Search Results (21,133)

The growing adoption of electric vehicles (EVs) and the increasing need for coordinated charging and energy management have highlighted the importance of vehicle-to-everything (V2X) technologies within battery management systems (BMSs). However, existing studies often treat EVs as idealized storage systems, overlooking battery and BMS-related operational constraints, and typically analyze driving, charging, and bidirectional energy exchange in isolation, limiting realistic, end-to-end evaluation of daily operation scenarios. This paper addresses these gaps by analyzing how advanced, BMS-integrated V2X capabilities can be deployed in real-world EV operation, focusing on battery utilization, operational performance, and system-level energy interactions. A unified, scenario-based methodology combines mobility demand, AC/DC charging behavior, and bidirectional V2X services within a single daily operational framework. Representative use cases for both passenger EVs and electric light commercial vehicles (eLCVs) are developed to capture realistic driving patterns, environmental conditions, and energy exchange scenarios. The results indicate that V2X operation can provide substantial gross economic value in the investigated scenarios. For the eLCV cases, the estimated increase in equivalent full cycle (EFC) throughput rate ranges from approximately 14.3% to 30.3%, while combined summer–winter cumulative avoided electricity purchase cost reaches approximately EUR 4033 for the higher-power charging strategy, equivalent to 57.0% of the adopted battery cost reference. The analysis also highlights the strong influence of ambient temperature and usage patterns on energy consumption, charging strategies, and overall system performance. Overall, this work provides a holistic and practical evaluation framework for V2X-enabled BMS operation, demonstrating its potential to improve grid support, enhance energy efficiency, and support sustainable EV integration while balancing economic and battery-lifetime trade-offs. Full article

Anode materials play a pivotal role in a wide range of electrochemical applications, including electrolysis, energy storage, corrosion protection, and industrial oxidation processes. This review provides a comprehensive analysis of recent advances in anode materials, with particular emphasis on their structural characteristics and major preparation methods, including thermal decomposition, electrochemical deposition, sol–gel processing, and magnetron sputtering. The degradation behaviour of anodes under electrochemical operating conditions is also critically discussed, together with strategies for improving their durability and overall performance. Particular attention is given to metal oxide-coated anodes, especially those based on ruthenium oxide (RuO₂) and iridium oxide (IrO₂), which remain the most representative systems in dimensionally stable anode (DSA) research and industrial applications. Emerging coating materials, including Co₃O₄- and carbon-based catalysts, are also reviewed as promising alternatives for reducing noble metal usage while maintaining acceptable electrochemical performance. In addition, the role of intermediate layers in titanium-based anodes is examined, with emphasis on their contribution to coating adhesion, conductivity, interfacial stability, and long-term electrode performance. This review further discusses the applications of anode materials in chlorine- and oxygen-related electrochemical industries and evaluates the performance of DSAs in relation to substrate selection, coating composition, and operational requirements. Alternative furnace technologies for anode baking are also reviewed, including conventional furnace heating, laser heating, and microwave heating, together with representative industrial furnace systems such as muffle, continuous, and vacuum furnaces. Overall, this review provides an integrated overview of the current progress in anode material research and development, while highlighting the key challenges and future directions for improving anode efficiency, durability, and sustainability in industrial electrochemical applications. Full article

Long-duration energy storage (ES) has aroused widespread concern by virtue of its potential in renewable energy consumption and the achievement of carbon neutrality goals. Compressed Carbon Dioxide Energy Storage (CCES) works as one of the most attractive technologies for long-duration ES. However, efficient and economical CCES systems are still lacking. In the present study, two novel CCES systems have been proposed, namely Closed-CCES and Semi-open-CCES. Under typical design conditions, the Closed-CCES system achieves a cycle efficiency of 62.25%, whereas the Semi-open-CCES system, featuring simultaneous cooling, heating, and power outputs, attains a superior energy storage density (ESD) of 7.38 × 10⁷ J·m⁻³. Compared with comparable energy storage systems, the two proposed systems exhibit distinct advantages in cycle efficiency and energy storage density, respectively. As noted by exergy analysis, the key loss source of Closed-CCES is the heat exchanger HE2, while the loss of Semi-open-CCES is mainly concentrated in the thermal storage device HFT1. Sensitivity analysis shows that ambient temperature and thermal storage pressure slightly affect the performance of both systems, while heat exchanger efficiency impacts the performance of Closed-CCES more significantly. Economic assessments reveal that both systems outperform conventional technologies in levelized cost of electricity (LCOE). The Closed-CCES system demonstrates superior economic viability with a lower LCOE of 0.0808 $/kW·h versus 0.0985 $/kW·h for the Semi-open system, with the advantage persisting in various operational scenarios. Research results provide a basis for the practical engineering implementation of CCES technology, contributing to the broader pursuit of long-duration energy storage solutions for carbon neutrality. Full article

