Multi-objective optimal sizing of hybrid energy storage systems for grid-connected wind farms using fuzzy control

Abstract

With the emergence of large-scale wind farms in northwest China, the stable control of wind power through hybrid energy storage systems (HESS) is an effective measure. To match the grid-connected power quality requirements with the wind fluctuations, an adaptive wavelet decomposition based smoothing strategy achieves power distribution in the HESS. In this study, a multi-objective life cycle model is established and applied to the 99 MW Caka wind farm in Qinghai Province, China. Combined with the characteristics of the local wind output, typical model input scenarios are selected based on cluster analysis. Through the comparison of multiple schemes, the optimal HESS configuration scheme is obtained and proves to be superior to a single energy storage system scheme in terms of replacement cycle while reducing costs by 3.8%. The number of wind fluctuations is significantly reduced by 71.25% and the expected stable power output is guaranteed. Compared with traditional control, the fuzzy control strategy reduces the deviation of state of charge from the healthy range by 77.26%. Finally, the influence of energy storage cost and typical scenarios on the configuration of the HESS are analyzed. The results can provide a reference for the planning and construction of wind-HESS systems.