TY - GEN
T1 - MPC-ADALINE Control Strategy for a Renewable Energy Powered Shunt Active Power Filter
AU - Krama, Abdelbasset
AU - Rohouma, Wesam
AU - Metry, Morcos
AU - Pillai, Dhanup Somasekharan
AU - Che Wanik, Mohd Zamri
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This paper presents a novel control strategy for a renewable powered shunt active power filter (SAPF), integrating model predictive control (MPC) with an adaptive linear neuron (ADALINE) for effective harmonic and reactive power compensation, thereby enhancing overall power quality. The proposed SAPF system employs a three-phase voltage source inverter interfaced via an LCL filter and is energized by local power generation source emulating renewable energy systems and storage devices. The MPC algorithm ensures fast and optimal control of the injected current while effectively mitigating resonance related issues. Concurrently, the ADALINE based harmonic identifier accurately extracts dominant harmonic components from the load current. This integrated approach enables precise tracking of reference compensating currents, significantly reducing harmonic distortion and reactive power demand. Simulation results demonstrate the robustness of the MPC-ADALINE scheme, lowering grid current THD to 3.08 % and satisfying international power quality standards across a wide range of load conditions. Consequently, the proposed system enhances grid power quality and stability while facilitating clean energy integration.
AB - This paper presents a novel control strategy for a renewable powered shunt active power filter (SAPF), integrating model predictive control (MPC) with an adaptive linear neuron (ADALINE) for effective harmonic and reactive power compensation, thereby enhancing overall power quality. The proposed SAPF system employs a three-phase voltage source inverter interfaced via an LCL filter and is energized by local power generation source emulating renewable energy systems and storage devices. The MPC algorithm ensures fast and optimal control of the injected current while effectively mitigating resonance related issues. Concurrently, the ADALINE based harmonic identifier accurately extracts dominant harmonic components from the load current. This integrated approach enables precise tracking of reference compensating currents, significantly reducing harmonic distortion and reactive power demand. Simulation results demonstrate the robustness of the MPC-ADALINE scheme, lowering grid current THD to 3.08 % and satisfying international power quality standards across a wide range of load conditions. Consequently, the proposed system enhances grid power quality and stability while facilitating clean energy integration.
KW - Adaptive Linear Neuron (ADALINE)
KW - LCL filter
KW - Model Predictive Control
KW - Power Quality
KW - Shunt Active Power Filter
UR - https://www.scopus.com/pages/publications/105016252069
U2 - 10.1109/ISIE62713.2025.11124751
DO - 10.1109/ISIE62713.2025.11124751
M3 - Conference contribution
AN - SCOPUS:105016252069
SN - 979-8-3503-7480-3
T3 - Proceedings Of The Ieee International Symposium On Industrial Electronics
BT - 2025 Ieee 34th International Symposium On Industrial Electronics, Isie
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th IEEE International Symposium on Industrial Electronics, ISIE 2025
Y2 - 20 June 2025 through 23 June 2025
ER -