The growth of renewable energy in the last two decades has led to the development of new power electronic converters. The DC microgrid can operate in standalone mode, or it can be grid-connected. A DC microgrid consists of various distributed generation (DG) units like solar PV arrays, fuel cells, ultracapacitors, and microturbines. The DC-DC converter plays an important role in boosting the output voltage in DC microgrids. DC-DC converters are needed to boost the output voltage so that a common voltage from different sources is available at the DC link. A conventional boost converter (CBC) suffers from the problem of limited voltage gain, and the stress across the switch is usually equal to the output voltage. The output from DG sources is low and requires high-gain boost converters to enhance the output voltage. In this paper, a new high-gain DC-DC converter with quadratic voltage gain and reduced voltage stress across switching devices was proposed. The proposed converter was an improvement over the CBC and quadratic boost converter (QBC). The converter utilized only two switched inductors, two capacitors, and two switches to achieve the gain. The converter was compared with other recently developed topologies in terms of stress, the number of passive components, and voltage stress across switching devices. The loss analysis also was done using the Piecewise Linear Electrical Circuit Simulation (PLCES). The experimental and theoretical analyses closely agreed with each other.

The design of a solar PV system and its performance evaluation is an important aspect before going for a mass-scale installation and integration with the grid. The parameter evaluation of a solar PV model helps in accurate modeling and consequently efficient designing of the system. The parameters appear in the mathematical equations of the solar PV cell. A Chaos Induced Coyote Algorithm (CICA) to obtain the parameters in a single, double, and three diode model of a mono-crystalline, polycrystalline, and a thin-film solar PV cell has been proposed in this work. The Chaos Induced Coyote Algorithm for extracting the parameters incorporates the advantages of the conventional Coyote Algorithm by employing only two control parameters, making it easier to include the unique strategy that balances the exploration and exploitation in the search space. A comparison of the Chaos Induced Coyote Algorithm with some recently proposed solar photovoltaic cell parameter extraction algorithms has been presented. Analysis shows superior curve fitting and lesser Root Mean Square Error with the Chaos Induced Coyote Algorithm compared to other algorithms in a practical solar photovoltaic cell.

Objectives: To improve power transfer and efficiency in Dual Active Bridge (DAB) converters, this study compares and assesses the Single-Phase Shift (SPS) and Extended Phase Shift (EPS) control techniques. Methods: Using the Dual Active Bridge (DAB) arrangement, the research focuses on implementing SPS and EPS control methods to an Isolated Bidirectional Full-Bridge DC-DC Converter (IBDC). A comprehensive review of the IBDC's operating modes and the EPS's control concept is included in this study. Findings: In comparison with EPS, SPS control is limited by a smaller operating range, higher power loss, and higher circulating current. Conversely, EPS exhibits benefits such as decreased back power flow, increased Zero Voltage Switching (ZVS) range, and decreased current stress. These conclusions are supported by the simulation results, which show that EPS control outperforms SPS in terms of operational stability, harmonics, and efficiency. Under the SPS control at different phase shift minimums, THD is 15.06%; whereas, for EPS it is 12.90%. Novelty: This study demonstrates how EPS outperforms SPS in DAB converters, providing better operational range, THD, and efficiency. Keywords: Isolated Bidirectional Full-Bridge DC–DC Converters (IBDCs), Dual Active bridge (DAB), Single Phase Shift (SPS), Extended Phase Shift (EPS), Current Stress, Power Transmission