Search Results (18,585)

Hydropower stations, as critical infrastructure for basic energy supply, play a pivotal role in ensuring the reliability of power systems through their safe and stable operation. Grounding grids operating long-term in complex soil environments are prone to corrosion and degradation, disrupting current distribution balance and causing spatial asymmetry in the voltage field, thereby compromising system safety. Corrosion branch resistance increment identification based on the electrical network method is typically modeled as a parameter inversion optimization problem. However, this problem exhibits underdetermination and other characteristics, making it difficult for traditional analytical methods to obtain stable solutions. To address this, this paper proposes a quantum perturbation scheduling candidate pool-guided sine–cosine algorithm (QSPSCA). Building upon the classical sine–cosine algorithm framework, it incorporates a dynamic candidate pool with multi-source attractor points and a quantum-inspired long-tail scheduling local refinement operator. This achieves an enhanced and smooth transition between global exploration and local refinement. Comparative experiments based on the CEC2017 benchmark and a hydropower station grounding grid corrosion diagnosis case demonstrate that QSPSCA outperforms multiple comparison algorithms in terms of average optimality and result stability. Furthermore, QSPSCA is applied to three typical engineering-constrained optimization problems. Results demonstrate that, whilst satisfying engineering constraints, this method consistently yields higher-quality feasible solutions with superior convergence accuracy and stability compared to alternative algorithms. Therefore, QSPSCA is not only applicable to underdetermined inversion diagnostics but also provides a solution framework with broad applicability for complex engineering optimization problems under structural symmetry perturbations. Full article

In high-frequency 400 V/48 V matrix planar LLC resonant converters for data center power supplies, enlarged interwinding parasitic capacitance can induce significant transformer-related common-mode (CM) displacement currents. However, the effects of secondary-side rectifier commutation and local winding position on the resulting CM spikes have not been sufficiently clarified. This paper establishes a unified analytical expression for the transformer-related CM current in a converter with a half-bridge primary and a full-bridge synchronous-rectifier (SR) secondary. The analysis shows that asynchronous SR commutation shifts the secondary reference potential and introduces additional excitation through the interwinding parasitic capacitances, thereby producing double-pulse CM current spikes. The unequal spike amplitudes among different secondary-side rectifier units are further explained by the combined effects of local winding position and distributed parasitic coupling. Based on these findings, a shielding-layer scheme was then proposed and verified on a 400 V/48 V, 300 kHz, 3 kW prototype. The experimental results show average reductions of about 15 dB over 150 kHz–800 kHz and 20 dB over 800 kHz–6.5 MHz in the CM voltage spectrum, whereas the prototype achieves a peak efficiency of 97.78%. Full article

Piezoelectric cantilever beam harvesters are widely considered for self-powered bridge monitoring, yet their performance is often constrained by resonance detuning under low-frequency ambient vibrations. This issue is particularly pronounced in bridge environments, where the dominant vibration frequencies are typically low and narrowly distributed. While several frequency tuning strategies have been proposed, their relative effectiveness under bridge-relevant conditions has not been systematically evaluated within a unified experimental framework. This study experimentally evaluated four tuning strategies for cantilever piezoelectric energy harvesters, i.e., spring tuning, magnetic tuning, tip mass adjustment, and beam length modification, to identify effective methods for matching the dominant frequency of bridge deck vibrations. A unified test platform using a common harvester configuration was established, and performance was quantified by resonant frequency alignment, maximum output voltage, and −3 dB bandwidth. Among the four methods, root-based spring tuning showed the best overall performance, achieving frequency matching while retaining strong electrical output, with a maximum voltage of 9.01 V and a bandwidth of approximately 1.5 Hz. Magnetic tuning also provided accurate frequency control, but reduced voltage by 15–25%. By contrast, tip mass and beam length tuning produced larger resonance shifts but caused voltage reductions of up to approximately 50%. Full article

