centre for Advanced Power and Energy Research, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Sel [ORCID]
Mohd Radzi MA: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; Centre for Advanced Power and Energy Research, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Sel [ORCID]
Che Soh A: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; Centre for Advanced Power and Energy Research, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Sel [ORCID]
Mariun N: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; Centre for Advanced Power and Energy Research, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Sel
Abd Rahim N: University of Malaya Power Energy Dedicated Advanced Centre (UMPEDAC), University of Malaya, Kuala Lumpur 59990, Malaysia [ORCID]
Hajighorbani S: Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; Centre for Advanced Power and Energy Research, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Sel
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Journal Name

Energies

Volume

9

Issue

6

Article Number

E397

Year

2016

Publication Date

2016-05-27