Search Results (5)

We have demonstrated the fabrication of laminate composites with functional features to demonstrate energy storage capabilities. The present study investigates the surface modification of carbon fibers by coating dual materials of reduced graphene oxide (rGO) and cellulose-based activated carbon to enhance their energy storage capacitance for the development of structural supercapacitors. The dual coating on carbon fibers enabled a near 210-fold improvement in surface area, surpassing that of pristine carbon fibers. This formed a highly porous graphene network with activated carbon, resulting in a well-connected fiber–graphene-activated carbon network on carbon fibers. The electrochemical supercapacitor, fabricated from surface-functionalized carbon fibers, provides the best performance, with a specific capacitance of 172 F g⁻¹ in an aqueous electrolyte. Furthermore, the symmetrical structural supercapacitor (SSSC) device delivered a specific capacitance of 227 mF g⁻¹ across a wide potential window of 6 V. The electrochemical stability of the SSSC device was validated by a high capacitance retention of 97.3% over 10,000 cycles. Additionally, the study showcased the practical application of this technology by successfully illuminating an LED using the proof-of-concept SSSC device with G-aC/CF electrodes. Overall, the findings of this study highlight the potential of carbon fiber composites as a promising hybrid material, offering both structural integrity and a functional performance suitable for aerospace and automobile applications. Full article

This paper addresses the optimal placement and sizing of Modular Static Synchronous Series Compensators (M-SSSCs) to enhance power system performance. The proposed methodology optimizes four key objectives: reducing transmission line loadability, minimizing power losses, mitigating voltage deviations, and enhancing voltage stability using the L-index. The methodology is validated on two systems: the IEEE 14-bus test network and a sub-area of the Colombian power grid, characterized by aging infrastructure and operational challenges. The optimization process employs three metaheuristic algorithms—Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Teaching–Learning-Based Optimization (TLBO)—to identify optimal configurations. System performance is analyzed under both normal operating conditions and contingency scenarios (N − 1). The results demonstrate that M-SSSC deployment significantly reduces congestion, enhances voltage stability, and improves overall system efficiency. Furthermore, this work highlights the practical application of M-SSSC in modernizing real-world grids, aligning with sustainable energy transition goals. This study identifies the optimal M-SSSC configurations and placement alternatives for the analyzed systems. Specifically, for the Colombian sub-area, the most suitable solutions involve installing M-SSSC devices in capacitive mode on the Termocol–Guajira and Santa Marta–Guajira 220 kV transmission lines. Full article

The distribution of the surface suspended sand concentration (SSSC) in the Yangtze River estuary is extremely complex. Therefore, effective methods are needed to improve the efficiency and accuracy of SSSC inversion. Hyperspectral remote sensing technology provides an effective technical means of accurately monitoring and quantitatively inverting SSSC. In this study, a new framework for the accurate inversion of the SSSC in the Yangtze River estuary using hyperspectral remote sensing is proposed. First, we quantitatively simulated water bodies with different SSSCs using sediment samples from the Yangtze River estuary, and analyzed the spectral characteristics of water bodies with different SSSCs. On this basis, we compared six spectral transformation forms, and selected the first derivative (FD) transformation as the optimal spectral transformation form. Subsequently, we compared two feature band extraction methods: the successive projections algorithm (SPA) and the competitive adaptive reweighted sampling (CARS) method. Then, the partial least squares regression (PLSR) model and back propagation (BP) neural network model were constructed. The BP neural network model was determined as the best inversion model. The new FD-CARS-BP framework was applied to the airborne hyperspectral data of the Yangtze estuary, with R² of 0.9203, RPD of 4.5697, RMSE of 0.0339 kg/m³, and RMSE% of 8.55%, which are markedly higher than those of other framework combination forms, further verifying the effectiveness of the FD-CARS-BP framework in the quantitative inversion process of SSSC in the Yangtze estuary. Full article

With the rapid development of the renewable energy source (RES), network congestion management is increasingly important for transmission system operators (TSOs). The limited transmission network capacity and traditional intervention methods result in high RES curtailment. The near-term, powerful, and flexible solutions, such as advanced flexible AC transmission systems (FACTS), are considered to mitigate the risks. The mobile modular static synchronous series compensator (MSSSC) is one of the grid-enhancing solutions. The mobility of the solution allows it to offer fast deployment and seasonal redeployability with limited cost. The demonstration of the mobile MSSSC solution has shown significant benefits for RES curtailment reduction, network congestion alleviation, and facilitating the demand and RES connection. For unlocking the true value of the mobile solution, they should be optimally allocated in the transmission networks. This paper develops a security-constrained DCOPF-based optimisation tool to investigate the optimal allocation of the mobile MSSSC solution in transmission networks. A linear mobile MSSSC model with the operation dead-band was introduced that can be used in large-scale realistic power system planning. The proposed model was implemented in the IEEE 118-bus system to assess the performance of the mobile MSSSC. Full article

Fluvial sediment dynamics plays a key role in the Amazonian environment, with most of the sediments originating in the Andes. The Madeira River, the second largest tributary of the Amazon River, contributes up to 50% of its sediment discharge to the Atlantic Ocean, most of it provided by the Andean part of the Madeira basin, in particular the Beni River. In this study, we assessed the rainfall (R)-surface suspended sediment concentration (SSSC) and discharge (Q)-SSSC relationship at the Rurrenabaque station (200 m a.s.l.) in the Beni Andean piedmont (Bolivia). We started by showing how the R and Q relationship varies throughout the hydrological year (September to August), describing a counter-clockwise hysteresis, and went on to evaluate the R–SSSC and Q–SSSC relationships. Although no marked hysteresis is observed in the first case, a clockwise hysteresis is described in the second. In spite of this, the rating curve normally used ( $\mathrm{SSSC}={\mathrm{aQ}}^{\mathrm{b}}$ ) shows a satisfactory R² = 0.73 (p < 0.05). With regard to water discharge components, a linear function relates the direct surface flow Q_s–SSSC, and a hysteresis is observed in the relationship between the base flow Q_b and SSSC. A higher base flow index (Q_b/Q) is related to lower SSSC and vice versa. This article highlights the role of base flow on sediment dynamics and provides a method to analyze it through a seasonal empirical model combining the influence of both Q_b and Q_s, which could be employed in other watersheds. A probabilistic method to examine the SSSC relationship with R and Q is also proposed. Full article