Models are described for calculating the crack initiation times for Alloy 600 and Type 304 SS in PWR and BWR primary coolant circuits, respectively. In PWRs, initiation is defined in terms of the grain boundary oxidation concept of Scott and Le Calvar, whereas in BWRs, cracks are envisioned to nucleate from corrosion pits. In contrast, in BWRs, we envision cracks to nucleate from corrosion pits, with the difference in the two systems being primarily due to electrochemical factors. Thus, in BWR primary coolant and the absence of hydrogen water chemistry (HWC), the oxidizing conditions due to the radiolytic production of H₂O₂ cause the ECP to be significantly more positive than the critical pitting potential. Accordingly, the nucleation and growth of pits due to passivity breakdown and the establishment of differential aeration between the pit nucleus’s internal and external environments, which results in growth of pits to the critical size necessary to satisfy the Kondo criteria for transition of a pit into a crack, is judged to be a realistic scenario. Contrariwise, in PWR primary coolant, the ECP is so negative [≈−1.0 V_she] due to the large amount of pressurizing H₂ present in the circuit [20–60 cm³(STP)/kg H₂O] that the nucleation and growth of pits is not possible. However, Totsuka and Smialowska found that MA Alloy 600 suffers hydrogen-induced cracking (HIC) at an ECP < −0.85 V_she, demonstrating that, in service with a high hydrogen concentration, brittle fractures will occur. The initiation sites were not identified. The crack initiation models for Alloy 600 in PWRs and Type 304 SS in BWRs reproduce the effects of the following independent variables: applied stress, temperature, cold work, grain boundary segregations, water chemistry, pH, and electrochemical potential. The origins of the observed scatter in experimentally measured crack initiation times are discussed, and the challenges of developing a more general crack initiation model (GCIM) are identified. From a mathematical viewpoint, the most significant challenge arises from the nested distributions involving the many parameters and expressions within the GCIM that are either distributed because of an imprecise definition or because some experimentally determined input parameters are experimentally scattered. Additionally, the evolution of semi-elliptical surface cracks resulting from the electrochemical crack length (ECL) being shorter than the classical mechanical crack length (MCL) must be incorporated if the GCIM is to find utility in the water-cooled nuclear power industry where semi-elliptical surface cracks are normally observed. Full article

In this paper, we introduce a new age-dependent reliability class, termed the new better (worse) than renewal used in Laplace transform order after age $t_0$ ($NBRU{L}^{*}{t}_0$). This class extends existing aging notions by characterizing lifetime distributions through renewal-based Laplace transform ordering beyond a specified age threshold. Several theoretical properties of the proposed class are established, including its relationships with classical aging classes. A goodness-of-fit test for exponentiality against the $NBRU{L}^{*}{t}_0$ alternative is developed using the framework of U-statistics, yielding a scale-invariant test statistic with a tractable asymptotic distribution. The asymptotic normality and Pitman asymptotic efficiency of the proposed test are derived, demonstrating superior efficiency relative to several existing nonparametric competitors. Extensive Monte Carlo simulations are conducted to obtain critical values and to assess the power performance of the test under both complete and randomly right-censored samples. The results indicate that the proposed test exhibits high power and robustness, particularly in the presence of aging effects and censoring. Applications to real engineering and medical datasets illustrate the practical relevance of the $NBRU{L}^{*}{t}_0$ class in reliability analysis and survival studies. Full article

The accelerating adoption of electric vehicles (EVs) alongside renewable distributed generators (RE-DGs), particularly solar photovoltaic (PV) and wind-based systems, is reshaping the operational and planning paradigms of modern power distribution networks. In this study, an optimal allocation framework is developed for the simultaneous integration of EV charging stations (EVCSs) and RE-DGs within a looped configuration of the IEEE 33-bus distribution system. Two advanced metaheuristic techniques—Improved Grey Wolf Optimizer (IGWO) and Metaheuristic COOT-Based Optimization (MCBO)—are employed to determine the optimal siting and sizing of these resources. The optimization objectives focus on minimizing active power losses while enhancing voltage stability and reducing overall voltage deviation across the network. Simulation results reveal that the MCBO algorithm demonstrates superior performance, yielding a maximum reduction of 82.49% in active power losses with the integration of standalone PV, and 78.14% when PV is deployed in conjunction with EVCSs. Similarly, wind turbine generator (WTG) integration resulted in a loss reduction of 85.74% without EVCSs and 81.57% with EVCS integration using the same approach. The findings further indicate that looped network configurations consistently outperform traditional radial systems in both loss reduction and voltage profile enhancement, underscoring their suitability for accommodating future EV and renewable energy penetrations in smart distribution grids. Full article

