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Microgrids (MGs) have become more prominent because of their ability to integrate renewable energy resources effectively. However, MGs face challenges in maintaining power quality due to the intermittent nature of renewable sources and the inherent time delay associated with feedback control loops, particularly in inverter-dominated systems with parallel distributed generators. This article proposes an enhanced multistep finite control set-based model-predictive controller (MSFCS-MPC) designed for AC MGs to effectively mitigate time delay. The considered AC MG design constitutes parallel inverter-fed DGs with intermittent source and load dynamics, where the photovoltaic with a boost converter and the battery with a bidirectional DC–DC converter are modeled to capture the realistic behavior of DC-link voltage instead of ideal DC conditions. The proposed model-predictive control framework incorporates a multistep algorithm to mitigate the effect of time delay and to enhance the dynamic performance of the system. The robustness of the proposed model is evaluated under load disturbances for different delay values and compared with the existing conventional control strategies. The proposed MSFCS-MPC achieves faster active and reactive power settling time of 0.18–0.24 and 0.20–0.27 s, respectively, compared to 0.22–0.28 and 0.26–0.30 s for the conventional finite control set-based model-predictive controller (FCS-MPC) and 0.40–0.45 and 0.45–0.50 s for the proportional–integral (PI) controller. Furthermore, the proposed approach improves waveform quality by maintaining voltage total harmonic distortion (THD) below 2% and reducing current THD to approximately 2%, even for delay values up to 50μs, whereas the conventional FCS-MPC and the PI controller exhibit voltage and current distortions. The efficacy of the proposed model is further validated through real-time simulations, utilizing OPAL-RT OP4510.
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Vimala et al. (2026) studied this question.
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