The main aim of this paper is to introduce a framework for the design and modelling of a photovoltaic (PV)-wind hybrid system and its control strategies. The purpose of these control techniques is to regulate continuous changes in the operational requirements of the hybrid system;currently, in power system networks, the distribution of energy plays a major role in maintaining power reliability in distribution systems. In this study, the proposed hybrid system was incorporated with a combined PV and wind energy system. Maximum power point tracking (MPPT) methods have been proposed to achieve maximum efficiency from the designed system. In addition, this study focused on improving the stability of the hybrid system. To improve the power quality and transient stability of the proposed system, we introduce a novel control strategy called the distributed power flow controller (DPFC) implementation with an optimization technique called the lion optimization algorithm(LOA)technique. This LOA control technique was developed for the first time in the application of a DPFC controller in a grid-connected system. The control technique was developed using signals from the system parameters, that is, voltage and current. To tune these parameters, this study used fuzzy logic and lion optimization techniques. The proposed system with controllers was tested in MATLAB/Simulink and the results were compared.

Global energy demand is growing rapidly owing to industrial growth and urbanization. Alternative energy sources are driven by limited reserves and rapid depletion of conventional energy sources (e.g., fossil fuels).Solar photovoltaic (PV), as a source of electricity, has grown in popularity over the last few decades because of their clean, noise-free, low-maintenance, and abundant availability of solar energy. There are two types of maximum power point tracking (MPPT) techniques: classical and evolutionary algorithm-based techniques. Precise and less complex perturb and observe (P&O) and incremental conductance (INC) approaches are extensively employed among classical techniques. This study used a field-programmable gate array (FPGA)-based hardware arrangement for a grid-connected photovoltaic (PV) system. The PV panels, MPPT controllers, and battery management systems are all components of the proposed system. In the developed hardware prototype, various modes of operation of the grid-connected PV system were examined using P&O and incremental conductance MPPT approaches.

In this paper a novel non-isolated bidirectional converter with the features of a quadratic buck-boost voltage gain, continuous input, and continuous output currents; which can be employed in energy storage applications, via., batteries or super capacitors. The proposed converter combines the advantages of high voltage gain, wide voltage range, low voltage stress across power switches, less current ripples, and common ground between the input and output sides. The proposed bidirectional converter comprises ten components: four bidirectional switches, three inductors, and three capacitors. Initially, this brief discusses the converter operation in discharging and charging modes; then, steady-state and dynamic modeling analyses are presented. Furthermore, the proposed converter is compared with recent bidirectional converters considering various performance indices. Additionally, experimentations are conducted on a 300 W, 50 kHz laboratory prototype of the proposed converter. The experimental results confirmed the viability of the proposed converter for energy storage applications with a peak efficiency of 97.9 % in discharging and 97.16 % in charging operation.