With the large-scale integration of high-voltage direct-current (HVDC) transmission systems, the receiving-end AC grid exhibits weak voltage-support capability. Consequently, grid-forming (GFM) battery energy storage converters are required to satisfy both current-limiting and voltage-support requirements during fault conditions. To address the challenge of maintaining GFM characteristics while limiting overcurrent, this paper proposes an improved low-voltage ride-through (LVRT) control strategy based on adaptive virtual impedance. The inherent limitations of switching-based strategies, which may cause overcurrent and instability due to control delays, are analyzed. The feasible region of the adaptive virtual impedance is determined, and a closed-loop regulation scheme based on real-time current-amplitude feedback is developed. To verify the feasibility and effectiveness of the proposed control strategy, hardware-in-the-loop (HIL) experiments are conducted, in which the proposed strategy is compared with existing current-limiting strategies. The results demonstrate that the proposed strategy limits both transient and steady-state fault currents to approximately 1.5 pu while maintaining high converter capacity utilization, with a reactive-power increment of approximately 0.8 pu. Furthermore, under different three-phase voltage sag depths and asymmetric fault conditions, the proposed strategy effectively limits fault currents while maintaining reactive power support, thereby enhancing the transient voltage-support capability of the HVDC receiving-end AC grid. Full article

With the wide-scale deployment of battery packs in a variety of applications, some life cycle challenges are coming to light. These challenges include extending their operational life as a pack given their increasing cell-level imbalances and repurposing their cells into new battery packs to give them a second life, e.g., in grid storage. This paper presents a new circuit topology addressing both issues using active (controlled and nondissipative) cell-to-cell balancing for online operation, i.e., while the battery energy storage system is in use. The proposed circuit design is fast and safe for balancing, relying on current control to target each individual cell’s maximum charging and discharging current, while taking into account the pack current. The design has the lowest number of switches and circuit components compared to the state-of-the-art techniques, and is also flexible, allowing for the addition or replacement of cells in series. Its practical hierarchical control system enables speed, reliability, and reconfigurable limits in real-time operation on the individual cells. Experimental validation is carried out on homogeneous and heterogeneous packs in online operation, and the results demonstrate the speed and efficacy of the proposed technique. Full article

Traditional grid-forming converter (GFC) control faces fundamental challenges in maintaining DC bus stability during rapid power transients, primarily due to the limited dynamic response capability of source-side energy storage devices. To address this, this paper proposes a hybrid control strategy integrating long short-term memory (LSTM) networks with a joint GFC and storage converter (SC) control scheme. The LSTM detects short-term voltage trends from historical DC bus data to generate a feedforward compensation signal, while the joint SC-GFC control dynamically incorporates the GFC’s inertial power demand into the SC’s power reference. Hardware-in-the-loop experiments show that, compared to traditional independent control under the same step transient conditions, the proposed method can reduce power overshoot by approximately 79.2%. The LSTM-enhanced joint control maintains stable power flow and significantly suppresses low-frequency oscillations, validating the necessity of data-driven trend prediction for achieving superior inertial support in practical constrained environments. This work provides a communication-free, practical solution for enhancing GFC performance. Full article

