Advanced control scheme for harmonic mitigation and performance improvement in DC-AC microgrid with parallel voltage...

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Hybrid microgrids (HMGs) integrating photovoltaic (PV) systems and battery storage are crucial for grid stability and reliability.
• Managing power flow and ensuring DC-link voltage stability in multi-stage HMGs with parallel inverters presents significant control challenges.

Purpose of the Study:

• To propose a finite set model predictive control (FS-MPC) strategy for a three-phase, two-stage PV and battery-based HMG.
• To enhance power quality (PQ) and reliability (PR) through optimized energy management and reduced computational complexity.

Main Methods:

• Development of a discrete-time HMG model for predicting grid, circulating, and offset currents.
• Selective application of 64 switching vectors in FS-MPC to reduce computational load while maintaining performance.
• Integration of an incremental conductance-based maximum power point tracking algorithm (IC-MPA) and a bidirectional converter model.
• Implementation of a centralized energy management technique (CEMT) for optimized energy flow.

Main Results:

• Demonstrated significant improvements in power quality (PQ) and reliability (PR) under dynamic operating conditions.
• Achieved enhanced harmonic compensation and mitigation of frequency instability.
• Validated faster response times and practical effectiveness through simulations and hardware experiments.

Conclusions:

• The proposed FS-MPC strategy offers an effective solution for real-time control of PV and battery-based HMGs.
• The approach successfully balances computational efficiency with high performance in complex microgrid applications.
• The study highlights the system's capability to improve overall microgrid stability and energy utilization.