Search Results (6,837)

Plant electrical signals are closely related to light conditions, and changes in light intensity lead to variations in the amplitude, frequency, and other characteristics of plant electrical signals. Therefore, real-time analysis of the relationship between plant electrical signals and light factors is crucial for monitoring plant growth status. In this study, Aloe Vera was chosen as the experimental subject, and electrical signal data were collected under different light intensities, followed by preprocessing including wavelet threshold denoising. Furthermore, a hybrid model architecture combining one-dimensional convolutional neural networks (1D-CNNs) and lightweight gated recurrent units (GRUs) was proposed to address the temporal signal characteristics of plant electrical signals and edge computing requirements. The 1D-CNN module extracts local spatial features, which are then modeled in time by the optimized GRU module with channel pruning. Model compression was achieved through parameter quantization. Finally, the computational and storage modules of the model were deployed on an FPGA development board using hardware description language for simulation verification. The results indicate that the system achieved a classification accuracy of 90.1%, a detection time of 43.2 ms, and a power consumption of 4.95 W, demonstrating the comprehensive advantages in terms of accuracy, response speed, and power consumption. This approach effectively improves data processing speed and reduces system power consumption while maintaining high classification accuracy, thereby providing technical support for the development of plant growth monitoring technologies. Full article

Titanium dioxide is attractive for energy storage due to its abundance, stability, non-toxicity, low cost, and favorable electronic/optical properties. Colossal permittivity (CP) in co-doped TiO₂ is mainly linked to defect structures rather than intrinsic bulk behavior. This work studies the dielectric properties of TiO₂ co-doped with niobium and magnesium, synthesized by solid-state reaction. Grain size effects were examined by varying ball milling parameters of (½Mg½Nb)_0.05Ti_0.95O₂ and then were correlated with structure, morphology, and dielectric response. X-ray diffraction (XRD), infrared spectroscopy (FTIR), scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDS), X-ray photoelectron spectroscopy (XPS), and impedance spectroscopy (IS) (40 Hz–10⁶ Hz, 150–370 K) were employed for structural, morphological, and electrical characterization. XRD confirmed the rutile phase. For co-doped samples, larger grains yielded higher dielectric constants, reaching high permittivity (ε′ = 429, T = 300 K, f = 10 kHz at 500 rpm for 2 h). Lower loss tangent (tan δ = 0.11, T = 300 K, f = 10 kHz at 200 rpm for 2 h) is linked to Mg segregation at grain boundaries. The most conductive sample showed the highest dielectric constant, suggesting an IBLC polarization mechanism driven by grain boundary effects. XPS confirmed Nb and Mg incorporation, with Ti⁴⁺ dominant and minor Ti³⁺ from oxygen vacancies and surface hydroxylation/defects. Full article

This article introduces a cost-effective, IoT-enabled flexible energy management system (EMS) for residential photovoltaic (PV) microgrids with battery storage, implemented on an ESP32 microcontroller. The proposed system achieves indirect control over commercial household inverters by altering wattmeter readings and utilizing Modbus communication, thereby avoiding expensive hardware modifications. A significant contribution of this work is enabling the injection of energy from the Battery Energy Storage System (BESS) into the grid, a capability often restricted by commercial inverters. Real-world experimentation validated robust performance of the proposed system, demonstrating its ability to dynamically manage energy flows, achieve minimal tracking errors, and optimize energy usage in response to both flexibility market signals and electricity prices. This approach provides a practical and accessible solution for prosumers to actively participate in energy trading and flexibility markets using widely available technology. Full article

The integration of ultracapacitors into the propulsion systems and implicitly into the hybrid energy storage systems (HESSs) of electric vehicles offers significant prospects for increasing performance, improving efficiency and extending the lifetime of battery systems. However, the realization of these benefits critically depends on the implementation of sophisticated control algorithms. From fundamental rule-based systems to advanced predictive and intelligent control strategies, the evolution and integration of these algorithms are driven by the need to efficiently manage the power flow, optimize energy utilization and ensure the long-term reliability of hybrid energy storage systems. This study briefly presents (in the form of a mini review) the research in this field and the development directions and application of state-of-the-art control algorithms, also highlighting the needs, challenges and future development directions. Based on the analysis made, it is found that from the point of view of performance vs. ease of implementation and computational resource requirements, fuzzy algorithms are the most suitable for HESS control in the case of common applications. However, when the performance requirements of HESSs relate to special and high-tech applications, HESS control will be achieved by using convolutional neural networks. As electric vehicles continue to evolve, the development of more intelligent, adaptive and robust control algorithms will be essential for achieving the full potential of integrating ultracapacitors into electric mobility. Full article