Reversible Solid Oxide Cells (rSOCs) are highly efficient energy conversion systems for power generation in fuel cell mode (SOFC) and energy storage in electrolysis mode (SOEC). These devices are typically manufactured through multi-step processing routes based on conventional functional ceramic fabrication techniques, such as tape-casting, extrusion, screen-printing and spraying. In this work, an alternative mold-casting approach is proposed for the fabrication of planar electrolyte-supported rSOCs. Electrolytes made of 8 mol% yttria-stabilized zirconia (YSZ) were prepared via an aqueous gel-casting process using agarose as the gelling agent. The casting molds were fabricated by 3D printing with polylactic acid (PLA) filament. Dense electrolytes with well-controlled geometries were successfully obtained. Complete cells were produced using porous Ni–YSZ as a fuel electrode and porous lanthanum strontium manganite–YSZ. The cells were microstructurally characterized, and their electrochemical performance was evaluated under both SOFC and SOEC operating conditions at 800–900 °C. At 900 °C, the cell achieved a peak power density of 220 mW cm⁻² in fuel cell mode and an injected current density of 340 mA cm⁻² at 1.3 V in electrolysis mode. Mid-term galvanostatic testing in SOFC mode at 850 °C for 400 h demonstrated good durability and structural stability of the fabricated cells. After the initial stabilization period, the cell exhibited a low degradation rate of 3 mV kh⁻¹. Full article

Fuzzy multi-criteria decision-making is important for technology assessment when expert judgments contain uncertainty, hesitation, and inconsistent evidence. This study develops a T-Spherical Fuzzy-Valued Neutrosophic Set (T-SFVNS)-based MEREC-EDAS framework for evaluating low-carbon cooling and energy-management technologies for data centers. Expert linguistic assessments are represented by T-Spherical Fuzzy-Valued Neutrosophic Numbers and aggregated before a score function is used at the explicit scalarization boundary. Standard MEREC then derives objective criterion weights from criterion-removal effects, and standard EDAS ranks alternatives by their positive and negative distances from the average score profile. The application evaluates nine technologies against ten criteria using assessments from thirty domain specialists. The corrected MEREC calculation assigns the greatest weights to carbon reduction potential (0.127), electricity demand reduction (0.125), maintenance complexity (0.124), operational cost efficiency (0.123), and cooling efficiency (0.123). The final ranking is Direct-to-Chip Liquid Cooling, Liquid Immersion Cooling, AI-Enabled Energy Management, Water-Side Free Cooling, Free-Air Cooling, Rear-Door Heat Exchanger Cooling, Hot/Cold Aisle Containment, Renewable-Powered Cooling, and Thermal Storage-Assisted Cooling. Weight perturbation, q-parameter, leave-one-expert-out, alternative-deletion, dominated-alternative, and multi-method comparisons show that the leading tier is robust, although the exact order of the two liquid-cooling technologies is sensitive in some scenarios. The findings provide a transparent and reproducible decision-support basis while explicitly acknowledging the information compression and rank-reversal limitations of score-based MCDM. Full article

With the high-proportion integration of renewable energy, integrated energy systems face greater demands regarding renewable energy utilisation, power balancing, and operational efficiency. By aggregating distributed generation, energy storage and load resources, integrated energy systems can provide effective support for multi-energy coordinated scheduling. This paper proposes a 24 h day-ahead multi-objective optimal scheduling framework for an integrated hydro–wind–photovoltaic–storage energy system based on multi-objective particle swarm optimisation (MOPSO). Firstly, this paper establishes mathematical models for wind power, photovoltaic (PV), hydropower, and energy storage units. Subsequently, it incorporates the outputs of hydropower, wind power, PV, and storage, along with the charging and discharging of energy storage and the process of purchasing electricity from and selling electricity to the main grid, into a unified optimisation model. The objectives are to maximise economic benefit and variable renewable energy utilisation while minimising the peak-to-valley difference in residual load. To address the conflicts between these multiple objectives, a MOPSO algorithm combined with a normalised weighted scoring method is employed to select a compromise optimal solution. Results from case studies based on typical days of the four seasons and various operational strategies demonstrate that the proposed method can rationally allocate the outputs of different energy sources, reduce the system’s dependence on the main grid, and improve variable renewable energy utilisation, thereby providing a reference for the optimal scheduling of integrated energy systems. Full article

