Search Results (101)

A transition from fossil fuels to renewable energy is underway to achieve net-zero emissions. The institutional arrangements in Indonesia’s energy transportation sector are crucial for various stakeholders involved in the energy transition. This study combines historical institutionalism with a multi-level perspective to analyze how policy formulation, critical junctures, and path dependence shape institutional changes toward sustainable mobility. The evolution of institutional arrangements can be categorized into three phases: the establishment of fuel-oil-based infrastructure and dependency (1970–2003); the diversification of cleaner fuels through compressed natural gas and biofuels (2004–2014); and the development of affordable and clean energy, focusing on biofuels and electrification (2015 to present). In parallel, a quantitative total cost of ownership analysis of vehicles using different fuel types demonstrates how institutional reforms, fiscal incentives, and regulatory support reshape the economic feasibility of low-carbon technologies. Landscape pressures—such as global decarbonization, fuel import dependence, and energy security challenges—interact with niche innovations, including biofuels, electric vehicles, and hybrid systems, to drive systemic transformation. The findings indicate that institutional changes, supported by quantitative economic evidence and technology diffusion, play a pivotal role in realigning Indonesia’s transport energy regime toward a more resilient, inclusive, and sustainable transition. Full article

Multilevel active bridge converters are potential candidates for many modern high-power DC applications due to their ability to integrate multiple sources while minimizing weight and volume. Therefore, this paper deals with an analytical, simulation-based, and experimentally verified investigation of their circulating current behavior, power factor performance, and power loss characteristics. A high-frequency link analysis framework is developed to characterize voltage, current, and power transfer waveforms, providing insight into reactive power generation and its impact on overall efficiency. By introducing a modulation-based control approach, the proposed converters significantly reduce circulating currents and enhance the power factor, particularly under varying phase-shift conditions. Compared to quadruple active bridge topologies, the discussed multilevel architectures offer reduced transformer complexity and improved power quality, making them suitable for demanding applications such as electric vehicles and aerospace systems. Full article

With the growing adoption of electric vehicles, optimizing the user experience of charging infrastructure has become critical. However, extracting actionable insights from the vast number of user reviews remains a significant challenge, impeding demand-driven operational planning for charging stations and degrading the user experience. This study leverages three pre-trained language models to perform sentiment classification and multi-level topic identification on 168,129 user reviews from Beijing, facilitating a comprehensive understanding of user feedback. The experimental results reveal significant task-model specialization: RoBERTa-WWM excels in sentiment analysis (accuracy = 0.917) and fine-grained topic identification (Micro-F1 = 0.844), making it ideal for deep semantic extraction. Conversely, ELECTRA, after sufficient training, demonstrates a strong aptitude for coarse-grained topic summarization, highlighting its strength in high-level semantic generalization. Notably, the models offer capabilities beyond simple classification, including autonomous label normalization and the extraction of valuable information from comments with low information density. Furthermore, integrating textual and spatial analyses revealed striking patterns. We identified an urban–rural emotional gap—suburban users are more satisfied despite fewer facilities—and used geographically weighted regression (GWR) to quantify the spatial differences in the factors affecting user satisfaction in Beijing’s districts. We identified three types of areas requiring differentiated strategies, as follows: the northwestern region is highly sensitive to equipment quality, the central urban area has a complex relationship between supporting facilities and satisfaction, and the emerging adoption area is more sensitive to accessibility and price factors. These findings offer a data-driven framework for charging infrastructure planning, enabling operators to base decisions on real-world user feedback and tailor solutions to specific local contexts. Full article

This study investigates a lithium-ion battery failure in heating insoles that ignited during normal walking while powered off. Through comprehensive material characterization, electrical testing, thermal analysis, and mechanical gait simulation, we systematically excluded electrical or thermal abuse as failure causes. X-ray/CT imaging localized the ignition source to the lateral heel edge of the pouch cell, correlating precisely with peak mechanical stress identified through gait analysis. Remarkably, the cyclic load was less than 10% of the single crush load threshold specified in safety standards. Key findings reveal multiple contributing factors as follows: the uncoated polyethylene separator’s inability to prevent stress-induced internal short circuits, the circuit design’s lack of battery health monitoring functionality that permitted undetected degradation, and the hazardous placement inside clothing that exacerbated burn injuries. These findings necessitate a multi-level safety framework for lithium-ion battery products, encompassing enhanced cell design to prevent internal short circuit, improved circuit protection with health monitoring capabilities, optimized product integration to mitigate mechanical and environmental impact, and effective post-failure containment measures. This case study exposes a critical need for product-specific safety standards that address the unique demands of wearable lithium-ion batteries, where existing certification requirements fail to prevent real-use failure scenarios. Full article

