Distributed Quantum-Assisted Multi-SAPF Architecture Based on Deterministic Current Control and Asynchronous QUBO–QAOA–VQE Supervisory Optimization
Marian Gaiceanu, Razvan Buhosu, George-Andrei Marin, Marius George SolomonThe increasing penetration of nonlinear industrial loads, distributed renewable generation, and intelligent electrical infrastructures requires active power filters capable of simultaneously providing high-performance harmonic mitigation, reactive power compensation, coordinated operation of multiple converters, and deterministic real-time implementation. Conventional centralized shunt active power filters (SAPFs) exhibit limited scalability, while optimization-based approaches often compromise deterministic execution because of their computational complexity. To address these challenges, this paper proposes a Distributed Quantum Multi-Shunt Active Power Filter (Quantum Multi-SAPF) that combines deterministic-based local current control with asynchronous quantum-assisted supervisory optimization. The proposed architecture employs four distributed SAPF units operating under a hierarchical cyber–physical framework. The lower control layer, implemented on a MATLAB R2026a, includes all fast electrical functions—signal acquisition, SOGI-based synchronization, Clarke transformation, instantaneous p–q current reference generation, current regulation, interleaved PWM modulation, and protection—which are executed deterministically at a switching frequency of 15 kHz. The upper supervisory layer operates asynchronously at 20 Hz and formulates converter coordination as a quadratic unconstrained binary optimization (QUBO) problem solved using Quantum Approximate Optimization Algorithm (QAOA) allocation together with Variational Quantum Eigensolver (VQE) predictive correction. This multi-rate architecture separates fast electrical dynamics from slow supervisory optimization, ensuring that uncertain optimization latency does not affect converter stability. The proposed controller is validated through comprehensive switching-level simulations on the MATLAB R2026a platform. Numerical results demonstrate a reduction in source current total harmonic distortion from 24.615% to 0.142%, corresponding to a 99.423% harmonic reduction, while improving the source power factor to 0.99999 and achieving 99.999% reactive power compensation. The distributed four-SAPF synchronization network maintains coherent phase alignment among all converter units throughout the simulation, thereby supporting coordinated compensation and balanced current sharing. This synchronized operation contributes to highly accurate compensation current tracking, with an RMS tracking error of only 0.026 A, while limiting the source current unbalance to 0.026%. These results confirm the effectiveness of the distributed synchronization and local control architecture in maintaining coordinated and balanced operation of the four parallel SAPFs. The proposed interleaved modulation strategy, combined with optimized current sharing, maintains balanced converter utilization while suppressing circulating currents without requiring a dedicated circulating current controller. The proposed Distributed Quantum Multi-SAPF establishes a scalable framework that combines deterministic industrial control with quantum-assisted supervisory optimization. The architecture provides high harmonic compensation capability, near-unity power factor, balanced converter utilization, comprehensive Safe Operating Area supervision, and practical industrial feasibility, making it a promising solution for future smart grids, renewable energy integration, electric vehicle charging infrastructures, and intelligent power quality conditioning systems.