MPC-ADALINE Control Strategy for a Renewable Energy Powered Shunt Active Power Filter

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.