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Model predictive control-based energy management for microgrids in weak utility grid environments
Journal article   Open access   Peer reviewed

Model predictive control-based energy management for microgrids in weak utility grid environments

S. Saha, M. Elliott, S. Huda, J. Abawajy, F. Jiang, A.M.T. Oo, Y. Sun and T. Mao
International Journal of Electrical Power & Energy Systems, Vol.181, pp.1-22
2026
DOI: https://doi.org/10.1016/j.ijepes.2026.112066
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Published Version Open Access CC BY V4.0

Abstract

Battery degradation Battery energy storage system Energy management system Microgrids Model predictive control Solar photovoltaic Weak utility grids
This paper presents a model predictive control based energy management system for microgrids with high renewable energy penetration in weak utility grid environments. Weak grid–microgrid interconnection, characterised by high equivalent grid impedance and low available fault levels, results in high voltage sensitivity at the point of common coupling to power exchange, which may lead to voltage instability and renewable energy curtailment within the microgrid. The proposed energy management system adopts a two-layer structure. The hourly optimisation layer uses a rolling-horizon model predictive control approach to schedule battery energy storage system charging, discharging, and reactive power under forecasted uncertainties in renewable generation, load demand, and electric vehicle charging. The instantaneous control layer further refines these set-points to accommodate short-term variations in load, solar generation, and electric vehicle charging behaviour. The framework enables adaptive, cost-effective, and degradation-aware operation by maintaining voltage within permissible limits while preventing both renewable energy and load curtailment. The approach is validated on a suburban microgrid representing a Brisbane suburb with 4.95 MW solar photovoltaic generation, 4.95 MWh lithium-ion battery energy storage, and electric vehicle charging facilities. Simulation results show that, compared to an existing energy management system, the proposed method eliminates 2068 MWh of solar curtailment, reduces battery degradation from 98.9 kWh to 52.66 kWh, and increases the annual net economic benefit from AU$679,297 to AU$1,031,168. These results demonstrate improved renewable energy utilisation, economic performance, and long-term microgrid sustainability under weak grid conditions.

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