Off-grid photovoltaic (PV) hydrogen production systems must coordinate rapidly varying PV power, battery energy, and the operating states of multiple alkaline water electrolyzers. Inappropriate coordination may lead to PV curtailment, frequent unit switching, and persistent workload concentration on a small number of electrolyzers. This paper develops an efficiency- and load-balanced operation (ELBO) scheme as an improved rule-based supervisory strategy rather than an online optimization method. ELBO adopts a two-level decision structure. A planned number of online electrolyzers is first determined from the moving-average PV power and the reference power associated with high single-unit efficiency. This planned count is then corrected using real-time PV power, battery state of charge, and the previous electrolyzer states. The controller adjusts the powers of the online units before changing their number, uses the battery to bridge temporary power deficits, and distributes the remaining adjustable power under the operating and ramp-rate constraints. Five representative PV profiles selected from one year of measured data were used to compare ELBO with PV-following operation (PFO), multi-electrolyzer coordinated operation (MECO), and an offline mixed-integer linear programming (MILP) benchmark. ELBO produced 1328 kg of hydrogen, which was 8.85% and 6.07% higher than PFO and MECO, respectively. Its overall PV-to-hydrogen efficiency and PV utilization reached 65.2% and 94.9%, respectively, with 36 start–stop events. MILP produced 1345 kg of hydrogen, only 1.28% more than ELBO, but required the complete future PV sequence. Ablation analysis further shows that the planned-count layer, moving-average filtering, battery-supported retention, and load-balancing allocation contribute to different and complementary aspects of capacity matching, operating continuity, and workload distribution. The results indicate that the benefit of ELBO arises from the ordered coordination of these supervisory functions and that it provides a practical compromise between operating performance, workload distribution, information requirements, and computational complexity under the representative conditions considered. Full article

The rapid transition toward electrified mobility and climate neutrality has prioritized the structural and environmental optimization of battery electric vehicle (BEV) subsystems. While vehicle lightweighting enhances operational efficiency, the production phase of structural enclosures and battery cells frequently introduces severe environmental and economic impacts and supply chain vulnerabilities. This study presents a comprehensive cradle-to-gate environmental life cycle assessment (LCA), life cycle costing (LCC), and semi-quantitative social assessment of alternative battery housing materials and battery cell architectures. To achieve a functionally accurate comparison, alternative materials, including a novel recyclable thermoplastic acrylic sheet molding compound (SMC), commercial thermoset SMCs, aluminum (AlMg₃), and stainless steel, are evaluated using an analytical stiffness- and strength-equivalent methodology across three real-world geometric demonstrators. Simultaneously, lithium iron phosphate (LFP) liquid electrolyte prismatic cells and solid-state polymer pouch cells are assessed. Material-level results indicate that, while aluminum minimizes the structural mass, primary aluminum manufacturing exhibits the highest global warming potential and processing costs. Conversely, Polytec SMC and Elium SMC achieve the lowest environmental impacts alongside competitive total production costs. At the cell level, prismatic LFP architectures display superior environmental performance compared to solid-state pouch cells, which suffer from energy-intensive processing and lower volumetric capacity normalization. Demonstrator-level aggregation reveals that the electrochemical cells heavily dominate the environmental and economic footprint of the complete assembly, with the housing accounting for less than 5% of the total global warming potential (GWP) and 1% of the total costs. The social assessment reveals moderate and comparable performance across all systems, with slight advantages for thermoplastic composite-based configurations in terms of circularity potential and innovation perception. Overall, the study highlights the critical importance of the cell architecture and manufacturing processes in determining battery system sustainability, while demonstrating the relevance of lightweight composite housings in reducing the structural mass with a minimal environmental penalty. Full article

With the increasing penetration of wind and photovoltaic generation, microgrids are playing an increasingly important role in promoting renewable energy accommodation, enhancing operational flexibility, and enabling low-carbon energy management. However, the strong uncertainty of renewable generation and load demand, together with the coupling effects of electricity, hydrogen, and carbon markets, poses significant challenges to the optimal planning and operation of microgrid energy storage systems. To address these issues, this paper proposes a bi-level optimal sizing framework for an electric–hydrogen hybrid energy storage system (EHH-ESS) in a microgrid under multi-market coupling. First, typical wind–solar–load scenarios are generated using a Wasserstein generative adversarial network with gradient penalty (WGAN-GP), so as to capture the stochastic characteristics and temporal correlations of renewable generation and load demand. Then, a multi-market coupling index (MCI), integrating electricity price, hydrogen price, and carbon price signals, is constructed to characterize time-varying economic and low-carbon operating incentives and to guide coordinated dispatch decisions. On this basis, a bi-level multi-objective optimization model is established. The upper level determines the optimal capacities of battery storage, electrolyzers, fuel cells, and hydrogen tanks, while the lower level performs hourly coordinated operation of the microgrid under multi-market conditions. The model considers annual equivalent total cost, renewable energy curtailment rate, and carbon emissions as objective functions, and is solved using the NSGA-III algorithm. Compared with the no-storage benchmark, the proposed scheme improves the annual operating economics and renewable-energy accommodation under the studied market conditions. The proposed method significantly reduces annual operating cost and improves renewable energy accommodation. However, under the current carbon price and grid emission factor settings, the optimal economic solution increases carbon emissions relative to the baseline, indicating a trade-off between economic arbitrage and low-carbon operation. Full article

