Search Results (11,059)

The increasing penetration of renewable energy has made the transient stability of new power systems a critical concern. Grid-forming (GFM) energy storage can provide voltage and frequency support for renewable energy stations. However, existing studies on the transient stability of GFM converters predominantly consider only the synchronization of a GFM converter with an infinite bus and do not fully account for the effects of renewable-energy injection and LVRT control in remote-grid-connected renewable energy stations. To fill this gap, this paper establishes a transient power-angle stability analysis model for a GFM energy storage system in renewable energy stations connected to a remote grid. Based on the equivalent swing equation and the equal-area criterion, the transient instability mechanisms under different renewable energy source LVRT depths are investigated. The results demonstrate that increasing renewable energy output reduces the transient stability margin of the GFM converter. Furthermore, the system exhibits two distinct transient response modes depending on the renewable energy source LVRT depth: under shallow LVRT depth, the GFM converter accelerates first and then decelerates, whereas under deep LVRT depth, it decelerates first and then exhibits a swing-back oscillation. These findings, validated through time-domain simulations, provide a theoretical basis for understanding the effects of renewable energy output, LVRT control, virtual inertia, and virtual damping on the transient stability of GFM-integrated renewable energy systems. Full article

The transport sector contributes nearly 20% of New Zealand’s total greenhouse gas emissions, making it crucial for interventions to meet the 2050 net-zero target. Transitioning to electric vehicles (EVs) presents a sustainable solution but poses challenges in electricity distribution due to unpredictable EV charging behaviours. This research addresses these challenges by developing three mathematical models that optimise EV charging patterns, manage power flow along distribution lines and incorporate battery storage systems. Using the Tāmaki area as a case study, the models analyse total energy demand and optimal battery storage size, revealing that a 3.49 MWh battery system could mitigate the projected 2040 peak daily grid energy demand of 541.5 MWh and avoid costly power line upgrades. The study also introduces a vehicle-to-grid (V2G) integration model, showcasing its potential to reduce grid dependence and improve energy utilisation. The findings provide critical insights for Auckland’s electricity distribution companies, supporting strategic asset upgrades and offering evidence-based guidance for government policies on EV adoption. In summary, this research provides innovative solutions for optimising EV charging infrastructure, benefiting utility companies and policymakers by informing data-driven decisions. The comprehensive approach, which includes power flow, battery storage, and V2G technology, presents a scalable framework for international cities facing similar challenges, promoting global sustainable transport solutions towards achieving international climate targets and sustainable urban development. Full article

For millennia, farmers in cassava’s homeland in the neotropics selected varieties suited to their climate, soils, biological environments, management systems, and nutritional needs. These actions were fundamental to the crop’s success as a reliable staple energy source. After the arrival of Europeans in the New World, these varieties spread first to Africa and later to Asia, where they were further selected for local conditions and needs. The founders of the International Center for Tropical Agriculture in Cali, Colombia, recognized the importance of legacy landrace varieties as sources of genetic diversity for breeding to support tropical production systems, improve nutrition, and boost income. One of earliest activities of the new center, beginning in 1969, was to organize the collection of cassava landraces to establish a genetic resource for breeding purposes at the center’s headquarters in the Cauca Valley. We describe the multifaceted understanding about this remarkable heritage through thorough evaluation over a diverse range of environments and the creation of new varieties aimed at adding value across the crop’s diverse agro-ecologies and uses. CIAT breeders, along with a broad coalition of partners, have targeted demands from growers, processors, and consumers throughout the tropics. Latin American germplasm remains the foundational source of novel, high-value traits that differentiate cassava products across markets, underpinning the continued gains in productivity, quality, and end-use performance. Full article

