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A model predictive control for a renewable-based multi energy system by integrating data-driven algorithm
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DOI：10.1016/j.egyr.2025.07.013.png)
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Abstract
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This paper has proposed a multi-energy resource power system being linked into an electrical power grid. In the system, wind and solar power resources work with a hydrogen energy storage system. In order to maximize the injection of renewable energy sources into the power grid, a data-drive model predictive control strategy is proposed and allocates the energy flow in this multi-energy power system. After introducing the structure of the system, the study selects four seasons typical renewable power generation for case studies. Afterwards, key indicators for the system performance with wind, photovoltaic and power grid are discussed. The test results show that the proposed system under the control strategy can promote the local utilization of renewable energy, with an absorption rate increase up to 73.86%.
Keywords:
Hydrogen energy storage system
Model predictive control
Multi-energy system
State space model
Wind power utilization
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