G. Jegadeeswari

This paper presents a novel methodology for the strategic placement, control, and integration of a Unified Power Quality Conditioner (UPQC) within grid-connected and islanded microgrid (µG) systems that integrate Distributed Generation (DG). The system is modeled and studied using MATLAB/Simulink. The Point of Common Coupling (PCC) hosts both the DG converters equipped with the battery and the shunt active power filter (APFsh) component of the UPQC. Positioned in series between the grid and the PCC is the UPQC’s series active power filter (APFse). A DC link facilitates the integration of the energy storage system. A key innovation in this approach is the implementation of a fuzzy logic (FLC) based islanding detection and reconnection mechanism, referred to as UPQCIDR, which functions as a secondary control layer. This control strategy enhances the system’s ability to manage voltage interruptions during grid-connected operation, while also addressing reactive power compensation, harmonic distortion, and voltage sags/swells. During both islanded and interconnected modes, the DG converter is responsible for supplying active power, whereas the shunt component of UPQC compensates for harmonic power and reactive demands. Furthermore, the suggested configuration ensures continuous operation of the DG converter during voltage disturbances, including phase jumps, thereby improving overall system resilience and power quality.

This research concentrates on the problem associated with rapid filling of type III hydrogen cylinders in hydrogen-powered aerial vehicles. Rapid filling leads to certain temperature rises in the cylinder due to adiabatic compression and it is jeopardizing the structural integrity. Existing research mainly focused on the effects of pressure variation and temperature rises on hydrogen cylinders. However, there is limited research on the effects of temperature rises in Type III hydrogen storage cylinders incorporated with PTFE-coated aluminium liners under various temperature and mass flow rates related to aerial application. Based on the previous research gap, a 2D axisymmetric cylinder model was developed in ANSYS R21 for a 5 L, 35 MPa Type III PTFE-coated aluminium liner wrapped in carbon fiber hydrogen cylinder. A model analysed under the real gas behaviours through the Redlich-Kwong equation with various inlet conditions of temperature (283–323 K), filling pressure (5–35 MPa) and mass flow rate (0.01–0.05 kg/s). The simulation outcome indicates the increase in internal gas temperature from 293 K to 417 K and the optimum temperature region near the inlet due to recirculatory heating. At a maximum temperature of 323 K, the internal temperature rises up to 600.2K toward the thermal stability limits of PTFE. Due to the insulating properties of PTFE, it reduces the temperature distribution from the inner layer to the outer layer of the cylinder and ensures temperature containment. This research work indicates that a minimum inlet temperature of 283K, a medium filling pressure of 20 MPa, and a moderate mass flow rate of 0.03 kg/s in 6 seconds provide an enhanced thermal stability of the cylinder. This research emphasizes the significance of controlling inlet parameters, not just pressure and flow rate but also temperature, to enhance the safe and efficient lightweight hydrogen storage cylinder used in UAV applications.

Nowadays, Unmanned Aerial Vehicles (UAVs) increasingly support applications in surveillance, logistics, and environmental monitoring, yet their operational capability is fundamentally restricted by the limitations of onboard energy sources. The commonly used lithium-polymer (Li-Po) battery provides low energy density, voltage degradation under various loading conditions, and short endurance, typically limiting the flight duration to approximately 12 minutes. Hydrogen PEMFCs exhibit higher energy density, stable voltage outcomes, and sustainable operation, making them a suitable alternative for long-endurance operations. To examine this inherent property, a 300 W air-cooled PEMFC is integrated into a 450 mm quadcopter test platform and experimentally evaluated under controlled static (non-flight) bench-test conditions at different electrical loading levels, and its performance is compared to a conventional power source. During the bench-scale UAV evaluation, the regulated UAV power bus maintained a stable output voltage of approximately 12.5 V with a current below 4.6 A, demonstrating stable power delivery to the propulsion system. The fuel cell polarization curve shows that voltage reduces from 35.6 V to 32.2 V as current magnitude increases, while power output reaches approximately 14 W. In contrast, the Li-Po battery provides a 0.8 V voltage drop during operation and significantly shorter endurance. During 30-minute operation, the stack temperature increased from 25 °C to 40 °C, indicating stable thermal operation. Comprehensive analysis shows that fuel cell stacks provide better voltage stability, constant power delivery, comparatively stable electrical performance relative to the Li-Po battery, ensuring that it is suitable for potential for long-duration operation UAV operations and improved operational reliability.

This study describes a highly effective process innovation in power conversion architecture for Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) electric vehicle (EV) application, by integrating a photovoltaic (PV) system, a single-ended primary inductor converter (SEPIC), intelligent control techniques, and bidirectional energy transfer capability. The PV system is coupled through a SEPIC converter with adaptive neuro fuzzy inference system based Grey wolf optimisation (ANFIS-GWO) maximum power point technique (MPPT) which effectively controls and maximizes the output voltage from PV under fluctuating irradiance situations, enabling constant direct current (DC) power for other converters. In order to satisfy the high-efficiency and high- voltage demands of EV charging applications, a new high-gain DC-DC converter with high voltage gain and reduced voltage stress across switching devices is proposed. A cascaded ANFIS controller (CANFIS) is employed to control the proposed converter, which includes the outer voltage regulating system producing the reference current and the inner current regulating system producing the optimal duty ratio for interleaved phases, leading to better transient operation, enhanced reliability, and accurate balance current under fluctuating load conditions. The proposed design is further incorporating a bidirectional DC-DC converter and a grid connected voltage source inverter (VSI) to support G2V charging and V2G power transfer among the EV battery and grid. This improves stability of grid, permits demand-side control, and promotes integration of green energy. The efficacy of the proposed systems is confirmed through MATLAB/Simulink, revealing superior voltage gain, efficiency, and improved dynamic response provides a flexible and robust choice for the development of power-grid-integrated EV applications.