RNA aptamers are often used as ligand-recognition modules in engineered RNA systems, but integration into larger RNA constructs can influence stability and ligand binding. As a result, aptamer sequences may need to be adapted to new environments while preserving essential properties. Here, we examine this sequence editability problem for the theophylline RNA aptamer. Starting from the experimentally determined structure, we introduced targeted mutations in peripheral structural elements while leaving the recognition site unchanged. The native aptamer, mutated variants, a Mg²⁺-depleted system, and a caffeine-bound control were analyzed using three independent 1 $\mathsf{\mu }$s molecular dynamics simulations. Binding energetics were estimated with multiple end-point as well as alchemical free energy approaches. Results were interpreted together with base pair stability, the conformational landscape of the binding pocket, and per-nucleotide energy contributions. This allows us to predict whether an edit is tolerated or disruptive. Some mutations retained structural and energetic profiles comparable to the native aptamer, whereas others reduced ligand affinity by propagating structural distortions into the binding pocket. These results show that sequence changes outside the binding site can modulate ligand binding indirectly, and that the ligand interaction network is useful for evaluating edited aptamers. The introduced workflow provides a novel combination of established computational strategies for efficient in silico screening of aptamer variants before experimental testing and can be integrated into the design of larger RNA structures. This works particularly well when an experimental structure is available and the tested mutations are small enough not to disrupt the folding pathway. Full article

Buildings have significant impacts on the environment throughout their life cycle in terms of energy and water consumption, material usage, and waste generation. This study aims to evaluate the Sivas Train Station and Sivas High-Speed Train Station buildings, which were constructed in different periods and with different construction techniques, within the scope of sustainable renovation. In the study, the literature on sustainable architecture and building renovation approaches was reviewed; field observations, archival documents, interviews, and on-site measurements of temperature, thermal transmittance, and lighting were utilized. The buildings were compared based on criteria such as energy and water efficiency, material selection, and waste management. The findings indicate that the lack of insulation, old joinery, and absence of windbreaks in the Sivas Train Station, as well as the extensive glass surfaces, high user traffic, entrance layout, and operational issues with technical systems in the High-Speed Train Station, lead to energy losses. The lack of independent monitoring of water consumption in both buildings, the absence of systems for using rainwater, snow and graywater, and the inadequacy of waste separation practices have been identified as significant deficiencies. As a result of the study, different renovation strategies were proposed, preserving the original values of the historical structure and adapting the new structure to real usage conditions. It was concluded that sustainable renovation should be considered a continuous and holistic process that includes not only physical interventions but also building management, user training, regular monitoring, inspection, and certification. Full article

Smart meters are the core terminals for distribution network data acquisition in smart cities, yet their collected data commonly suffer from quality issues caused by harsh operating environments, communication failures, hardware degradation, and human factors. This paper presents a systematic review of anomaly detection and data repair methods for smart meter data based on a critical analysis of many publications. First, we characterize five typical anomalies—sudden jumps, reading stagnation, reverse readings, pulse spikes, and gradual drifts—from physical root causes to data manifestations and provide unified mathematical definitions with explicit traceability to the existing literature. Additional anomaly types including meter replacement jumps, data duplication from retransmission, complete missing segments, and timestamp errors are also discussed to present a more complete picture of operational data quality challenges. Second, existing anomaly detection methods are systematically reviewed and classified into four categories—statistical, machine learning, deep learning, and dedicated time-series methods—with representative studies, quantitative performance metrics, and scenario-specific applicability examined for each. Third, data repair approaches are reviewed across four categories—traditional interpolation, matrix completion, generative models, and time-series prediction—with systematic comparison of their accuracy and limitations across different anomaly types and durations. Based on the synthesized evidence, we identify three cross-cutting structural limitations that persist across method categories: the performance ceiling of data-only detection without physical constraint embedding, the open-loop architecture that separates detection from repair and allows error propagation, and the exclusive reliance on statistical error metrics that fails to distinguish physically plausible repairs from those violating conservation laws. To address these gaps, we discuss a physics-guided integrated framework incorporating physical constraint embedding, joint anomaly diagnosis, scenario-adaptive repair, and posterior verification as a promising forward-looking direction. Finally, open challenges and future research directions are outlined, including parameter adaptation in unlabeled scenarios, multi-source data fusion for physical disambiguation, new power system extensions, explainable AI integration, edge-computing deployment, and standardized benchmark development. This review provides a comprehensive theoretical reference and technical roadmap for smart meter data quality research in the context of smart city energy systems. Full article