This review provides a critical overview of MXenes, an innovative class of 2D transition metal carbides, nitrides, and carbonitrides, emphasizing their synthesis, properties, and application potential. We systematically examine synthesis methods, contrasting top-down approaches with emerging green alternatives and bottom-up techniques, evaluating each in terms of scalability, cost, and environmental impact. This paper highlights MXenes’ unique characteristics, including high electrical conductivity, tunable surface chemistry, and structural versatility, which enable their use in energy storage, environmental remediation, biomedicine, and electromagnetic shielding. Key challenges such as oxidative instability, interfacial incompatibility, and hazardous etching processes are critically discussed. We identify future research priorities, including defect-engineered stabilization, AI-optimized manufacturing, and advanced integration protocols to bridge the gap between laboratory breakthroughs and industrial deployment. By integrating these insights, this review offers a roadmap for advancing MXenes from laboratory innovation to industrial application. Full article

The ocean, as one of the largest thermal energy storage bodies on earth, has great potential as a thermal-electric energy reserve. Application of the relatively fixed-temperature ocean as the heat sink, and using concentrated solar energy as the heat source, one may construct a mobile power station on the ocean’s surface. However, a traditional solar-based heat source requires a large footprint to concentrate the light beam, resulting in bulky parabolic dishes, which are impractical under ocean engineering scenarios. For buoy-sized applications, the small form factor of the energy collector can only achieve limited temperature differential, and its energy quality is deemed to be unusable by traditional spring-loaded free piston Stirling engines. Facing these challenges, a low-temperature differential free piston Stirling engine is presented. The engine features a large displacer piston (ϕ136, 5 mm thick) made of corrugated board, and an aluminum power piston (ϕ10). Permanent magnets embedded in both pistons couple them through magnetic attraction rather than a mechanical spring. This magnetic “spring” delivers an inverse-exponential force–distance relation: weak attraction at large separations minimizes damping, while strong attraction at small separations efficiently transfers kinetic energy from the displacer to the power piston. Engine dynamics are captured by a lumped-parameter model implemented in Simulink, with key magnetic parameters extracted from finite-element analysis. Initial results have shown that the laboratory prototype can operate continuously across heater-to-cooler temperature differences of 58–84 K, sustaining flywheel speeds of 258–324 RPM. Full article

Buildings with electrified heat pump systems, onsite photovoltaic (PV) generation, and energy storage offer strong potential for demand flexibility. This study compares two storage configurations, thermal energy storage (TES) and battery energy storage (BESS), to evaluate their impact on cooling performance and cost savings. A Model Predictive Control (MPC) framework was developed to optimize system operations, aiming to minimize costs while maintaining occupant comfort. Results show that both configurations achieve substantial savings relative to a baseline. The TES system reduces daily operating costs by about 50%, while the BESS nearly eliminates them (over 90% reduction) and cuts grid electricity use by more than 65%. The BESS achieves superior performance because it can serve both the controllable heating, ventilation, and air conditioning (HVAC) system and the home’s broader electrical loads, thereby maximizing PV self-consumption. In contrast, the TES primarily influences the thermal load. These findings highlight that the choice between thermal and electrical storage greatly affects system outcomes. While the BESS provides a more comprehensive solution for whole-home energy management by addressing all electrical demands, further techno-economic evaluation is needed to assess the long-term feasibility and trade-offs of each configuration. Full article

The last decade has been characterized by a growing environmental awareness and the rise of climate change concerns. Continuous advancement of renewable energy technologies in this context has taken a central stage on the global agenda, leading to a diverse array of innovations, ranging from cutting-edge green energy production technologies to advanced energy storage solutions. In this evolving context, ensuring the sustainability of energy systems—through the reduction of carbon emissions, enhancement of energy resilience, and responsible resource integration—has become a primary objective of modern energy planning. The integration of hydrogen technologies for power-to-gas (P2G) and power-to-power (P2P) and energy storage systems is one of the areas where the most remarkable progress is being made. However, real case implementations are lagging behind expectations due to large-scale investments needed, which, under high energy price uncertainty, act as a barrier to widespread adoption. This study proposes a risk-averse approach for sizing an Integrated Hybrid Energy System considering the uncertainty of electricity and gas prices. The problem is formulated as a mixed-integer program and tested on a real-world case study. The analysis sheds light on the value of synergies and innovative solutions that hold the promise of a cleaner, more sustainable future for generations to come. Full article

