Measurement: Energy最新文献_第4页

Resilient load frequency control of cyber–physical power systems with off-the-shelf redundant communication channels under FDI attacks 具有现成冗余通信信道的网络-物理电力系统在FDI攻击下的弹性负荷频率控制

Measurement: Energy

Pub Date : 2025-06-16 DOI: 10.1016/j.meaene.2025.100053

Chongxin Huang , Song Deng , Hui Ge

The ICT-dependent cyber–physical power systems are exposed to increasing cyber security threats. It has been revealed that cyber-attacks may significantly deteriorate control performances or even destroy system stability. Since the load frequency control (LFC) application plays a vital role in the frequency stability of power systems, multiple redundant communication channels have been designed for an existing LFC system in advance. This paper considers the real multi-channel feature of the power communication network and proposes a secure signal extraction method for the LFC system against false data injection (FDI) attacks. To ensure the reliability of the measurement and control signals, we adopt the median filtering (MF) algorithm to extract the intact signal from multiple redundant signal channels. Furthermore, we prove that the MF algorithm can always obtain the secure signal from multi-channel signals when the number of normal signals is greater than that of abnormal signals. Eventually, we use the benchmark IEEE 30-bus system to validate the effectiveness of the proposed method.

依赖信息通信技术的网络物理电力系统面临着日益严重的网络安全威胁。据透露，网络攻击可能会显著降低控制性能，甚至破坏系统稳定性。由于负荷频率控制对电力系统的频率稳定性起着至关重要的作用，在现有的负荷频率控制系统中，预先设计了多个冗余通信信道。考虑到电力通信网络的真实多信道特性，提出了一种针对虚假数据注入攻击的LFC系统安全信号提取方法。为了保证测控信号的可靠性，我们采用中值滤波（MF）算法从多个冗余信号通道中提取完整信号。进一步证明了当正常信号的数量大于异常信号的数量时，MF算法总是能够从多通道信号中获得安全信号。最后，我们使用基准IEEE 30总线系统来验证所提出方法的有效性。

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引用次数: 0

A machine learning based model for classifying incipient faults and degree in power transformer windings using voltage current diagram technique 基于电压电流图技术的电力变压器绕组早期故障分类模型

Measurement: Energy

Pub Date : 2025-06-09 DOI: 10.1016/j.meaene.2025.100056

Sametah Macine Ngong , Ftatsi Mbetmi Guy-de-patience , Mohaman Gonza , Ndjiya Ngasop

Power transformers are important components of electrical systems. Their failure or malfunction can have serious consequences, affecting the overall functionality or safety of the electrical system. Rapid and accurate diagnosis of transformer internal faults are key factors of efficient and safe operation. in the literature, several techniques of power transformers windings diagnosis exist. The voltage current diagram is a promising and powerful technique acknowledged to be efficient and quick in winding faults diagnosis. However, two major limitations of this technique reported in the literature are: its inability to detect incipient faults and the method of faults classification which is manual. In this study, two machine learning algorithms (SVM and linear regression) are combined with voltage current diagram to diagnose internal incipient faults by analysing data collected during fault simulations on a layer type power transformer. Three main faults responsible of power transformer failure are considerate: turn to turn short-circuit, buckling stress and axial displacement. For each type of fault, a dataset is generated and the model is trained. The SVM algorithm is used to identify the type of fault (classification), and the linear regression algorithm is used to determine its degree of severity. The highest performance of classification was obtained using the RBF kernel (82 %) and the determination of the degree of severity using R-squared gave a score of 99,9 %.

