Time-Domain Protection for Transmission Lines Connected to Wind Power Plant based on Model Matching and Hausdorff Distance

The system impedance instability,high-order harmonics,and frequency offset are main fault characteristics of wind power system.Moreover,the measurement angle of faulty phase is affected by rotation speed frequency component,which causes traditional directional protections based on angle comparison between voltage and current to operate incorrectly.In this paper,a time-domain protection for connected to wind power plant based on model matching is proposed,which compares the calculated current and the measured current to identify internal faults and external faults.Under external faults,the calculated current and measured current waveform are quite similar because the protected transmission lines is equivalent to a lumped parameter model and the model itself is not damaged.However,the similarity of calculated current and measured current is quite low,due to destroyed integrity of model under internal faults.Additionally,Hausdorff distance is introduced to obtain the similarity of the calculated current and measured current.Since the proposed protection scheme is applied in time domain,it is independent from current frequency offsets of wind energy system,high-order harmonics,and system impedance variations.Comprehensive case studies are undertaken through Power Systems Computer Aided Design(PSCAD),while simulation results verify the accuracy and efficiency of the proposed approach in fault identification.

Perfectly matched layer-absorbing boundary condition for finite-element time-domain modeling of elastic wave equations

The perfectly matched layer （PML） is a highly efficient absorbing boundary condition used for the numerical modeling of seismic wave equation. The article focuses on the application of this technique to finite-element time-domain numerical modeling of elastic wave equation. However, the finite-element time-domain scheme is based on the second- order wave equation in displacement formulation. Thus, the first-order PML in velocity-stress formulation cannot be directly applied to this scheme. In this article, we derive the finite- element matrix equations of second-order PML in displacement formulation, and accomplish the implementation of PML in finite-element time-domain modeling of elastic wave equation. The PML has an approximate zero reflection coefficients for bulk and surface waves in the finite-element modeling of P-SV and SH wave propagation in the 2D homogeneous elastic media. The numerical experiments using a two-layer model with irregular topography validate the efficiency of PML in the modeling of seismic wave propagation in geological models with complex structures and heterogeneous media.

Crystallography of Zr poisoning of Al-Ti-B grain refinement using edge-to-edge matching model

The mechanism of zirconium poisoning on the grain-refining efficiency of an Al-Ti-B based grain refiner was studied. The experiment was conducted by melting Al-5Ti-1B and Al-3Zr master alloys together. The edge-to-edge matching model was used to investigate and compare the orientation relationships between the binary intermetallic compounds present in the Al-Ti-B-Zr system. The results show that the poisoning effect probably results from the combination of Al3 Zr with Al3 Ti and the decreased amount of Ti solute, for Al3 Ti particles have good crystallographic relationships with Al3 Zr. Totally six orientation relationships may present between them, while they play vital roles in grain refinement. TiB2 particles appear to remain unchanged because of a bit large misfit. Only one orientation relationship may present between them to prevent Al3 Zr phase from forming on the surface of TiB2, though TiB2 is agglomerated. The theoretical calculation agrees well with the experimental results. The edge-to-edge matching model is proved to be a useful tool for discovering the orientation relationships between phases.

Forward heuristic breadth-first reasoning based on rule match for biomass hybrid soft-sensor modeling in fermentation process

Biomass is a key parameter in fermentation process, directly influencing the performance of the fermentation system as well as the quality and yield of the targeted product. Hybrid soft-sensor modeling is a good method for on-line estimation of biomass. Structure of hybrid soft-sensor model is a key to improve the estimating accuracy. In this paper, a forward heuristic breadth-first reasoning approach based on rule match is proposed for constructing structure of hybrid model. First, strategy of forward heuristic reasoning about facts is introduced, which can reason complex hybrid model structure in the event of few known facts. Second, rule match degree is defined to obtain higher esti- mating accuracy. The experiment results of Nosiheptide fermentation process show that the hybrid modeling process can estimate biomass with higher accuracy by adding transcendental knowledge and partial mechanism to the process.

Cumulative logit model in the analysis of endometrial cancer under a matched pair case-control design

Background: Binary as well as polytomous logistic models are widely used for estimating odds ratios when the exposure of prime interest assumes unordered multiple levels under matched pairs case-control design. In our previous studies, we have shown that the use of a polytomous logistic model for estimating cumulative odds ratios when the outcome (response) variable is ordinal (in addition to being polytomous) under matched pairs case-control design. The cumulative odds ratios were estimated based on separate fitting of the model at each of the cutpoint level as compared to less than equal to that level. In this paper we propose an alternative method of estimating the cumulative odds ratios and reanalyze the Los Angeles Endometrial Cancer data in the context of dose levels of conjugated oestrogen exposure and development of endometrial cancer under the matched pair case-control design. Methods: In the present study, the cumulative logit model is fitted using a single multinomial logit model for the data. For this, the full maximum likelihood estimation procedure is adopted. A test for equality of the cumulative odds ratios across the exposure levels is proposed. Results: The analysis revealed that there is a strong evidence of risk for developing endometrial cancer due to oestrogen exposure above each of the three dose level as compared to less than equal to that level. The estimated values at the three cutpoint levels were found to be 6.17, 3.60 and 5.16 respectively. Conclusions: The odds of developing endometrial cancer are very high for the users of any amount of oestrogen, even if it is the least dose, as compared to the non-users.