Understanding the degradation behavior of lithium-ion batteries under realistic application conditions is critical for the design and operation of Battery Energy Storage Systems (BESS). This research presents a modular, cell-level simulation framework that integrates electrical, thermal, and aging models to evaluate system performance in representative utility and residential scenarios. The framework is implemented using Python and allows time-series simulations to be performed under different state of charge (SOC), depth of discharge (DOD), C-rate, and ambient temperature conditions. Simulation results reveal that high-SOC windows, deep cycling, and elevated temperatures significantly accelerate capacity fade, with distinct aging behavior observed between residential and utility profiles. In particular, frequency modulation and deep-cycle self-consumption use cases impose more severe aging stress compared to microgrid or medium-cycle conditions. The study provides interpretable degradation metrics and visualizations, enabling targeted aging analysis under different load conditions. The results highlight the importance of thermal effects and cell-level stress variability, offering insights for lifetime-aware BESS control strategies. This framework serves as a practical tool to support the aging-resilient design and operation of grid-connected storage systems. Full article

Lithium-ion batteries are extensively used for energy storage in renewable, electronic, and automotive applications. However, once their electrical capacity is exhausted, they become hazardous waste that requires energy-intensive recycling processes. This study investigates the thermodynamic and exergetic behavior of LiMn₂O₄-based lithium-ion batteries subjected to controlled electrical overvoltage from renewable energy sources, aiming to quantify their potential for thermal energy generation and recovery. A detailed mathematical model was developed to describe the coupled heat transfer and electrochemical phenomena occurring during overvoltage conditions, and experimental validation was performed under various voltage levels and charging states. Energy and exergy analyses were applied to determine the configuration yielding the highest conversion efficiency for both new and aged cells. The maximum thermal energy efficiency reached 81% for new batteries and 4% for used batteries, while the corresponding exergetic efficiencies were 5% and 1.6%, respectively. Although this study does not propose the immediate large-scale reuse of spent batteries as thermal devices, the results provide quantitative insight into irreversible energy conversion processes and highlight their potential contribution to waste heat recovery and energy optimization strategies in sustainable industrial systems. This thermodynamic framework offers a novel approach for valorizing end-of-life batteries within circular energy models, reducing environmental impact, and advancing the integration of renewable energy-driven heat recovery technologies. Full article

High-voltage fuses are critical safety components in electric vehicle (EV) battery systems, yet their thermal behavior under charging currents remains insufficiently characterized. This study develops and validates a physics-based thermal resistor-capacitor (RC) network model of a high-voltage melting fuse, accounting for copper elements, quartz sand filling, and polyester casing. Experimental accelerated life tests and current step load profiles were performed in a climate chamber at 70 °C, with temperature measurements at the fuse terminals. The RC model was constructed using material properties and geometry-derived parameters, including three copper element sections, one quartz sand node, and one case node. A discretized state–space formulation was implemented to simulate the transient thermal behavior. The results reveal distinct dynamic and stationary characteristics, with thermal time constants varying strongly between fuse sections. Comparisons with experimental data demonstrate that the proposed model captures both rise time and steady-state behavior, with deviations attributable to contact resistances and parasitic effects. The findings highlight that charging currents in practical profiles typically remain below 50% of fuse current ratings, leaving optimization potential for higher permissible currents, faster charging, and reduced downtime while maintaining safety. The outcome of this model is highly relevant for lifetime prediction models. Full article