电力变压器是电力系统的重要组成部分。它们的故障或故障会产生严重后果，影响电气系统的整体功能或安全。快速、准确地诊断变压器内部故障是保证变压器高效、安全运行的关键。在文献中，已有几种电力变压器绕组诊断技术。电压电流图在绕组故障诊断中被认为是一种高效、快速的技术。然而，文献中报道的该技术的两个主要局限性是：无法检测早期故障和故障分类方法是手工的。本研究通过对层状电力变压器故障仿真数据的分析，将两种机器学习算法（SVM和线性回归）与电压电流图相结合，对变压器内部早期故障进行诊断。引起电力变压器故障的三种主要故障是：匝间短路、屈曲应力和轴向位移。对于每种类型的故障，生成一个数据集并训练模型。采用SVM算法识别故障类型（分类），采用线性回归算法确定其严重程度。使用RBF核获得的分类性能最高（82%），使用r平方确定严重程度的得分为99.9%。

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引用次数: 0

Performance evaluation of CO2 reduction in green materials 绿色材料中二氧化碳减排的性能评价

Measurement: Energy

Pub Date : 2025-06-06 DOI: 10.1016/j.meaene.2025.100054

P. Manikandan , E. Veeramanipriya , S. Sumitha

The concrete sector has come under a greater microscope to lower its carbon dioxide emissions due to growing sustainability awareness. Most of the carbon dioxide emissions from the industry are caused by transporting materials and manufacturing Portland cement, the primary binder in concrete. To improve sustainability and achieve net-zero emissions by 2050, the industry has, nevertheless, made a number of hopeful moves in the last ten years. This study examines the permeability conduct of polymer E waste in concrete. Specifically, it finds that the optimal amount of fly ash content in concrete, regardless of the presence of recycled polymer E waste, reduces saturated water absorption and increases it as fly ash mixing increases. With an increase in fly ash and E waste, porosity and sorptivity are somewhat rising. Linear regression in IBM SPSS 23 Statistical analysis is used to demonstrate the compressive strength of the tests using a statistical software. The experimental value is compared with the predicted value using the relationship between the predicted and experimental values of recycled polymer E waste concrete to evaluate the percentage of error. This research examined how the construction industry addresses these sustainability challenges to raise awareness among its stakeholders and the industry itself also the present work is intended to describes the performance assessment and statistical analysis of green building materials (recycled polymer E waste concrete) with the mixture of fly ash and analyzing various characteristics for CO₂ reduction.

由于可持续发展意识的增强，混凝土行业受到了更大的关注，以降低二氧化碳排放。该行业的大部分二氧化碳排放是由运输材料和制造波特兰水泥造成的，波特兰水泥是混凝土的主要粘合剂。然而，为了提高可持续性并在2050年前实现净零排放，该行业在过去十年中采取了一些充满希望的举措。研究了聚合物E废弃物在混凝土中的渗透行为。具体而言，研究发现在不考虑再生聚合物E废弃物的情况下，混凝土中粉煤灰的最佳掺量会降低饱和吸水率，并随着粉煤灰掺量的增加而增加饱和吸水率。随着粉煤灰和电子垃圾的增加，孔隙率和吸附率有所上升。IBM SPSS 23中的线性回归使用统计分析来证明测试的抗压强度使用统计软件。利用再生聚合物E废混凝土预测值与预测值之间的关系，将实验值与预测值进行比较，评价误差百分比。本研究考察了建筑行业如何应对这些可持续性挑战，以提高其利益相关者和行业本身的认识，本研究还旨在描述绿色建筑材料（再生聚合物E废物混凝土）与粉煤灰混合物的性能评估和统计分析，并分析二氧化碳减排的各种特性。

