Abstract
The presented work employs the multiple random feature kernel mean p-power algorithm (MRFKMP) for the voltage source converter (VSC) control of a three-phase four-wire grid-tied dual-stage photovoltaic-hybrid energy storage system (HESS) to achieve multiple objectives during various induced dynamic conditions. The proposed control enables the VSC to accomplish manifold goals, i.e., reactive power compensation, power quality enhancement, load, power balancing at common coupling point and grid voltage balancing during unity power factor mode of operation. The proposed system is scrutinized under steady-state and numerous dynamic states such as irradiation variation, specified power mode, abnormal grid voltage, load, and grid voltage unbalancing. The seamless control facilitates the swift resynchronization of the grid as well as maintaining stability during islanding and re-synchronization operations while satisfying the necessary load requirements. The associated HESS consisting of battery and ultra-capacitor is competent enough in managing the interruptions occurring on the grid, load and photovoltaic side. The DC bus voltage is controlled by the PI controller, which is tuned by the generalized normal distribution algorithm and kept at the desired level during diverse operating conditions. The optimized DC bus generates an accurate loss component of current and further enhances the VSC performance. The proposed system is investigated by simulation and found acceptable as per IEEE 519 standards.
Highlights
Renewable energy systems (RES), such as photovoltaic (PV) and wind energy systems (WES), have established themselves as a dependable and sustainable green energy source that is adaptable to existing grids [1]
The re-synchronization is initiated at 0.4 s, and the system is kept under intentional islanding for a few cycles to ensure the grid stability, in which the f, ω and Vd of load are matched with the incoming grid
DC Bus Analysis maintain the stability of the system, and it reduces the need for a larger coupling capacitor
Summary
Renewable energy systems (RES), such as photovoltaic (PV) and wind energy systems (WES), have established themselves as a dependable and sustainable green energy source that is adaptable to existing grids [1]. A multiple random feature kernel mean p-power (MRFKMP)based adaptive algorithm is proposed for the VSC control of a three-phase four-wire grid-tied dual-stage PV-HESS system. The GNDO algorithm is utilized for the optimal gain tuning of the PI controller to secure the VDC during various induced dynamic conditions in the system and generate the accurate loss component of current for enhanced VSC performance. The rest of the paper is organized as follows: Section 2 describes the proposed topology and its description; Section 3 presents the implemented control strategies—VSC control, Seamless control, DC-DC bi-directional converter control and GNDO optimized DC link voltage control; Section 4 describes the results and discussions of the presented system during various induced dynamic conditions; Section 5 shows the main conclusions of the research work
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