TY - JOUR
T1 - Advanced control scheme for harmonic mitigation and performance improvement in DC-AC microgrid with parallel voltage source inverter
AU - Sahoo, Buddhadeva
AU - Samantaray, Subhransu Ranjan
AU - Alhaider, Mohammed M.
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - This article proposes a finite set model predictive control (FS-MPC) strategy for a three-phase, two-stage photovoltaic (PV) and battery-based hybrid microgrid (HMG) system. The system incorporates parallel inverters with dual DC-link capacitors connected to a shared DC grid, enabling enhanced reliability and efficient power-sharing. A discrete-time HMG model is developed to predict key system parameters such as grid, circulating, and offset currents. To reduce computational complexity, the FS-MPC selectively employs 30 out of 64 switching vectors, ensuring faster processing without sacrificing performance. The system integrates an incremental conductance-based maximum power algorithm (IC-MPA) to achieve efficient PV energy extraction and a bidirectional converter model to regulate battery charging/discharging operations, maintaining DC-link voltage stability. A centralized energy management technique (CEMT) is also introduced to optimize energy flow and enhance system performance. The proposed approach is validated through comprehensive software simulations and hardware experiments, demonstrating significant improvements in power quality (PQ) and reliability (PR) under dynamic conditions. Key contributions include enhanced harmonic compensation, frequency instability mitigation, and faster response times, highlighting the practical effectiveness of the system in real-time hybrid microgrid applications.
AB - This article proposes a finite set model predictive control (FS-MPC) strategy for a three-phase, two-stage photovoltaic (PV) and battery-based hybrid microgrid (HMG) system. The system incorporates parallel inverters with dual DC-link capacitors connected to a shared DC grid, enabling enhanced reliability and efficient power-sharing. A discrete-time HMG model is developed to predict key system parameters such as grid, circulating, and offset currents. To reduce computational complexity, the FS-MPC selectively employs 30 out of 64 switching vectors, ensuring faster processing without sacrificing performance. The system integrates an incremental conductance-based maximum power algorithm (IC-MPA) to achieve efficient PV energy extraction and a bidirectional converter model to regulate battery charging/discharging operations, maintaining DC-link voltage stability. A centralized energy management technique (CEMT) is also introduced to optimize energy flow and enhance system performance. The proposed approach is validated through comprehensive software simulations and hardware experiments, demonstrating significant improvements in power quality (PQ) and reliability (PR) under dynamic conditions. Key contributions include enhanced harmonic compensation, frequency instability mitigation, and faster response times, highlighting the practical effectiveness of the system in real-time hybrid microgrid applications.
KW - Centralized energy management technique (CEMT)
KW - Finite set model predictive control (FS-MPC)
KW - Hybrid microgrid (HMG)
KW - Maximum power algorithm (MPA)
KW - Power quality (PQ)
UR - http://www.scopus.com/inward/record.url?scp=85219629715&partnerID=8YFLogxK
U2 - 10.1038/s41598-025-90807-5
DO - 10.1038/s41598-025-90807-5
M3 - Article
C2 - 40016332
AN - SCOPUS:85219629715
SN - 2045-2322
VL - 15
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 7051
ER -