Floating Offshore Wind (FOW) enables offshore wind deployment in deeper waters not suitable for bottom-fixed turbines, unlocking new areas for renewable energy generation. Most major cost contributors to FOW have clear pathways for cost reduction however mooring systems are the exception due to the pre-existing market maturity. Solutions to lower mooring costs include Mechanical Compliance Devices (MCDs) aimed at reducing the high peak and snatch loads in mooring lines and thus driving down the capital, operations and maintenance costs. In this paper, a comparison of a physical tank testing campaign and corresponding numerical analysis, for an MCD is described and analysed. The objective of the testing campaign was to validate the component-only tank results with the modelling of an MCD, namely Dublin Offshore’s Load Reduction Device (LRD) using a multi-body dynamics (MBD) approach. The paper presents analysis of the experimental testing and numerical modelling and compares the results with the validated Load–Extension Curve (LEC). Experimental testing was carried out at 1:38.5 scale using bespoke mooring test apparatus at Lír, Ireland’s National Ocean Test Facility. The results of testing are presented for all of the MCD model scales tested and compared with the modelled LEC. The correlation between the experimental and numerical data and with the LEC, characterised by Pearson Correlation Coefficient (R) in the range of 0.952 to 0.999, demonstrates the ability to model the LRD using the MBD approach. Full article

As the construction of new-type power systems continues, the extensive integration of renewable energy and power-electronic devices has significantly increased the risk of cascading failures in power grids, making accurate prediction of cascading-failure evolution paths crucial for grid security. However, real-world fault samples are extremely scarce, and conventional physics-based simulations are too computationally intensive for real-time online early warning. To address these challenges, this paper proposes a cascading failure evolution path prediction method based on massive event chain mining and prior knowledge constraints. First, we construct a refined cascading-failure simulation model that incorporates the action logic of the three defense lines to generate a large standardized event-chain dataset, thereby addressing the data scarcity faced by data-driven models. Second, a sequence-prediction engine that combines word embeddings, LSTM-based temporal modeling, and prior-knowledge constraints is developed; the physical action logic of the power system is explicitly incorporated into the loss function to improve the physical plausibility of the predictions. Finally, an evaluation framework from event prediction to third-defense-line early warning is constructed to assess system-level security risks. Based on simulations of the IEEE 39-bus AC/DC hybrid system, the proposed method is shown to achieve single-step Top-1 accuracies of 97.0% and 96.8% for the system-level critical events of frequency limit violation and system instability, respectively, with corresponding Top-3 accuracies of 99.2% and 99.4%. The overall Top-1 and Top-3 accuracies are 89.8% and 98.2%, respectively; the mean single-inference time is approximately 9.6 ms, corresponding to a speedup of more than 4700 times over conventional time-domain simulation, and the weighted mean early-warning lead time is 1.78 s. Full article

The interfacial reaction between solder and substrate is a critical factor governing joint reliability, making it essential to understand the formation and stability of interfacial reaction layers when developing new high-temperature lead-free solders. This study investigates the interfacial reaction layers formed in Zn-5Al-3Mg solder/Cu substrate joints soldered at 693 K under vacuum. With a binary Zn-Al solder, the Cu substrate is progressively consumed by Zn, and the intermediate phases CuZn₄, Cu₅Zn₈, and CuZn nucleate and grow concurrently at the solder interface. The addition of a minor amount of Mg to the Zn-Al alloy, however, fundamentally alters this reaction sequence. Transmission electron microscopy analyses, including scanning transmission electron microscopy–energy-dispersive X-ray spectroscopy (STEM-EDS), energy-filtered TEM (EF-TEM), and electron diffraction, reveal three distinct interfacial layers: an outer Mg₂Zn₁₁ layer, a middle two-phase mixture of CuZn₄/Mg₂CuZn₃, and an inner Cu₅Zn₈ layer adjacent to the Cu substrate. The biphasic CuZn₄/Mg₂CuZn₃ mixture layer is shown to form via a quasi-peritectic reaction governed by sequential four-phase equilibria in the Zn-Mg-Cu ternary system. These findings demonstrate that minor Mg additions redirect the interfacial reaction pathway between Zn-Al-based solders and Cu substrates, providing new insight for the design of high-temperature Pb-free solder systems. Full article