As industries come under growing pressure to minimize carbon emissions without compromising the efficiency of operations, the integration of energy-aware production scheduling with emerging energy markets, renewable energy, and policy mechanisms is critical. This paper identifies critical shortcomings in current academic and industrial approaches—namely, an excessive reliance on deterministic assumptions, a limited focus on dynamic operational realities, and the underutilization of regulatory mechanisms such as carbon trading. We advocate for a paradigm shift to more robust, adaptable, and policy-compliant scheduling systems that provide space for on-site renewable generation, battery energy storage systems (BESSs), demand-response measures, and real-time electricity pricing schemes like time-of-use (TOU) and real-time pricing (RTP). By integrating recent advances and their critical analysis of limitations, we map out a future research agenda for the integration of uncertainty modeling, machine learning, and multi-level optimization with policy compliance. In this paper, we propose the need for joint efforts from researchers, industries, and policymakers to collectively develop industrial scheduling systems that are both technically efficient and adherent to sustainability and regulatory requirements. Full article

The carbon footprint factor of a power system is a crucial basis for calculating carbon emissions from electricity consumption. However, the current carbon footprint factor of China’s power system faces several issues, such as a limited spatial range, outdated updates, an incomplete accounting scope, and unclear accounting methods. To make the power system’s carbon footprint accounting method and its temporal and spatial scope more comprehensive, this study reconstructs the accounting method based on the emission factor method, adding factors such as transmission losses, power transmission across spatial ranges, and Sulfur hexafluoride (SF₆) gas leakage. This study’s analysis reveals that these three accounting factors have a significant impact on the power system’s carbon footprint factor. In terms of the time dimension, the carbon footprint factor has decreased by more than 20% over the past 18 years, and when the time interval is refined to a monthly scale, the carbon footprint factor exhibits significant seasonal fluctuations. In the spatial dimension, the coefficient of variation (CV) for regional and provincial power system carbon footprint factors reached 27.38% and 29.98%, respectively, in 2022. For the same geographic location, the difference in carbon footprint factors between provincial and regional levels ranged from −73.98% to 119.95%. This study shows that the current carbon footprint factor of the power system has limitations, and there is an urgent need to improve the accounting factors, establish multi-level spatial division standards for provincial and regional scales, and shorten the update intervals while ensuring data timeliness. This will enhance the temporal and spatial accuracy of the carbon footprint factor, providing scientific support for precise carbon emission management. Full article

Background: Exposure to household air pollution (HAP) is one of the primary risk factors for acute lower respiratory infection (ARI) morbidity and mortality among children in low-income settings. This study aimed to examine the relative contribution of residing in deprived neighbourhoods and exposure to HAP on the occurrence of ARI among children using data from the 2014–2015 Chad Demographic and Health Survey (DHS). Methods: We applied multilevel modelling techniques to survey data of 2882 children from 372 communities to compute the odds ratio (OR) for the occurrence of ARI between children of respondents exposed to clean fuels (e.g., electricity, liquid petroleum gas, natural gas, and biogas) and respondents exposed to polluting fuel (e.g., kerosene, coal/lignite, charcoal, wood, straw/shrubs/grass, and animal dung). Results: The results showed that children exposed to household polluting fuels in Chad were 215% more likely to develop ARI than those not exposed to household air pollution (OR = 3.15; 95% CI 2.41 to 4.13). Further analysis revealed that the odds of ARI were 185% higher (OR = 2.85; 95% CI 1.73 to 4.75) among children living in rural residents and those born to teenage mothers (OR = 2.75; 95% CI 1.48 to 5.15) who were exposed to household polluting fuels compared to their counterparts who were not exposed. In summary, the results of the study show that the risk of ARI is more common among children who live in homes where household air-polluting cooking fuel is widely used, those living in rural areas, those living in socioeconomically deprived neighbourhoods and from the least wealthy households, and those born to teenage mothers in Chad. Conclusions: In this study, an independent relative contribution of variables, such as HAP from cooking fuel, neighbourhood deprivation, living in rural areas, being from a low-income household, having a mother who is a manual labourer worker, and being given birth to by a teenage mother, to the risk of ARI among children is established. Full article

