Optimally selected objective and model predictive control based optimal strategy of wind power with energy storage

Authors

Xiao YAN, College of Electrical Engineering and New Energy， China Three Gorges University, Yichang 443002, China; Hubei Provincial Engineering Research Center of Intelligent Energy Technology，China Three Gorges University， Yichang 443002, China
Shan CHENG, College of Electrical Engineering and New Energy， China Three Gorges University, Yichang 443002, China; Hubei Provincial Engineering Research Center of Intelligent Energy Technology，China Three Gorges University， Yichang 443002, China
Xianwang ZUO, College of Electrical Engineering and New Energy， China Three Gorges University, Yichang 443002, China; Hubei Provincial Engineering Research Center of Intelligent Energy Technology，China Three Gorges University， Yichang 443002, China
Kanglin WEI, College of Electrical Engineering and New Energy， China Three Gorges University, Yichang 443002, China; Faculty of Intelligence Manufacturing, Yibin University, Yibin 644000,China

Keywords

wind power fluctuation smoothing, optimal selection of target, fuzzy control, model predictive control

Abstract

Aiming at the problem that the wind storage system's power fluctuation suppression effect is unsatisfactory, the wind storage system's operation is optimized. Considering the time series coupling characteristics of wind storage system operation and the influence of future wind power fluctuation on the energy storage system (ESS), an optimization strategy based on stabilizing target optimization method and model predictive control (MPC) is proposed. Firstly, the expected grid?connected power is calculated according to the predicted wind power and the constraints of ESS, and the local prediction accuracy is introduced to correct it. Then, combined with the current state of charge (SOC) of ESS, the optimal stabilization target is obtained by fuzzy control; Lastly, the MPC with particle swarm optimization (MPC?PSO) strategy is used to optimize the ESS power, so as to minimize the difference between the grid?connected power of next time and the optimal target power and minimize the ESS power. The simulation results show that the strategy proposed in this paper has a better wind power fluctuation smoothing effect and can effectively reduce the operation cost of energy storage.

DOI

10.19781/j.issn.1673-9140.2023.01.001

First Page

1

Last Page

10

Recommended Citation

YAN, Xiao; CHENG, Shan; ZUO, Xianwang; and WEI, Kanglin (2023) "Optimally selected objective and model predictive control based optimal strategy of wind power with energy storage," Journal of Electric Power Science and Technology: Vol. 38: Iss. 1, Article 1.
DOI: 10.19781/j.issn.1673-9140.2023.01.001
Available at: https://jepst.researchcommons.org/journal/vol38/iss1/1