Artificial Neural Network Active Power Filter with Immunity in Distributed Generation

  • Mohamed Kadem Laboratory of Intelligent Control and Electrical Power Systems (ICEPS), Department of Electrical Engineering, Djilali Liabes University, P. O. B. 89, Ben M'hidi, 22000 Sidi Bel Abbès, Algeria
  • Abdelhafid Semmah Laboratory of Intelligent Control and Electrical Power Systems (ICEPS), Department of Electrical Engineering, Djilali Liabes University, P. O. B. 89, Ben M'hidi, 22000 Sidi Bel Abbès, Algeria
  • Patrice Wira Institute of Research in Computer Science, Mathematics, Automation and Signal (IRIMAS), Haute Alsace University, Rue Albert Camus 61, 68093 Mulhouse, France
  • Abdelkader Slimane Laboratory of Applied Mechanics, Department of Mechanical Engineering, University of Sciences and Technology of Oran Mohamed Boudiaf, P. O. B. 1505, El M'Naouer, 31000 Oran, Algeria; Laboratory of Materials and Reactive Systems (LMSR), Department of Mechanical Engineering, Djilali Liabes University, P. O. B. 89, Ben M'hidi, 22000 Sidi Bel Abbès, Algeria

Abstract

With an electrical grid shifting toward Distributed Generation (DG), the emerging use of renewable energy resources is continuously creating challenges to maintain an acceptable electrical power quality thought-out the grid; Therefore, in an energy market where loads are becoming more and more sensitive in a distributed generation filled with polluting nonlinear loads, power quality improvement devices such Active Power Filters (APFs) have to evolve to meet the new standards, since theirs conventional control strategies can't properly operate when multiple power quality problems happens at once, even the one using AI based control as it will be proven in this paper. In this paper a neural network based Active Power Filter will be tested in a DG environment where both current and voltage harmonics, along with fast frequency variation occurs, we will see how the PLL can downgrade its performances enormously under such hostile conditions, We propose to solve this problem by replacing the conventional PLL with a nonlinear least square (NLS) frequency estimator, this novel NLS-ADALINE SAPF is immune in high DG penetration environment, as it will be tested and validated experimentally on an Opal-RT OP5600 FPGA based real-time simulator.

Keywords: power quality, Active Power Filter, artificial neural network, nonlinear least square, Distributed Generation
Published online
2020-01-28
How to Cite
Kadem, M., Semmah, A., Wira, P. and Slimane, A. (ONLINE) “Artificial Neural Network Active Power Filter with Immunity in Distributed Generation”, Periodica Polytechnica Mechanical Engineering. https://doi.org/10.3311/PPme.12775.
Section
Articles