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引用次数: 0

Handling concept drift in data-oriented power grid operations 处理面向数据的电网运行中的概念漂移

Measurement: Energy

Pub Date : 2025-05-31 DOI: 10.1016/j.meaene.2025.100052

Yasushi Miyata , Hiroshi Ishikawa

Data-oriented business transformation, also known as “digitalization”, can improve business tasks by providing better insights into the subject through the data. In digitalizing the power grid, more accurate state recognition from the measurement data is expected to promote a low-cost and stable power supply. Acquiring measurement data from the power grid, clustering, and anomaly detection to recognize the current state could lead to better decision-making for power grid operations. While measurement data serves as the starting point, the interpretation of data trends changes due to the influence of the surrounding environment and aging in the real world. This change in data trends, known as concept drift, poses a challenge to efficient data-oriented power grid operations with accurate state recognition using data clustering models. This is because the data clustering model, especially for complex systems like a power grid, is also built data-oriented, and data trends affect the model. To address this combined challenge of concept drift and its impact on the data clustering model, we propose Re-DBSCAN, a stream data clustering model capable of handling uncertain distributions, to detect concept drift and sequentially update its model for data streams from the power grid. The evaluation uses the WECC179 power grid model to simulate power oscillations and their trend changes with the basic concept drift types: abrupt, incremental, and gradual. Compared to other stream data clustering methods that lack a concept drift detection mechanism, the proposed Re-DBSCAN showed less degradation in purity, indicating higher clustering accuracy. The results suggest that by handling concept drift by detecting data trend changes and sequentially adapting the clustering model, Re-DBSCAN can more accurately cluster measurement data containing concept drift based on its trend changes.

面向数据的业务转换，也称为“数字化”，可以通过数据提供对主题的更好见解，从而改进业务任务。在电网数字化的过程中，从测量数据中更准确地识别状态有望促进低成本和稳定的电力供应。从电网中获取测量数据、聚类和异常检测来识别当前状态，可以为电网运行提供更好的决策。虽然测量数据是起点，但在现实世界中，由于周围环境和老龄化的影响，数据趋势的解释会发生变化。这种数据趋势的变化被称为概念漂移，这对使用数据聚类模型进行准确状态识别的高效数据导向电网运营提出了挑战。这是因为数据聚类模型，特别是像电网这样的复杂系统，也是面向数据构建的，数据趋势会影响模型。为了解决概念漂移的综合挑战及其对数据聚类模型的影响，我们提出了Re-DBSCAN，一种能够处理不确定分布的流数据聚类模型，用于检测概念漂移并根据来自电网的数据流顺序更新其模型。评价采用WECC179电网模型模拟电力振荡及其趋势变化，基本概念漂移类型为突变型、增量型和渐变型。与其他缺乏概念漂移检测机制的流数据聚类方法相比，本文提出的Re-DBSCAN方法纯度下降较小，表明聚类精度更高。结果表明，Re-DBSCAN通过检测数据趋势变化来处理概念漂移，并对聚类模型进行序次调整，可以更准确地根据趋势变化对包含概念漂移的测量数据进行聚类。

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引用次数: 0

Sensing-based monitoring systems for electric vehicle battery – A review 基于传感的电动汽车电池监测系统综述

Measurement: Energy

Pub Date : 2025-05-03 DOI: 10.1016/j.meaene.2025.100050

Ferdous Irtiaz Khan, Md Moinul Hossain, Gang Lu

The swift uptake of Electric Vehicles (EVs) has increased the demand for improved Battery Management Systems (BMS) to ensure the safety, efficiency, and durability of lithium-ion batteries. This review explores the current advancements in EV battery monitoring technologies, with a focus on sensing mechanisms that estimate critical parameters such as battery states and thermal conditions. Various sensor technologies, including image-based methods, acoustic sensing, force sensors, thermal sensors, magnetic probing and optical sensors, are reviewed and discussed, highlighting their advantages, limitations, and suitability for practical applications. Additionally, gaps and challenges within the field are identified, including cell-level sensing, onboard monitoring, data acquisition mechanism, fault diagnostics and the application of sensors for internal analysis. These challenges underscore the necessity of developing scalable, non-invasive, and cost-effective solutions.

电动汽车（ev）的迅速普及增加了对改进电池管理系统（BMS）的需求，以确保锂离子电池的安全性、效率和耐用性。本文探讨了电动汽车电池监测技术的最新进展，重点介绍了用于估计电池状态和热条件等关键参数的传感机制。各种传感器技术，包括基于图像的方法，声学传感，力传感器，热传感器，磁探测和光学传感器，进行了回顾和讨论，突出了它们的优点，局限性，并适合于实际应用。此外，还指出了该领域的差距和挑战，包括细胞级传感、车载监测、数据采集机制、故障诊断以及传感器在内部分析中的应用。这些挑战强调了开发可扩展、非侵入性和具有成本效益的解决方案的必要性。

引用次数: 0

Green synthesis and characterization of nano selenium using the extract of Phyllanthus emblica 余甘子提取物纳米硒的绿色合成及表征