The purpose of this paper is to derive and propose site-specific joint environmental contours for two eligible Offshore Wind Farm Organized Development Areas (OWFODAs) in the Aegean Sea, Greece. The contours are tailored primarily for the design, structural reliability assessment and definition of site-specific environmental load combinations of offshore wind turbines (OWTs); they are quantified based on publicly available 28-year data sets related to offshore wind and wave conditions, namely, wave height, $H_s$, wave peak period, $T_p$ and mean wind speed at the hub height of the wind turbine, ${\overline{u}}_{hub}$. A new methodology, using the modified Inverse First Order Reliability Method (IFORM), is proposed to accurately reflect the regional climate peculiarities, combined with fifth-order polynomials and a sigmoid function to fit the data of the Weibull parameters and correctly capture the low- and mid-range values of $H_s$, which are statistically far more frequent. Several results, in terms of 2D and 3D contour surfaces for two locations in each OWFODA, for 50-year and 100-year return periods are presented. Finally, two tables are cited: one gathering $H_s$ and $T_p$ values corresponding to the maximum ${\overline{u}}_{\mathrm{h}\mathrm{u}\mathrm{b}}$ conditions, and another gathering ${\overline{u}}_{\mathrm{h}\mathrm{u}\mathrm{b}}$ and $T_p$ values corresponding to the maximum $H_s$ conditions. The presented joint probability distributions and the environmental contour surfaces bridge metocean statistical modelling with renewable energy systems design. By providing site-specific joint metocean conditions, the proposed methodology supports offshore wind farm design and structural assessment, thereby contributing to sustainable wind energy development in the Aegean Sea. Full article

Skeletal muscle is a core component of the motor system, responsible for movement, posture maintenance, and energy metabolism. It plays a vital role in physiological stress, injury repair, and metabolic homeostasis. In recent years, with the advancement of epigenetic research, RNA modification has become a hot topic in skeletal muscle biology. This article systematically reviews the progress in the study of RNA modification in regulating the fate of skeletal muscle, focusing on the dynamic regulatory mechanisms and pathophysiological significance of N6-methyladenosine (m⁶A) modification in muscle differentiation, regeneration, and atrophy. It also briefly introduces the existing evidence for 5-methylcytidine (m⁵C), adenosine-to-inosine (A-to-I) editing, and pseudouridine (Ψ) in skeletal muscle. A comprehensive understanding of these mechanisms is crucial for elucidating the physiological regulation of skeletal muscle and the pathogenesis of related diseases and also provides a new direction for the development of intervention strategies. Full article

During the asymmetric short-circuit period and the fault recovery stage of the renewable energy collection system, the non-fault phase and the PCC point show transient overvoltage characteristics, respectively, which threaten the safe and stable operation of the system. Aiming at the transient overvoltage problem during the asymmetric fault of the renewable energy collection system, this paper first establishes the sequence component equivalent circuit of the renewable energy collection system, deduces the expression of non-fault phase overvoltage at the fault point considering asymmetric fault ride-through control of renewable energy, and reveals the influence of negative-sequence reactive current of renewable energy on non-fault phase overvoltage. Secondly, combined with the system equation and the constraints of overcurrent and overvoltage, the safety region of the renewable energy current reference value under asymmetric fault is established. On this basis, the transient overvoltage comprehensive suppression strategy based on the optimization of the current reference value during fault and the rapid identification of fault clearing time is proposed, which realizes the overvoltage suppression in the full process of asymmetric fault. Finally, the renewable energy collection system is built in the Matlab/Simulink R2023b simulation platform, and the correctness and effectiveness of the transient overvoltage analysis and suppression strategy proposed in this paper are verified. Full article