Due to the highly demanding operating conditions of the Modular Multilevel Converter (MMC), as well as its inherently complex structure, electric field analysis of the MMC valve is crucial for the safe and stable operation of MMC-HVDC (MMC high voltage direct current) transmission systems. In this paper, a high-speed modeling method for an MMC valve based on data derivation is proposed. Firstly, the relationship between the MMC valve electric field calculation model parameters and the MMC-HVDC transmission system parameters was studied. Based on this, the data derivation system for the electric field calculation model parameters of all components of the MMC valve was established. A modeling parameters database based on empirical knowledge is also used in the calculation process of the data derivation system. The output model parameter matrix includes the geometric parameters, position parameters, and electrical parameters of the components. Based on the output matrix, the electric field calculation model of the converter valve can be quickly generated. Furthermore, to improve the accuracy of the calculations and reduce computation time, a discrete modeling method that combines mesh optimization was proposed. In the process of discretized electric field modeling, a mesh division influence factor based on the accuracy of electric field calculation is proposed. By adjusting the mesh division influence factor during the electric field calculation, the accuracy of the electric field calculation can be optimized rapidly. Finally, the effectiveness and practicality of the high-speed modeling method for the MMC valve are verified through comprehensive case studies conducted on the ±320 kV onshore MMC-HVDC valve. It is demonstrated that the high-speed modeling method proposed in this paper can significantly reduce the modeling time of the converter valve and greatly improve the accuracy of electric field calculation. Full article

Currently, the control strategies of electric power-steering (EPS) systems mainly focus on power-steering torque control. There is no direct relationship between steering torque and steering motion intensity, which makes steering wheel adjustment difficult and does not easily meet the driver’s expectations. This paper proposes a method to represent the driver’s steering intention (steering torque) in the form of steering motion intensity based on the analysis of the dynamic characteristics of the EPS system and vehicle motion dynamics. This method establishes the optimal relationship between steering torque and motion intensity according to Stevens’s law of psychology, providing a theoretical basis for optimizing the driving feel. The study uses lateral acceleration and steering wheel steering angles as intermediate variables to connect the driver’s input information with vehicle dynamics and calculates the steering torque through the inverse dynamics of the steering system and the inverse dynamics of vehicle motion. The nonlinear relationship of steering assistance torque with vehicle speed and steering torque is analyzed into three functional modules. A new comprehensive model is proposed to analyze the characteristics of EPS steering assist based on a “comfortable driving style”, “sporty driving style”, and “multi-level driving style—comfortable driving style at low speed, sporty at medium speed, and heavy at high speed”, corresponding to three different power-steering characteristic maps. Full article

With the high proportion of wind and photovoltaic (PV) power connection in the new electricity system, the system output power volatility is enhanced. When the output fluctuation of the system is suppressed, the pumped storage condition is changed frequently, which leads to the vibration enhancement of the unit and a decrease in the system safety. This paper proposes a pump turbine health evaluation model based on the combination of a weighting method and cloud model in a high proportion wind and PV power connection scenario. The wind–PV output characteristics of the complementary system in a year (8760 h) and a typical week in four seasons (168 h) are analyzed, and the characteristics of frequent working condition transitions of pumped storage units are studied against this background. A five-level health classification system including multi-dimensional evaluation indicators is established, and a multi-level health evaluation based on cloud membership quantification is realized by combining the weighting method and cloud model method. The case analysis of a pumped storage power station within a new electricity system shows that the system as a whole presents typical cloud characteristics (Ex = 76.411, En = 12.071, He = 4.014), and the membership degree in the “good” state reaches 0.772. However, the draft tube index (Ex = 62.476) and the water guide index (Ex = 50.333) have shown a deterioration trend. The results verify the applicability and reliability of the evaluation model. This study provides strong support for the safe and stable operation of pumped storage units in the context of the high-proportion wind and PV power connection, which is of great significance for the smooth operation of the new electricity system. Full article

Due to system failures and the limited overcurrent capability of semiconductor devices, overcurrent in modular multilevel converters (MMC) is a key factor affecting the safe and stable operation of offshore wind power MMC-HVDC (modular multilevel converter high-voltage direct current) transmission systems. This paper proposes a field–circuit coupling analysis method for overcurrent research in MMC valve. The method integrates the electric field characteristics of valves with the analysis of MMC-HVDC systems. Firstly, the development process and influencing factors of overcurrent in valves in offshore wind power MMC-HVDC systems are analyzed. A field–circuit coupling model and an electric field calculation model for MMC valves are established. The electric field characteristics and stray parameters of MMC valves are analyzed synchronously and the result are incorporated into the field–circuit coupling model. The nonlinear transient parameters of surge arresters are calculated, and the results are incorporated into the field–circuit coupling model. Finally, a reasonable overcurrent suppression strategy for offshore MMC-HVDC valves is proposed based on the proposed method. The effectiveness and practicality of the field–circuit coupling overcurrent analysis method are verified through comprehensive case studies conducted on the ±500kV offshore MMC-HVDC valve overcurrent calculation and suppression. Full article