The genus Morpheis Hübner, [1820] (Lepidoptera: Cossidae) represents a taxonomically challenging group within Zeuzerinae, characterised by uniform, simply structured genitalia and significant intraspecific variability in external morphology, specifically in wing pattern, body colouration, and size. The taxonomic status and phylogenetic placement of many Morpheis taxa remain uncertain. Our study provides the first comprehensive taxonomic revision of Morpheis, based on detailed morphological analysis, examination of type specimens, assessment of distribution records, and molecular data. As a result, here we provide the first complete taxonomic list with updated diagnoses and distribution maps, based on 1247 specimen records and 191 publicly available observations. We describe the female genitalia of Morpheis for the first time and provide illustrations of imagoes for all currently recognised species, as well as of available type specimens. Additionally, we describe the immature stages and summarise the trophic associations of known Morpheis species. Based on morphological and molecular data, we recognise 11 valid Morpheis species. We applied molecular-based species delimitation methods, which uncovered far more candidate species within the genus than are recognised by traditional taxonomy, suggesting overlooked cryptic diversity that morphology alone cannot detect. We conclude that the integrative approach used here provides a powerful tool, especially valuable for understudied Zeuzerinae groups with high intraspecific variability in traditional characters. Full article

This paper proposes a collaborative optimal scheduling strategy based on asymmetric Nash bargaining for the integrated electricity–heat–hydrogen multi-microgrid system, which can minimize the overall system operation cost while guaranteeing the dynamic fairness of multi-microgrids energy transactions with full consideration of wind–solar uncertainty. First, a scenario generation method based on temporally correlated Latin hypercube sampling and Wasserstein probability distance-based scenario reduction is adopted to construct representative wind–solar uncertainty scenarios, which effectively mitigates the operational risks arising from wind and solar power output fluctuations in the coordinated dispatch of multi-microgrids. Then, an asymmetric Nash bargaining-based cooperative game model for energy trading is established, with each microgrid’s optimal independent operation cost as the negotiation breakdown point. The alternating direction method of multipliers is used for a distributed solution to obtain the optimal scheme that balances total system cost and trading fairness. Simulation results verify that the proposed strategy can effectively suppress operation risks from renewable uncertainty, significantly cut total system cost by 36.85%, and fully ensure trading fairness among multi-microgrid entities, with favorable engineering application value. Full article

What is the influence of different multilevel governance architectures on the provision of infrastructural powers? Multilevel governance corresponds [i] to the vertical distribution of decisions and responsibilities between territorial spheres of government, or [ii] polycentric relationships among different agents. In this work, the focus is on vertical [Type I], and polycentric models [Type II] are outside the scope of this study. Only the vertical subnational perspective will be considered, which can be associated with federalism, decentralization in administrative, fiscal and political dimensions or the scale of authority exercised by subnational governments. The result is the construction of a scale and typology of multilevel governance in the region, considering the influence on government “infrastructural powers” and, subsequently, indicators of and effective territorial penetration. Full article