The incorporation of renewable sources of energy in the power system of marine application has emerged to be indispensable owing to the requirement of minimizing the fossil fuel consumption and for meeting the ever-augmenting demand for electric power. Among renewable sources, solar energy is playing vital role in energy sectors due to its availability and also it is a green energy alternative. In this research work, a PV-powered Switched Reluctance Motor (SRM) based ship propeller is proposed with the intension of reducing marine pollution and progressing towards a carbon free future. The SRM is selected for this application due to its simple structure, fault tolerant, and reliable, making it highly suitable for ship propulsion. Moreover, for enhancing and stabilizing the variable output from PV, a Super-Lift Luo Converter (LUO) and Adaptive Neuro Fuzzy Inference System (ANFIS) are employed and it compared with conventional converters. The Luo converter being a higher gain DC to DC converter with lesser voltage stress and minimal input current ripple confirms that the PV output voltage is improved to the required higher level of efficiency about 98%. The ANFIS provides quick and improves the dynamic performance index and accurate error compensation of the converter. A Luo converter provides input to the BR converter which is used to energize the phase windings of the SRM. The speed of the motor is maintained constant under varying load situations with the aid of Proportional Integral (PI) controller and Vector control system. In MATLAB, the proposed PV powered SRM based ship propeller is simulated, and based on the results, the performance enhancement of the SRM fed submerged propulsion system is corroborated with notable process innovation.

Efficient DC-DC power conversion is essential for sustainable solar photovoltaic systems. Conventional converters often suffer from leakage currents, higher circuit complexity, and limited flexibility in interfacing with grid-connected inverters. This study introduced a novel hybrid DC-to-DC converter based on the C4S (coupled capacitor combined Cuk-SEPIC) converter, proposed precisely for sustainable solar photovoltaic systems. The designed converter offers a dual output in the form of a bipolar direct current (DC) bus, allowing flexible combination with grid-connected inverters that receive either unipolar or bipolar DC inputs. This setup not only enables effective transfer of power to the grid but also efficiently removes the leakage currents without the necessity of lossy DC-link capacitors from the load-side current loop. Moreover, the magnetic cores are integrated by employing the input and output coupled capacitors, which considerably minimize ripple current and ensure the capability of power extraction from the PV unit. A fuzzy logic controller is employed to dynamically adjust the converter’s action under varying load conditions and solar irradiance. The proposed topology minimizes driver circuits, reduces system complexity, eliminates leakage current without requiring lossy DC-link capacitors, and improves reliability. Simulation results demonstrate stable voltage regulation, reduced ripple, improved efficiency, and superior dynamic response compared to conventional control methods. The proposed converter demonstrates its potential as a high-performance, intelligent, and energy-efficient process innovation for modern sustainable solar energy systems.

Pulse width modulation (PWM) is essential for voltage source inverters (VSI) to generate high-quality voltage outputs. Conventional deterministic PWM generates predictable harmonics, causing clusters that increase acoustic noise. Random PWM (RPWM) disperses harmonic power over a wider frequency range, reducing noise and electromagnetic interference. Many RPWM techniques improve inverter quality, but only partially suppress dominant harmonics and lack effective harmonic spreading. Most studies focus on simulations with limited FPGA implementation or hardware validation. The use of digital tools like VHDL, ModelSim, and MATLAB co-simulation remains underutilized. This paper proposes two-triangle RPWM strategies to enhance harmonic dispersion and reduce total harmonic distortion (THD). Co-simulation results are shown for both SPWM and RPWM, along with comparisons of fundamental voltages, THD, and HSF across different modulation indexes. Additionally, synthesis data for the Xilinx XC3S500E FPGA processor is supplied. The last section offers a comparative analysis and experimental validation of SPWM and RPWM. These techniques enable enhanced inverter performance, lower acoustic noise, and process innovations in power electronic systems.

This study presents an advanced control strategy for switched reluctance motors applied in eco-friendly marine propulsion systems. To address the challenges of low-speed control precision and torque ripple inherent in SRMs, a novel integration of a high-gain DC-DC single-ended primary inductance converter with a bridge resonance converter is proposed to efficiently boost and regulate DC voltage. A proportional-integral (PI) controller optimized via the grey wolf optimization algorithm is developed to enhance speed control accuracy and significantly reduce torque fluctuations. Comparative simulations in MATLAB/SIMULINK (Ver 2024a), supported by hardware prototyping and experimental validation, demonstrate that the GWO-optimized PI controller outperforms classical PI control by delivering superior dynamic response, reduced torque ripple, and precise speed tracking. The proposed approach advances marine electric propulsion technology by offering a robust, efficient, and environmentally sustainable solution for SRM control.