Renewable energy sources offer a promising future, backed by mature technologies and a viable pathway toward sustainable energy systems. However, careful planning is necessary to efficiently utilize these resources, especially during site selection. Many rural areas lack access to grid electricity, making off-grid hybrid wind-solar power an attractive solution. In the Tigray region of Ethiopia, no such research has been conducted before. This study aims to identify suitable sites for hybrid wind-solar power for rural electrification using Geographic Information System (GIS), Analytic Hierarchy Process, and Monte Carlo simulation. The criteria fall into three categories: Climate, Topography, and Infrastructure, prioritized through pairwise comparisons by thirteen experts from five organizations engaged in renewable energy research, planning, and operations. Monte Carlo simulation was used for sensitivity analysis to address uncertainties in expert judgments and validate the rankings. The spatial analysis reveals 6470 km² as highly suitable for off-grid solar, 76 km² for off-grid wind with predominant easterly winds, and 177 km² as most favorable for hybrid generation. Areas of good suitability measure 447 km² for wind, 44,128 km² for solar, and 16,695 km² for hybrid systems. Based on this assessment, techno-economic analysis quantified the Levelized Cost of Energy (LCOE) under varying solar–wind shares and battery autonomy days. The analysis shows a minimum LCOE of $0.23/kWh with one-day storage and $0.58/kWh with three-day storage, indicating shorter autonomy is more cost-effective while longer autonomy enhances reliability. Sensitivity analysis shows financial parameters, particularly discount rate and battery capital cost, dominate system economics. Full article

Power-to-Heat and Seasonal Thermal Energy Storage are emerging technologies that facilitate the integration of variable renewable energy sources into building and district energy systems. This review synthesizes recent advancements in technologies, integration strategies, and case studies, with a particular focus on nearly zero-energy buildings and nearly zero-energy districts. A structured literature survey, prioritizing sources from 2020 to 2025, was conducted to map available options. The analysis includes Power-to-Heat systems, primarily electric boilers and heat pumps, as well as various seasonal thermal energy storage configurations, including Aquifer Thermal Energy Storage, Borehole Thermal Energy Storage, Pit Thermal Energy Storage, Tank Thermal Energy Storage, and Packed Bed Thermal Energy Storage. The findings indicate that coupling renewable energy with Power-to-Heat and seasonal thermal energy storage can significantly enhance the flexibility of buildings and district systems, reducing the curtailment of renewable sources by utilizing surplus electricity from renewable generation, particularly during periods of low demand, and lowering the environmental impact of buildings and district heating networks. Full article

In response to China’s “Dual Carbon” goals, this paper proposes a Transmission Network Expansion Planning (TNEP) model that explicitly incorporates the operational flexibility of Virtual Power Plants (VPPs). Unlike conventional approaches that focus mainly on transmission investment, the proposed method accounts for the aggregated dispatchable capability of VPPs, providing a more accurate representation of distributed resources. The VPP aggregation model is characterized by the inclusion of electric vehicles, which act not only as load-side demand but also as flexible energy storage units through vehicle-to-grid interaction. By coordinating EV charging/discharging with photovoltaics, wind generation, and other distributed resources, the VPP significantly enhances system flexibility and provides essential support for grid operation. The vertex search method is employed to delineate the boundary of the VPP’s dispatchable feasible region, from which an equivalent model is established to capture its charging, discharging, and energy storage characteristics. This model is then integrated into the TNEP framework, which minimizes the comprehensive cost, including annualized line investment and the operational costs of both the VPP and the power grid. The resulting non-convex optimization problem is solved using the Quantum Particle Swarm Optimization (QPSO) algorithm. A case study based on the Garver-6 bus and Garver-18 bus systems demonstrates the effectiveness of the approach. The results show that, compared with traditional planning methods, strategically located VPPs can save up to 6.65% in investment costs. This VPP-integrated TNEP scheme enhances system flexibility, improves economic efficiency, and strengthens operational security by smoothing load profiles and optimizing power flows, thereby offering a more reliable and sustainable planning solution. Full article

The large-scale integration of renewable energy sources has made power generation highly susceptible to climate variability, increasing operational risks within power systems. The growing frequency of extreme weather events has further intensified uncertainty and stochasticity, thereby elevating risks to supply security. To enhance the operational resilience of modern power systems under extreme weather conditions, this study proposes a multi-temporal and multi-spatial power supply planning model that explicitly incorporates the impacts of such events. First, the effects of extreme weather on the source–grid–load framework are analyzed, and a radiation attenuation model for the rainy season as well as a spatiotemporal evolution model for hurricanes are developed. Subsequently, a climate-dependent power output model is established, employing the Finkelstein–Schafer statistical method to construct a Typical Meteorological Year, which serves as input for the reliable power source modeling. Furthermore, a two-stage power supply planning model based on generation adequacy was established to optimize the location and capacity of various types of backup power sources. Case studies conducted on the IEEE 24-bus system demonstrate that optimized planning of thermal power units and energy storage systems can mitigate the overall power shortfall during extreme weather events, thereby improving the system’s ability to maintain a reliable electricity supply under adverse climate conditions. Full article