Suppose that we have a statistical model with q unknown parameters w, and an estimate $\widehat{w}$, based on a sample of size n. A basic question is: what is the covariance of the estimate? The covariance is needed for the Central Limit Theorem (CLT). This gives a first approximation for the distribution of $\widehat{w}$. But what if $q_n=n$ increases with n? How fast can it increase and the CLT still hold? An answer has so far only been given for the sample mean. The same is true for the Edgeworth expansions. These are expansions in powers of $n^{-1/2}$ for the density and distribution of $\widehat{w}$. For fixed q, these expansions are important, as they show how small n can be for the CLT to apply. When it does, they can greatly improve the accuracy of the CLT. I give conditions that allow for the Edgeworth expansions to remain valid when $q_n=q$ increases with n. Earlier Edgeworth expansions when $q_n=q$ increases, have only been done for a sample mean, and only for a 2nd order Edgeworth expansion. In contrast, I consider a very large class of estimates, the class of non-lattice standard estimates. An estimate is said to be a standard estimate if its mean converges to its true value as n increases, and for $r\ge 1$, its rth order cumulants have magnitude $n^{1-r}$ and can be expanded in powers of $n^{-1}$. For this class of estimates, I show that the Edgeworth expansions hold if $q_n$ grows as a power of n less than $1/6.$ That is, I give these expansions in powers of $n^{-1/2}{q}_n^3$. This large class of estimates has a huge range of potential applications, as estimates of high dimension are common in nearly all areas of applied statistics. The most important type of standard estimate is when $\widehat{w}$ is a smooth function of a sample mean, of dimension p say. When either or both $q_n=q$ and $p_n=p$ increase with n, I give conditions on their growth for the Edgeworth expansions for $\widehat{w}$ to remain valid: the eighth power of p times the sixth power of q cannot grow as fast as n. This holds for fixed $q=q_n$ if $p_n$ grows less than a power of n less than $1/8$. This appears to be the first time when Edgeworth expansions have been given when not one, but two dimensions, are allowed to increase to ∞ with n. This gives two different pathways for allowing an increase in dimensionality. When $q=1$, I give 5th order Edgeworth-Cornish-Fisher expansions for the standardized distribution and its quantiles of any smooth function of a sample mean of dimension $p_n$, when $p_n$ is a power of n less than $1/2$. However for the special case when this function is linear, there is no restriction whatever on how fast $p_n$ can increase! If also the components of the sample mean are independent, then these expansions are in powers of ${\left(np\right)}^{-1/2}$. I also give a method that greatly reduces the number of terms needed for the 2nd and 3rd order terms in the Edgeworth expansions, that is, for the 1st and 2nd order corrections to the CLTs. I also extend these results to the case where $\widehat{w}\in R^q$ is a function of several independent sample means, each of dimension increasing with n, with total dimension p. Full article

Microgrid sizing has traditionally been driven by economic, technical, environmental, and social criteria, while safety has often been treated implicitly or addressed at later stages of design and operation. In this context, safety refers to the prevention of unacceptable harm to people, assets, and the environment through appropriate design margins, protection coordination, operational limits, and risk-aware system configuration. However, the increasing penetration of distributed energy resources, battery energy storage systems, power electronics, and advanced digital control architectures has elevated safety to a critical design dimension that directly influences sizing decisions. Despite its importance, safety remains fragmented across the microgrid literature and lacks unified treatment within sizing-oriented studies. This paper presents a systematic review of microgrid sizing methodologies with a specific focus on safety-related indicators. The review critically examines how distinct safety dimensions—namely energy storage safety, protection and fault tolerance, operational margins and redundancy, grid interaction, cybersecurity, human and environmental safety—are addressed within traditional, artificial-intelligence-based, software-driven, and hybrid sizing approaches. Safety is conceptualized as a cross-cutting design constraint that shapes sizing variables and feasibility boundaries rather than as an independent optimization objective. By synthesizing the existing literature, this work identifies the safety dimensions most strongly coupled with sizing decisions. The paper further analyses how safety-related constraints can be incorporated into sizing frameworks and highlights key research gaps that hinder their systematic integration. The findings aim to provide a structured reference for researchers and practitioners seeking to embed safety considerations into microgrid sizing methodologies. Full article

A coordinated optimization method for emergency repair scheduling and system operation restoration is proposed to address large-scale transmission line outages caused by extreme weather events such as ice and snow disasters. First, an active outage scenario for transmission lines is constructed based on the Jones icing thickness model and an exponential failure probability model, while incorporating the spatial distribution characteristics of ice disasters. Subsequently, a bi-level optimization model with repair resource constraints is developed. The upper-level model determines the transmission line repair schedule with the objective of minimizing the total repair time while taking system power supply restoration efficiency into account. Based on the completion times of line repairs, the lower-level model optimizes the system restoration process by considering power flow constraints, generator start-up processes, and load restoration characteristics. To address the challenges posed by discrete operational states and strongly coupled bi-level constraints that are difficult to solve using conventional approaches, a logic-based Integer L-shaped coordinated solution method is proposed. Finally, the effectiveness of the proposed method is validated through case studies based on the IEEE New England 10-unit 39-bus system. The results demonstrate that the proposed method can significantly improve system load restoration levels while maintaining high repair efficiency. Full article

