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Citation:Jingyu Yang,Tongguang Yang,Longfu Luo,Li Peng.Tracking-dispatch of a combined wind-storage system based on model predictive control and two-layer fuzzy control strategy.[J].Protection and Control of Modern Power Systems,2023,V8(4):974-989[Copy]
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Tracking-dispatch of a combined wind-storage system based on model predictive control and two-layer fuzzy control strategy.
Jingyu Yang,Tongguang Yang,Longfu Luo,Li Peng
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Abstract:
To maximize improving the tracking wind power output plan and the service life of energy storage systems (ESS), a control strategy is proposed for ESS to track wind power planning output based on model prediction and two-layer fuzzy control. First, based on model predictive control, a model with deviations of grid-connected power from the planned output and the minimum deviation of the remaining capacity of the ESS from the ideal value is established as the target. Then, when the grid-connected power exceeds the allowable deviation band of tracking, the weight coefcients in the objective function are adjusted by introducing the frst layer of fuzzy control rules, combining the state of charge (SOC) of the ESS with the dynamic tracking demand of the planned value of wind power. When the grid-connected power is within the tracking allowable deviation band, the second layer of fuzzy control rules is used to correct the charging and discharging power of the ESS to improve its ability to track the future planned deviation while not crossing the limit. By repeatedly correcting the charging and discharging power of the ESS, its safe operation and the multitasking execution of the wind power plan output tracking target are ensured. Finally, taking actual data from a wind farm as an example, tests on a simulation platform of a combined wind-storage power generation system verify the feasibility and superiority of the proposed control strategy
Key words:  Wind power, Energy storage system, Track planned output, Model predictive control, Two-layer fuzzy control
DOI:10.1186/s41601-023-00334-6
Fund:This work was supported by the Major Science and Technology Project of Hunan Province (2020GK1013); Project of Natural Science Foundation of Hunan Province (2023JJ50344); Project of Educational Commission of Hunan Province (22C0512)
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