Optimal power allocation and capacity configuration based on variable cut-off frequency low-pass filtering for photovoltaic with hybrid energy storage system

Abstract

Photovoltaic (PV) power generation is affected by intermittent solar radiation, leading to fluctuations in output power and reducing the stability and reliability of PV systems. In general, a hybrid energy storage system (HESS) combined with a PV system is employed to smooth PV power fluctuation. However, the traditional algorithms for balancing the capacity of HESS, power fluctuations, and life cycle costs (LCC) remain challenging. To address this challenge, a modified method of variable cut-off frequency low-pass filtering (VFLPF) is developed to determine the capacity of battery and supercapacitor (SC) in HESS, as well as balance the relationship between PV power fluctuations and total energy system capacity (TESC). Additionally, Z_E and Z_p are adopted as metrics for evaluating the total energy system capacity and reference power, respectively, specifically employed to mitigate the maximum fluctuation rate (MFR) in PV systems. Moreover, the presented algorithm is validated by the photovoltaic module combined with the hybrid energy storage system (PVM-HESS) and the photovoltaic array combined with the hybrid energy storage system (PVA-HESS). In the presented PVM-HESS and PVA-HESS, the metrics Z_E are respectively reduced by 2.65–2.94 % and 20–54.10 % compared to the traditional fixed cut-off frequency low-pass filtering (FFLPF) strategies of S.Ⅰ (cut-off frequency of 160 Hz) and S.Ⅱ (cut-off frequency of 750 Hz), while the Zp is reduced by 3.3–45.62 % and 3.31–78 %, respectively. The life cycle costs determined by the presented algorithm are reduced by 7.71 % and 11.10–21.52 %. Furthermore, a three-port DC-DC converter of 450 W is designed to connect the DC Bus with the PV module and the hybrid energy storage system, in which the MFR of PV output power is reduced by 23.77 %. Finally, a 20 kWp PVA combined with the hybrid energy storage system optimises power allocation and capacity configuration while reducing the MFRs throughout the year by 0.07–64.53 %. In conclusion, the presented algorithm and strategy are an effective technical solution for reducing total energy capacity and reference power when smoothing power fluctuations, as well as providing theoretical support for coordinated operation of storage energy equipment in a hybrid energy storage system.