Sahoo Buddhadeva, Samantaray Subhransu Ranjan, Alhaider Mohammed M
Department of Electrical and Electronics Engineering, SR University, Warangal, 506371, Telangana, India.
School of Electrical Sciences, Indian Institute of Technology Bhubaneswar, Bhubaneswar, 752050, India.
Sci Rep. 2025 Feb 27;15(1):7051. doi: 10.1038/s41598-025-90807-5.
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.
本文提出了一种用于基于三相、两级光伏（PV）和电池的混合微电网（HMG）系统的有限集模型预测控制（FS-MPC）策略。该系统包含带有连接到共享直流电网的双直流链路电容器的并联逆变器，从而实现更高的可靠性和高效的功率共享。开发了一种离散时间HMG模型，以预测诸如电网电流、环流电流和失调电流等关键系统参数。为了降低计算复杂度，FS-MPC从64个开关矢量中选择性地采用30个，确保在不牺牲性能的情况下实现更快的处理。该系统集成了基于增量电导的最大功率算法（IC-MPA）以实现高效的光伏能量提取，并集成了双向变换器模型以调节电池充电/放电操作，维持直流链路电压稳定性。还引入了一种集中式能量管理技术（CEMT）来优化能量流并提高系统性能。所提出的方法通过全面的软件仿真和硬件实验得到验证，证明了在动态条件下电能质量（PQ）和可靠性（PR）有显著改善。关键贡献包括增强的谐波补偿、减轻频率不稳定性以及更快的响应时间，突出了该系统在实时混合微电网应用中的实际有效性。