In recent years, with the continuous growth of energy demand and the large-scale deployment of renewable energy sources, the power system’s need for high-capacity power transmission and energy storage systems has increased significantly. In this context, the integration of modular multilevel converters (MMCs) with energy storage (ES) systems has led to the development of the MMC with embedded energy storage systems (ES-MMC), which combines the advantages of both the MMC and the ES system. Over the past few years, research on ES-MMC-related technological issues has emerged rapidly. On this foundation, this paper provides an overview of the ES-MMC in terms of electrical topology, steady-state control strategies, common applications, and the challenges it faces. First, the advantages of various ES interfaces are analyzed, and a comparison on the techno-economic feasibility of different submodules with embedded energy storage is conducted. Then, the main control strategies of distributed ES-MMC are examined from several perspectives. Finally, the paper discusses the advantages of the ES-MMC over traditional solutions in various application scenarios and explores possible future research directions. The final analysis establishes ES-MMC’s advantages over traditional solutions in various application scenarios and explores its potential research prospects. Full article

Nanoscale Cu-rich precipitates (CRPs) play a crucial role in the irradiation embrittlement of reactor pressure vessels (RPVs), and binary Fe-Cu alloys serve as practical models to study the evolution of these precipitates. This study investigates the electrical resistivity of an Fe-1.17 wt.% Cu model alloy aged at 450 °C to enhance the understanding of electrical measurements for the non-destructive assessment of RPV irradiation embrittlement. Multi-level characterization methods were used to obtain quantitative data on multi-scale microstructures, including precipitates, dislocations, and grains. The formation and growth of CRPs were found to align closely with the Johnson–Mehl–Avrami model, and the variation in electrical resistivity showed a strong correlation with the evolution of the microstructure. Combined with detailed quantitative microstructure evolution analysis, an electrical resistivity prediction model that considers microstructural mechanisms has been developed. This model can accurately show the effect of CRPs on resistivity and can potentially be extended to RPV steels with other solute-rich precipitates, with a maximum absolute percentage error not exceeding 5%. These results provide a robust basis for the non-destructive and in-service evaluation of RPV irradiation embrittlement using electrical resistivity. Full article

To address the difficulty in detecting workers’ violation behaviors in electric power construction scenarios, this paper proposes an innovative method that integrates knowledge reasoning and progressive multi-level distillation techniques. First, standards, norms, and guidelines in the field of electric power construction are collected to build a comprehensive knowledge graph, aiming to provide accurate knowledge representation and normative analysis. Then, the knowledge graph is combined with the object-detection model in the form of triplets, where detected objects and their interactions are represented as subject–predicate–object relationship. These triplets are embedded into the model using an adaptive connection network, which dynamically weights the relevance of external knowledge to enhance detection accuracy. Furthermore, to enhance the model’s performance, the paper designs a progressive multi-level distillation strategy. On one hand, knowledge transfer is conducted at the object level, region level, and global level, significantly reducing the loss of contextual information during distillation. On the other hand, two teacher models of different scales are introduced, employing a two-stage distillation strategy where the advanced teacher guides the primary teacher in the first stage, and the primary teacher subsequently distills this knowledge to the student model in the second stage, effectively bridging the scale differences between the teacher and student models. Experimental results demonstrate that under the proposed method, the model size is reduced from 14.5 MB to 3.8 MB, and the floating-point operations (FLOPs) are reduced from 15.8 GFLOPs to 5.9 GFLOPs. Despite these optimizations, the AP50 reaches 92.4%, showing a 1.8% improvement compared to the original model. These results highlight the method’s effectiveness in accurately detecting workers’ violation behaviors, providing a quantitative basis for its superiority and offering a novel approach for safety management and monitoring at construction sites. Full article

This paper presents a comparative analysis of interior permanent magnet synchronous motor (IPMSM) drives powered by symmetrical and asymmetrical cascaded H-bridge multilevel inverters. The asymmetric topology operates using multiple DC sources with different voltage values, generating a voltage waveform with more output voltage levels than its traditional counterpart, all while maintaining the same hardware configuration. The main goal is to demonstrate that asymmetrical multilevel inverters are a promising option for improving the performance of electric drives while maintaining cost-efficiency and reliability. The proposed comparison is conducted through simulations in the MATLAB/Simulink R2024a environment, which allows an in-depth analysis of the dynamic performance of the electric drive. Additionally, the variation of the DC link input power of each H-bridge and the Total Harmonic Distortion (THD) of the voltage and current of the output of the converters were studied for different operating conditions in both cases. The obtained results were confirmed through real-time validation, demonstrating the applicability of electric drives powered by asymmetric converters and the advantages, in terms of efficiency, harmonic content and dynamic performance, in certain conditions of operation in terms of speed and applied load. Full article