An adaptive power smoothing approach based on artificial potential field for PV plant with hybrid energy storage system
Xiangqiang Wu, Yue Wu, Zhongting Tang, Tamás Kerekes
Abstract
The increasing quantity of PV installation has brought great challenges to the grid owing to power fluctuations. Hybrid energy storage systems have been an effective solution to smooth out PV output power variations. In order to reduce the required capacity and extend the lifetime of the hybrid energy storage system, a two-stage self-adaptive smoothing approach based on the artificial potential field is proposed to decompose and allocate power among the grid, battery, and supercapacitor dynamically. In the ramp rate control stage, an unsymmetric artificial potential field method is used to regulate the cutoff frequency of a low-pass filter, so as to limit the PV power ramp rate within the prescribed range and allocate the power between the grid and the hybrid energy storage system. In the HESS power distribution stage, a symmetric artificial potential field is adopted to distribute power between the battery and supercapacitor by regulating the cutoff frequency of another low-pass filter. The effectiveness of the proposed strategy is validated through a case study based on real-world PV data in Denmark. The results show that the proposed method outperforms to reduce the over-smoothing effect and battery degradation, which can reduce battery loss by up to 17% to 49% compared to existing smoothing approaches.