FO-PI Controller for Regulating DC Link Voltage in UPQC Integrated HES System for Power Quality Improvement

This paper emphasis on an optimized Fractional order PI controller (FOPI) for enhancing the power quality of three phase hybrid energy storage (HES) system integrated unified power quality conditioner (UPQC). In order to offer uninterrupted electricity, renewable energy sources regarding wind energy, solar PV, and battery energy storage systems (BESS) are also explored. Whenever the windmill as well as PV array is not supplying electricity, the BESS could improve the stability of the power distribution system, meet entire load requirements. Grid power quality harmonics as well as concerns induced via non-linear loads are addressed by the UPQC type with shunt and series active filter compensators. To ease the grid’s power quality issues and the harmonics introduced by non-linear loads there subsist the UPQC model with active filter shunt and series compensator. The FOPI controller is used for improving the power quality of a 3-phase hybrid energy storage device with an integrated UPQC. RES such as PV arrays, BESS, as well as wind energy are analyzed in order to deliver continuous electricity. Whenever the PV array as well as windmill is not supplying power, the BESS could provide entire load demand, which increases the stability of the power system distribution. The UPQC model including series and shunt active filter compensators exists to alleviate grid power quality problems as well as harmonics introduced by non-linear loads. The UPQC shunt compensator collects power from hybrid energy systems, while the load is protected from grid-related power quality issues by the series compensator. The FOPI controller is built with iso-damping characteristics to control the voltage of the DC connection at a desirable level. The gain of the FOPI controller (Kp, Ki, $\lambda$,) is optimally tuned by a Enhanced Seagull with Rooster Update (ES-RU) Algorithm, which merge the concepts of the Seagull Optimization Algorithm (SOA) as well as the Chicken Swarm Optimization Algorithm (CSO).