Abstract
AbstractTo 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 coefficients in the objective function are adjusted by introducing the first 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.
Funder
Major Science and Technology Project of Hunan Province
Project of Natural Science Foundation of Hunan Province
Project of Educational Commission of Hunan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Safety, Risk, Reliability and Quality
Reference39 articles.
1. Lin, Z. J., Chen, H. Y., Wu, Q. W., et al. (2020). Mean-tracking model based stochastic economic dispatch for power systems with high penetration of wind power. Energy, 193(5), 1–13.
2. Su, Y., & Teh, J. (2023). Two-stage optimal dispatching of AC/DC hybrid active distribution systems considering network flexibility. Journal of Modern Power Systems and Clean Energy, 33(1), 52–65.
3. Dui, X. W., Zhu, G. P., & Yao, L. Z. (2018). Two-stage optimization of battery energy storage capacity to decrease wind power curtailment in grid-connected wind farms. IEEE Transactions on Power Systens, 33(3), 3296–3305.
4. Li, X. J., Ma, R., Gan, W., et al. (2022). Optimal dispatch for battery energy storage station in distribution network considering voltage distribution improvement and peak load shifting. Journal of Modern Power Systems and Clean Energy, 10(1), 131–139.
5. He, G. N., Chen, Q. X., Kang, C. Q., et al. (2016). Optimal bidding strategy of battery storage in power markets considering performance-based regulation and battery cycle life. IEEE Transactions on Smart Grid, 7(5), 2359–2367.