The decarbonization of maritime transportation requires shipboard energy systems to coordinate conventional generators, renewable energy sources, energy storage devices, and thermal energy units under voyage-dependent operating constraints. This paper develops a configurable hybrid multienergy ship system for coordinated electrical and thermal energy scheduling. The proposed framework functionally separates the propulsion subsystem from the service and thermal subsystem while retaining system-level coordination among photovoltaic generation, wind generation, diesel generators, micro gas turbines, energy storage batteries, and thermal energy units. A convolutional neural network is employed to provide short-term photovoltaic power forecasts for day-ahead scheduling. The resulting scheduling problem simultaneously considers voyage completion, power balance, equipment operating limits, ramp-rate constraints, battery charging and discharging restrictions, operating costs, and pollutant emission treatment costs. The nonlinear operating logic is reformulated as a mixed-integer optimization problem and solved using CPLEX. A representative coastal voyage case study is used to evaluate the proposed framework. The results demonstrate that the method can coordinate multiple shipboard energy sources, satisfy the prescribed electrical and thermal demands, and provide a set of Pareto-optimal solutions describing the trade-off between operating cost and emission-related cost. The proposed framework provides a system-level scheduling approach for supporting the economic and low-carbon operation of hybrid multienergy ships under increasingly stringent maritime emission reduction requirements. Full article

The coordinated operation of interconnected multi-carrier energy hubs is a key enabler of cost-efficient and flexible energy management in modern smart cities. This paper develops a comprehensive optimization framework for the day-ahead scheduling of interconnected energy hubs in residential and commercial sectors. The problem is formulated as a mixed-integer linear programming (MILP) model that jointly manages electricity, natural gas, and thermal energy flows. To enhance operational flexibility, the proposed model incorporates demand response programs for both electrical and thermal loads, multiple energy storage technologies, and electric vehicles with vehicle-to-grid (V2G) capability. Six operating scenarios are defined to assess the impact of different resources and coordination levels, ranging from independent hub operation to fully integrated interconnected scheduling. Simulation results show that coordinated operation of the energy hubs, supported by flexible loads, storage systems, and electric vehicles, can significantly reduce total daily operating costs compared with conventional standalone configurations. The findings confirm that energy exchange among hubs, combined with demand-side flexibility and EV participation, improves both economic performance and system efficiency. The proposed framework offers a scalable scheduling approach for future integrated multi-energy systems. Full article

To address output-side high-frequency harmonics in a three-phase-to-single-phase matrix converter (3-1MC) with an inductive compensation unit and topological port asymmetry, two PWM switching-sequence optimization methods are proposed. Without power decoupling, the pulsating power associated with the single-phase output is coupled to the input side through the bidirectional switching network because the converter has no large energy-storage DC link. Under conventional modulation, the state sequence can produce large output-voltage steps and nonuniform commutation paths, thereby increasing switching-frequency harmonic components. The first proposed method avoids direct commutation of the line voltage with the largest instantaneous magnitude to the zero state by inserting line-voltage segments with smaller instantaneous magnitudes. The second method rearranges the switching-state sequence without changing the effective-vector durations, thereby reducing the number of switching transitions within each switching cycle. Compared with the conventional modulation method, Method 1 reduces the output-voltage THD from 35.4% to 31.4%, corresponding to a relative reduction of 11.3%. Method 2 reduces the THD from 35.4% to 27.5%, corresponding to a relative reduction of 22.3%. Full article