Measurement: Energy

Pub Date : 2025-05-03 DOI: 10.1016/j.meaene.2025.100051

S. Reema Sagitha , V. Aravindan , J. Suvetha Rani , M. Mahendran

To maintain the health of humans, animals, and microorganisms, selenium is a trace and essential micronutrient. Selenium nanoparticles (Se-NPs) have recently garnered the attention of numerous researchers as a result of their outstanding biocompatibility, low toxicity and significant bioavailability. Due to their increased bioactivity, Se-NPs finds extensive use in a variety of biomedical applications. Phyllanthus emblica (an Indian gooseberry) was employed as a stabiliser and reducer in the development of a straightforward method for the synthesis of Se-NPs in the present study. Fourier Transform Infrared Spectroscopy (FT-IR) and UV–Visible Spectroscopy were employed to characterize the synthesized selenium nanoparticles, including their optical properties. The synthesized nanoparticles photocatalytic degradation efficiency was investigated using Methylene Blue (MB) Dye. We tested the antibacterial properties of the synthesized Se-NPs against both gram-positive and gram-negative bacteria using the disc diffusion method. The synthesized Se-NPs demonstrated significant inhibition and antibacterial activity against both gram-positive and gram-negative isolates.

为了维持人类、动物和微生物的健康，硒是一种微量和必需的微量营养素。硒纳米颗粒（Se-NPs）由于其优异的生物相容性、低毒性和显著的生物利用度而引起了众多研究人员的关注。由于其增加的生物活性，Se-NPs在各种生物医学应用中得到了广泛的应用。本文以印度醋栗叶兰为稳定剂和还原剂，建立了一种直接合成Se-NPs的方法。利用傅里叶变换红外光谱（FT-IR）和紫外可见光谱（UV-Visible Spectroscopy）对合成的硒纳米粒子进行表征，包括其光学性质。用亚甲基蓝（MB）染料考察了合成的纳米颗粒的光催化降解效率。采用圆盘扩散法测试了合成的Se-NPs对革兰氏阳性菌和革兰氏阴性菌的抑菌性能。合成的Se-NPs对革兰氏阳性和革兰氏阴性菌株均有明显的抑制和抗菌活性。

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引用次数: 0

Electrical modelling of a grid-connected battery energy storage system via EMS and BMS data 基于EMS和BMS数据的并网电池储能系统电气建模

Measurement: Energy

Pub Date : 2025-04-25 DOI: 10.1016/j.meaene.2025.100048

Mirko Ledro , Jan Martin Zepter , Morten Paludan , Mattia Marinelli

With growing popularity of grid-connected battery energy storage systems (BESSs), operators require electrical models for optimal utilisation. These models should be provided by suppliers or manufacturers based on testing methods applied to individual cells or modules in specialised laboratories. However, operators are also interested in developing electrical models on their own. This paper explores the feasibility of modelling a grid-connected BESS without dismantling it, using only the data from its energy management system (EMS) and battery management system (BMS). The goal is to characterise a BESS directly on-site, controlling it through the available commands of its power converter system (PCS). The aim is to represent the electrical dynamics of the BESS with an equivalent Thevenin electric circuit composed of open circuit voltage, resistances, and capacitances. The overall usable capacity of the BESS and the efficiency of the PCS are also estimated. The subject of the investigation is a 300 kW/652 kWh Nickel-Manganese-Cobalt (NMC) Li-ion BESS composed of ten racks, each equipped with a PCS and ten battery modules. The analysis proves the feasibility of modelling the grid-connected BESS via data from EMS and BMS. An equivalent cell model is derived, with the open circuit voltage and internal impedance expressed for the entire state-of-charge range. The total resistance assumes values in the range of 1.580–2.424 m

Ω

, whereas the total capacitance is 609.5–1,580 kF. Consequently, the normalised total resistance is 3%–4%, aligned with the expectations from other NMC Li-ion cells. Finally, the energy capacity and PCS efficiency are reported as a function of the power of the PCS. The usable energy capacity per rack is approx. 59.7 kWh, which is 91.5% of the rated DC energy capacity, and it is independent of the power at which the BESS is discharged. The PCS efficiency is above 94% when operating at 15% of the PCS rated power or higher, during both rectifier and inverter mode. The obtained efficiency curves differ by approx. 2% from the ones reported in the converters’ data sheet.

