Nitrogen-phosphorus co-doped reduced graphene oxide (N-P-rGO) was synthesized as an anode material for lithium-ion batteries, through the hydrothermal method, using ammonium dihydrogen orthophosphate (NH 4 H 2 PO 4 ) as both the nitrogen and phosphorus source. FTIR and FESEM-EDS verified that nitrogen and phosphorus were incorporated into the graphene structure, resulting in wrinkled structure with heteroatoms distributed throughout the material. When evaluated as an anode material for LIB, the material exhibits significant improvements over as-received GO. N-P-rGO delivers about 650 mAhg −1 at 0.1Ag −1 , which is 62.5% higher than GO (400 mAhg −1 ). At current densities of 0.2, 0.5, 0.8, and 1.0 A g −1 , the material maintains reversible capacities of 580, 530, 496, and 460 mAhg −1 , respectively. Even at 5 A g −1 , N-P-rGO retains 133 mAhg −1 versus only 30 mAhg −1 for GO, and recovers to 595 mAhg −1 when tested again at 0.1 A g −1 . Cyclic stability tests at 5 Ag −1 reveal that N-P-rGO maintains 120–130 mAhg −1 for over 400 cycles, with over 95% capacity retention and nearly 100% Coulombic efficiency, substantially outperforming GO's 28–30 mAhg −1 with 80–85% retention after just 200 cycles. These results suggest that dual-doping with nitrogen and phosphorus is an effective way to enhance lithium-ion storage in graphene oxide, which increases charge storage capacity in LIBs.
This paper proposes a supervisory control framework for a 6-MW wind farm (WF) comprising four 1.5-MW doubly fed induction generator (DFIG)-based wind turbines (WTs) to improve power quality and mitigate electrical and mechanical stresses under grid-pollution conditions. A backstepping control (BC) strategy is implemented at each WT to regulate active and reactive power while enabling active harmonic compensation through the existing power-electronic converters. A proportional allocation algorithm coordinates the compensation effort among the available WTs according to the load-current magnitude, thereby allowing partial or full-WF harmonic compensation depending on the operating condition. MATLAB/Simulink simulations under variable wind speeds, with an average wind speed of approximately 8.2 m/s, demonstrate accurate tracking of the WF-level active and reactive power references, with steady-state errors below 1.4%. Under nonlinear-load conditions, the proposed compensation strategy reduces the grid-current total harmonic distortion (THD) from 43.02% to 1.37% and from 33.16% to 1.33%, corresponding to reductions of approximately 96.8154% and 95.9891%, while improving the power factor from 0.78 lagging to 0.998. In addition, the rotor-circuit current ripple and electromagnetic torque ripple are reduced by 42% and 37%, respectively, indicating reduced electrical and mechanical stress on the DFIG-based WTs. These results demonstrate that the proposed supervisory and BC-based compensation framework can simultaneously achieve effective power regulation, harmonic mitigation, and stress reduction without requiring dedicated additional active-filter converters.
Fixed series capacitors are effective in increasing transmission line capacity in grid-connected Doubly Fed Induction Generator (DFIG)-based wind farms. Sub-Synchronous Resonance (SSR) phenomena occur when the series capacitors are in operation. The Gate-Controlled Series Capacitor (GCSC) model is used to eliminate the SSR effect. However, while the GCSC can control low series capacitance conditions, it is insufficient in high series capacitance conditions. To address this problem, this study aims to enhance a resonance control model for the Rotor-Side Converter (RSC) and Grid-Side Converter (GSC) circuits to reduce the SSR effect and improve the system's efficiency under different operating conditions in the DFIG. By enhancing the resonance control models for the GCSC and converter circuits, comparisons are made on some parameters in the DFIG at different wind speeds and different fixed series compensation ratios. In these comparisons, evaluations were made using the traditional model, the GCSC model, and the enhanced resonance control model in multiple applications in the RSC and RSC-GSC circuits. In addition, eigenvalue analyses were examined in detail in the comparisons. The results showed that the resonance control models enhanced for the GCSC and RSC-GSC circuits stabilized the system in a short time, and the resulting oscillations were quickly damped.
In this study, the high-resolution numerical simulation of the three-dimensional radiative rotating flow of polyalphaolefins (PAOs)-based nanolubricant with synergistic dispersion of molybdenum disulfide (MoS2) and silicon dioxide (SiO2) hybrid nanoparticles over a permeable surface expansion is presented. Motile bioconvection microorganisms are incorporated in the hybrid nanofluid to maximize the convective thermal performance and to stabilize the matrix of the multiphase solutions. The computational fluid dynamics framework considers the multiphysical coupled effects of the Darcy-Forchheimer porous medium, thermal radiation, heat sources and convective Biot boundary conditions with an aligned magnetic angle. The numerical approach, BVP4c is used to solve the transformed nonlinear equations of the boundary layer, and response surface methodology is applied to the surface topologies for the statistical mapping of the interactive limits of the parameters. It is found from the quantitative evaluations that the dominance of the porosity parameter is that it exactly gives a 67.4012% increase in the secondary skin friction as the porosity factor increases from 0.5 to 2.5. Moreover, the effect of an aligned magnetic field improves the energy transfer rate by 77.47%. The results of a rigorous grid independence matrix test show that when the number of discrete grid nodes is increased beyond (N = 320), all boundary layer fluxes are asymptotically stabilized to within six decimal places. Consequently, absolute convergence results show that the absolute error residuals are always kept within a stable micro-band until 10-8, demonstrating the unprecedented numerical accuracy, stability and reliability of the present simulation for advanced microfluidic thermal management systems.
Lithium-ion battery packs integrated with solar photovoltaic (PV) systems are susceptible to state-of-charge (SOC) imbalance among series-connected cells, which can reduce charging efficiency, usable capacity, and battery lifetime. This study proposes an integrated energy management strategy that combines fractional open-circuit voltage (FOCV)-based maximum power point tracking (MPPT) with predictive SOC-based passive cell balancing for a solar-powered lithium-ion battery system. A 185 W PV module is interfaced with a 13-cell battery pack comprising 3.7 V, 2.6 Ah cells through a boost DC–DC converter. The FOCV-based MPPT regulates the PV operating voltage within 70%–80% of the open-circuit voltage, while the predictive balancing algorithm continuously evaluates individual-cell SOC and selectively activates MOSFET-controlled bypass resistors to reduce SOC disparities. The proposed system is modeled and evaluated in the Typhoon-HIL environment and validated in real time using a Typhoon HIL-402 platform. The system extracts a maximum PV power of 183.95 W and achieves an MPPT efficiency of 98.9%, balancing efficiency of 94.6%, energy-utilization efficiency of 99.2%, and balancing power loss of approximately 0.41 W. The proposed approach also reduces SOC equalization time by 35% relative to the reported baseline. These results demonstrate that the integrated strategy can simultaneously enhance solar energy utilization and improve SOC uniformity in lithium-ion battery systems.
