A Hierarchical Two-Layer MPC-Supervised Strategy for Efficient Inverter-Based Small Microgrid Operation

Salima Meziane, Toufouti Ryad, Yasser O. Assolami and Tawfiq M. Aljohani ()
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Salima Meziane: Laboratory of Electrical and Renewable Energies LEER, Department of Electrical Engineering, Souk Ahras University, Souk Ahras 41000, Algeria
Toufouti Ryad: Laboratory of Electrical and Renewable Energies LEER, Department of Electrical Engineering, Souk Ahras University, Souk Ahras 41000, Algeria
Yasser O. Assolami: Department of Electrical Engineering, College of Engineering at Yanbu, Taibah University, Yanbu Al-Bahr 41911, Saudi Arabia
Tawfiq M. Aljohani: Department of Electrical Engineering, College of Engineering at Yanbu, Taibah University, Yanbu Al-Bahr 41911, Saudi Arabia

Sustainability, 2025, vol. 17, issue 19, 1-36

Abstract: This study proposes a hierarchical two-layer control framework aimed at advancing the sustainability of renewable-integrated microgrids. The framework combines droop-based primary control, PI-based voltage and current regulation, and a supervisory Model Predictive Control (MPC) layer to enhance dynamic power sharing and system stability in renewable-integrated microgrids. The proposed method addresses the limitations of conventional control techniques by coordinating real and reactive power flow through an adaptive droop formulation and refining voltage/current regulation with inner-loop PI controllers. A discrete-time MPC algorithm is introduced to optimize power setpoints under future disturbance forecasts, accounting for state-of-charge limits, DC-link voltage constraints, and renewable generation variability. The effectiveness of the proposed strategy is demonstrated on a small hybrid microgrid system that serve a small community of buildings with a solar PV, wind generation, and a battery storage system under variable load and environmental profiles. Initial uncontrolled scenarios reveal significant imbalances in resource coordination and voltage deviation. Upon applying the proposed control, active and reactive power are equitably shared among DG units, while voltage and frequency remain tightly regulated, even during abrupt load transitions. The proposed control approach enhances renewable energy integration, leading to reduced reliance on fossil-fuel-based resources. This contributes to environmental sustainability by lowering greenhouse gas emissions and supporting the transition to a cleaner energy future. Simulation results confirm the superiority of the proposed control strategy in maintaining grid stability, minimizing overcharging/overdischarging of batteries, and ensuring waveform quality.

Keywords: hybrid control; model predictive control; droop control; distributed energy systems; smart communities; small microgrids; fast dynamic response; voltage stability; sustainable renewable energy systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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