随着并网电池储能系统（BESSs）的日益普及，运营商需要最佳利用的电气模型。这些模型应由供应商或制造商根据在专门实验室应用于单个细胞或模块的测试方法提供。然而，运营商也对自己开发电动模型感兴趣。本文探讨了在不拆卸的情况下对并网BESS建模的可行性，仅使用其能源管理系统（EMS）和电池管理系统（BMS）的数据。目标是直接在现场表征BESS，通过其功率转换系统（PCS）的可用命令对其进行控制。目的是用一个由开路电压、电阻和电容组成的等效Thevenin电路来表示BESS的电动力学。对BESS的总可用容量和PCS的效率进行了估计。此次调查的对象是一个300千瓦/652千瓦时的镍锰钴锂离子电池，由十个机架组成，每个机架配备一个PCS和十个电池模块。分析证明了利用EMS和BMS数据对并网BESS进行建模的可行性。推导了等效电池模型，并给出了整个充电状态范围内的开路电压和内部阻抗。总电阻的取值范围为1.580-2.424 mΩ，而总电容为609.5-1,580 kF。因此，标准化总电阻为3%-4%，与其他NMC锂离子电池的预期一致。最后，报告了能量容量和PCS效率作为PCS功率的函数。每个机架的可用能量容量约为。59.7 kWh，为直流额定能量容量的91.5%，与BESS放电功率无关。在整流和逆变两种工作模式下，当工作功率为PCS额定功率的15%或更高时，PCS效率均在94%以上。所得的效率曲线相差大约。2%来自转换器数据表中报告的数据。

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引用次数: 0

Recent advances in the measurement of thermochemical, electrochemical and photochemical efficiency of CO2 conversion to value-added products - its challenges and future directions 二氧化碳转化为增值产品的热化学、电化学和光化学效率测量的最新进展——挑战和未来方向

Measurement: Energy

Pub Date : 2025-04-24 DOI: 10.1016/j.meaene.2025.100049

Sonali Chaudhari, Harsh Pawar, Kajal Pawar, Pavan More

Converting CO₂ into value-added products is a sustainable method of lowering greenhouse gas emissions while producing useful chemicals and fuels. This review examines advancements in thermochemical, photochemical, and electrochemical approaches for CO₂ conversion. Thermochemical methods use high temperatures and metal oxide catalysts for hydrogenation, photochemical processes utilise light energy and semiconductor catalysts for mild reaction conditions, and electrochemical reduction employs diverse electrodes for selective product formation and renewable energy integration. Recent progress in catalyst design, including heterojunctions and nanostructured composites, has enhanced efficiency and stability. The review discusses the types of CO₂ reduction processes and their advantages. The comparative study of CO₂ conversion efficiency has been compared in detail in terms of the yield, selectivity, TON and faradaic efficiency of thermochemical, photochemical, and electrochemical techniques. To overcome the challenges of the three methods, the researcher developed plasma-assisted CO₂ reduction, which was explored as a future perspective.

将二氧化碳转化为增值产品是一种减少温室气体排放的可持续方法，同时生产有用的化学品和燃料。本文综述了热化学、光化学和电化学方法在CO2转化方面的进展。热化学方法使用高温和金属氧化物催化剂进行加氢，光化学过程使用光能和半导体催化剂进行温和的反应条件，电化学还原使用多种电极进行选择性产物形成和可再生能源整合。催化剂设计的最新进展，包括异质结和纳米结构复合材料，提高了效率和稳定性。综述了二氧化碳减排工艺的类型及其优点。从热化学、光化学和电化学技术的产率、选择性、TON和法拉第效率等方面对CO2转化效率的比较研究进行了详细的比较。为了克服这三种方法的挑战，研究人员开发了等离子体辅助二氧化碳还原技术，并将其作为未来的研究方向。