Transboundary river basins (TRBs) sustain billions of livelihoods, yet they face enduring systemic challenges of cooperative water governance. Although collaborative governance models consistently yield acceptable outcomes, adversarial dynamics and zero-sum approaches continue to dominate transboundary water management. This systematic review synthesizes the peer-reviewed literature (2000–2026) to evaluate how four major governance dimensions—and the cross-cutting integration of the water–energy–food (WEF) nexus—shape the effectiveness of water diplomacy in international basins. Socio-economic analysis reveals that benefit-sharing arrangements grounded in joint investment outperform zero-sum volumetric allocation, though implementation remains constrained by institutional fragmentation and governance lock-in. Power relations analysis demonstrates that material, institutional, knowledge-based, and narrative-framing asymmetries systematically define the range of achievable agreements and the reliability of cooperative commitments, with case analysis from the Nile, Mekong, Tigris–Euphrates, and Central Asian basins showing that comparable hydrological conditions yield divergent diplomatic outcomes depending on how power is distributed. Stakeholder engagement findings indicate that formal participatory mechanisms frequently produce symbolic rather than substantive inclusion, particularly where structural imbalances limit procedural access. Gender analysis provides that women’s inclusion improves agricultural productivity, water-use efficiency, and adaptive capacity—functioning as a governance variable with measurable system-performance effects rather than solely an equity objective. The WEF nexus operates as the integrative mechanism binding these dimensions, reframing diplomacy from volumetric allocation toward adaptive benefit arrangements that coordinate interdependent services across sectors. This review concludes that effective transboundary governance emerges from the concurrent integration of socio-economic benefit-sharing, power-responsive institutions, meaningful stakeholder participation, gender equity, and nexus-based coordination in global TRBs. Full article

Free-space optical (FSO) communication is an attractive high-capacity wireless technology for terrestrial, aerial, and satellite links. However, FSO performance is strongly affected by multiple impairments, including path loss, turbulence attenuation, pointing errors, and equipment loss. Therefore, accurate performance evaluation requires channel modelling that accounts for both deterministic power losses and stochastic channel effects. This paper presents a comprehensive and structured review of FSO channel modelling, covering the transmission, propagation medium, and receiver sections. The composite channel response is represented using a mathematical formulation. Commonly used FSO models are reviewed and organised, including Beer–Lambert and geometrical loss, Kim and Kruse path loss models, Lognormal, Gamma–Gamma, K, and Málaga distributions, along with pointing-error and angle-of-arrival models. Each model is explained in terms of its physical meaning, assumptions, and applicable operating conditions. Lastly, a numerical example is presented to demonstrate how deterministic losses and stochastic channel effects can be combined in FSO performance evaluation. Full article

Spiking neural networks (SNNs) offer inherent advantages in processing temporal information. However, their network topologies are predominantly algorithm-generated, lacking constraints from biological brain connectivity, which limits their bio-plausibility. In our previous work, we constructed a spiking neural network (SNN) by incorporating the topological structure of functional brain networks derived from fMRI data of healthy subjects and proposed an fMRISNN model. This model was further employed as the reservoir layer of a liquid state machine (LSM) to build a speech recognition framework. In this framework, the Lyon ear model and the BSA were used to encode speech signals into spike sequences; however, this approach suffers from high computational cost and limited adaptability to temporal variations. To address these limitations, we propose an enhanced Mel-frequency cepstral coefficient (MFCC)-driven sparse spike encoding method. For the speech recognition task, we systematically compare the two preprocessing pipelines in terms of spike number, spike sparsity, encoding time, and downstream speech recognition performance. Experimental results show that the proposed method generates substantially fewer spikes, achieves markedly higher sparsity, and requires significantly less encoding time, while maintaining nearly the same recognition accuracy under the same LSM-based framework. These findings indicate that improved speech input representation can enhance the computational efficiency of SNN-based speech recognition without compromising recognition capability. In addition, the fMRISNN model significantly outperforms several baseline models with algorithmically generated topologies. Compared with mainstream models reported in the literature, although the deep convolutional neural network (CNN) still achieves higher absolute recognition accuracy, the fMRISNN exhibits clear advantages in terms of model parameter size and theoretical energy efficiency. Full article