Driven by the rapid expansion of the new energy industry and the growing demand for photovoltaic (PV) power plant construction, optimizing site selection to ensure operational efficiency and stability has emerged as a critical imperative. Addressing the lack of precise zonation assessment systems for PV development in China’s arid and semi-arid regions, this study introduces a multi-dimensional, five-tier suitability evaluation framework. By integrating Boolean logic, the Bayesian Best–Worst Method (B-BWM), and Equal Interval classification, we developed a multi-resolution integrated assessment framework where spatial boundaries are mainly constrained by 30 m topographic and land-cover data. Results indicate that the candidate PV construction space (the upper two suitability classes, PDSI ≥ 3.40) spans 0.85 million km² concentrated in central-western Inner Mongolia and southeastern Xinjiang, and model validation achieves an Area Under the Curve (AUC) of 0.79. The annual technical potential reaches 19,069 TWh, equivalent to approximately 207% of China’s total electricity consumption in 2023. If fully developed, this potential offers a theoretical annual CO₂ emission reduction ranging from 12.69 to 21.48 billion tons under different conversion efficiency scenarios, with a baseline estimate of 14.65 billion tons. These multi-resolution integrated findings provide a useful spatial reference for preliminary site screening in arid and semi-arid regions, support China’s “Dual Carbon” goals, and offer a practical methodological approach for renewable energy planning on marginal lands. Full article

This study obtained the energy levels and examined the partition function (Z) of a quantum system described by an Eckart-like potential model. By adopting the Greene–Aldrich approximation scheme for the centrifugal term, the radial Schrödinger equation (SE) is solved and the analytic expression of the energy eigenvalues is obtained. The ro-vibrational Z is computed by explicitly incorporating the rotational quantum number, a feature often neglected or misapplied in many studies. This result is used to evaluate the key thermodynamic properties (TP), including the Gibbs free energy (G), entropy (S), and enthalpy (H). Numerical analysis reveals that the Z increases monotonically with temperature, while the G decreases in accordance with statistical thermodynamics. The S exhibits saturation-like behaviour at higher temperatures, while the H displays convex growth with increasing thermal energy. Parametric studies demonstrate that the Eckart-like potential allows for the controlled tuning of TP, with variations in the potential parameters, including the screening parameter, having distinct effects. The results generalise existing models, reproduce the Hulthén potential under specific conditions, show the effect of the rotational quantum number of TP, and provide new insights into the ro-vibrational statistical mechanics of exponential-type potentials. Full article

To address the transient power surges and DC-link voltage fluctuations arising from fast frequency response demands in new power systems, this paper proposes a Natural Switching Surface (NSS) control strategy for active neutral-point clamped (ANPC) converters. First, the operating modes and working principles of the ANPC converter are analyzed, and the phase trajectory relationship between the inductor current and DC-side voltage under diverse operating conditions is mathematically derived. On this basis, a systematic NSS control law is established according to the piecewise mathematical model of the converter. Furthermore, a current-limited NSS control scheme is developed to suppress transient current spikes, which realizes smooth voltage and current output regulation and effectively mitigates power transients and DC voltage fluctuations induced by fast frequency response operations and external power disturbances. Comprehensive simulation and prototype experimental results validate the superior performance of the proposed method. Quantitative comparisons demonstrate that, compared with the conventional PI control, the proposed strategy shortens the converter startup time by 1.5 s, restricts the DC voltage drop within 15 V under power disturbance conditions (in contrast to over 60 V with PI control), and achieves faster dynamic recovery and higher operation stability. The proposed method provides an effective solution for high-performance fast frequency response and stable grid integration of renewable energy and energy storage systems. Full article