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引用次数: 0

Thermal effects due to harmonics on dry-type transformers: Impact of filters and phase angles 干式变压器谐波的热效应：滤波器和相位角的影响

Measurement: Energy

Pub Date : 2025-04-09 DOI: 10.1016/j.meaene.2025.100045

Mateus Caruso Costa, Marcio Zamboti Fortes, Guilherme Gonçalves Sotelo, Bruno Wanderley França

Integrating distributed energy sources has introduced significant challenges to power quality. One notable issue is the generation of harmonic distortions by power electronics converters, which significantly affect the performance and efficiency of power transformers, leading to overheating and related adverse effects. Traditional metrics for non-sinusoidal currents, such as Total Harmonic Distortion (THD), Harmonic Loss Factor, and K-Factor, do not account for the phase angles of harmonic components. This paper evaluates the steady-state temperature of a dry-type transformer under different current conditions, emphasizing the impact of harmonic amplitudes and phase angles. Typical photovoltaic waveforms were applied experimentally to a custom dry-type transformer. Results demonstrated a temperature increase of up to 35% in harmonic cases, with a 7.9% variation observed between in-phase and out-of-phase harmonics of the same amplitudes. These findings highlight that harmonic phase angles can significantly influence transformer thermal behavior, underscoring the necessity of considering both harmonic amplitude and phase angles for a more accurate evaluation of transformer performance under non-linear loads.

分布式能源的整合给电能质量带来了巨大挑战。其中一个值得注意的问题是电力电子变流器产生的谐波失真，这会严重影响电力变压器的性能和效率，导致过热和相关的不良影响。非正弦电流的传统指标，如总谐波失真 (THD)、谐波损耗因数和 K 因数，没有考虑谐波成分的相位角。本文评估了干式变压器在不同电流条件下的稳态温度，强调了谐波幅值和相位角的影响。实验将典型的光伏波形应用于定制干式变压器。结果表明，在谐波情况下，温度最高可升高 35%，在相同振幅的同相和异相谐波之间观察到 7.9% 的变化。这些研究结果突出表明，谐波相位角会显著影响变压器的热行为，从而强调了同时考虑谐波幅值和相位角的必要性，以便更准确地评估变压器在非线性负载下的性能。

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引用次数: 0

Effect of WC particle shape factor on residual stresses generation at the surfaces level of Ni-WC coatings deposited by the PTAW process WC颗粒形状因子对PTAW沉积Ni-WC涂层表面残余应力产生的影响

Measurement: Energy

Pub Date : 2025-03-24 DOI: 10.1016/j.meaene.2025.100047

Deenadayalan K, Rahul B

This paper presents a comparative study on the residual stress formation in a Nickel-based matrix by the reinforcement of two types of WC particles having two different shape factors (angular and spherical) and density. Three types of coatings were prepared: pure Nickel-based super alloy (Spherical), Nickel-based super alloy with 30 % spherical WC particles, and Nickel-based super alloy with Angular WC particles. The prepared coatings (Ni, Ni-WCS & Ni-WCA) are characterised using the X-Ray Diffraction technique for the subsequent evaluation of residual stress. Namely three techniques Sin2ψ method, William Hall method and the Direct instrumentation method based on XRD were incorporated to determine and compare the residual stresses formed in the coatings. The results exhibited that the Ni and WC shape and form factor had a significant influence on the coating residual stress.

本文对比研究了两种不同形状因子（角形因子和球形因子）和密度的WC颗粒增强后镍基基体中残余应力的形成。制备了纯镍基超级合金（球形）、含30%球形WC颗粒的镍基超级合金和含角形WC颗粒的镍基超级合金三种涂层。制备的涂层(Ni, Ni- wcs &；使用x射线衍射技术对Ni-WCA进行表征，以进行后续的残余应力评估。即采用Sin2ψ法、William Hall法和基于XRD的直接仪器法三种方法来测定和比较涂层中形成的残余应力。结果表明，Ni和WC的形状和形状因子对镀层残余应力有显著影响。

引用次数: 0