基于Modelica语言的某气垫船机桨匹配建模及仿真

为满足某型气垫船推进系统的性能指标,开展基于国产化软件平台的机桨匹配算法研究。以某型气垫船的推进系统为对象,建立数学模型,并以基于Modelica语言的国产仿真平台MWorks为基础对该系统进行建模仿真。通过研究变螺距角、变转速时气垫船推进系统的性能,对机桨匹配算法进行优化。仿真结果表明,优化算法可满足螺距角变距时间要求、螺距角稳态误差要求以及燃机机动性能曲线要求,所提出的机桨匹配控制算法满足性能要求,研究结果可为类似气垫船推进系统设计提供借鉴。

Stochastic Modeling and Assisted History-Matching Using Multiple Techniques of Multi-Phase Flowback from Multi-Fractured Horizontal Tight Oil Wells

In this paper, the methods developed by?[1] are used to analyze flowback data, which involves modeling flow both before and after the breakthrough of formation fluids. Despite the versatility of these techniques, achieving an optimal combination of parameters is often difficult with a single deterministic analysis. Because of the uncertainty in key model parameters, this problem is an ideal candidate for uncertainty quantification and advanced assisted history-matching techniques, including Monte Carlo (MC) simulation and genetic algorithms (GAs) amongst others. MC simulation, for example, can be used for both the purpose of assisted history-matching and uncertainty quantification of key fracture parameters. In this work, several techniques are tested including both single-objective (SO) and multi-objective (MO) algorithms for history-matching and uncertainty quantification, using a light tight oil (LTO) field case. The results of this analysis suggest that many different algorithms can be used to achieve similar optimization results, making these viable methods for developing an optimal set of key uncertain fracture parameters. An indication of uncertainty can also be achieved, which assists in understanding the range of parameters which can be used to successfully match the flowback data.

智慧城市建设与城市数字经济发展——基于双重差分模型的实证分析

选取2011—2020年中国299个城市的面板数据,运用多期双重差分模型实证检验智慧城市试点政策对城市数字经济发展水平的影响。研究表明:智慧城市试点政策对城市数字经济发展水平有显著的促进作用,这一结论通过了倾向得分匹配、排除其他干扰政策和更换政策冲击时间等多种稳健性检验。机制分析表明:智慧城市建设通过提高信息基础设施和信息产业水平来促进城市数字经济发展。异质性分析显示:智慧城市试点政策在科教水平和行政级别较低的城市对数字经济发展的促进作用更大。

燃料电池增程式动力系统能量管理策略研究

以某款纯电动客车为研究对象,以增加车辆续驶里程为目的,提出燃料电池增程式混合动力系统结构,根据性能指标对动力系统各部件进行匹配计算和选型.提出了开关/功率跟随式能量管理策略,基于Cruise和Simulink分别搭建了整车动力系统模型和燃料电池及能量管理策略模型并进行联合仿真.结果表明,采用文中提出的能量管理策略车辆经济性相对于开关式和能量跟随式两种控制策略分别提高62%和31%,续驶里程相对于该两种控制策略分别提高41%和18%.

基于倾斜三维模型与机载LiDAR点云的DEM快速更新

随着倾斜摄影技术的发展和实景三维建设的不断推进,地形级实景三维地理场景对DEM现势性要求日益提高。为了解决传统方法更新DEM成本高、工作量大的问题,本文提出了利用倾斜三维模型成果转换点云,融合两期DSM和DOM进行变化检测,替换已有机载LiDAR点云,快速更新DEM的方法,并通过项目验证了该方法的可行性,极大地节约了生产成本,为DEM更新提供了思路。

四川地区精细化降水预报融合订正试验及检验

精细化定量降水网格预报是天气预报业务的重点和难点,基于西南区域智能数值网格模式预报系统(Southwest China WRF-based Intelligent Numeric Grid forecast System,SWC-WINGS)1 km×1 km分辨率的小时降水预报,利用时间滞后和概率匹配方法开展融合订正试验,再利用中国气象局多源融合降水系统(CMA Multi-source Precipitation Analysis System,CMPAS)三源融合降水实况格点数据,对2022年7—8月四川地区的小时降水预报融合订正结果进行检验,并在四川盆地西部一次短时强降水天气过程中进行应用,结果表明:(1)时间滞后集合降水预报相较于模式降水预报,存在小量级预报过度,大量级预报过于保守的问题;(2)时间滞后结合概率匹配的降水预报融合订正方法有效提升了各量级降水预报的TS评分,尤其1~2 h预报时效提升显著,小时雨量超过0.1 mm、5 mm、10 mm和20 mm量级的TS评分平均提升率分别为7.2%、17.2%、28.3%和36.3%;(3)一次短时强降水天气过程的应用结果表明,时间滞后结合概率匹配的融合订正方法对模式小时降水预报有较好的改进效果,尤其对大量级降水预报有较强的订正能力。

基于倾斜摄影的多回输电线路实景三维模型构建系统设计

为了使改进多回输电线路三维模型更加符合实际情况,该文将倾斜摄影技术引入多回输电线路实景三维模型构建系统中,提升数据获取的精准性。硬件方面,微处理器作为指令核心处理结构,负责读取并解析指令;设计多回输电线路数据采集模块和EP3SE110F1152C4数据存储器,并利用数据存储器对系统运行过程中的多项数据进行存储;软件方面,借助倾斜摄影技术,获取多回输电线路数据,并计算其对应的比例尺和航高,再对获取的数据进行优化,消除数据中的误差,并对其进行配准处理和特征匹配以及纹理映射和归一化处理,由此完成对多回输电线路实景三维模型的构建。经过实验验证,和以往的多回输电线路实景三维模型构建系统相比,设计的基于倾斜摄影的多回输电线路实景三维模型构建系统在实际应用中模型构建完整度为95.6%,构建效果更好。

车载激光点云道路标线分类提取方法

利用车载激光道路点云提取道路标线的难度较大。针对此问题,文章采用一种改进的基于点云特征图像的道路标线分类提取方法。首先将道路点云投影生成点云特征图像,通过结合图像梯度分析、图像二值化和连通域分析等操作,进一步进行道路标线像素提取;然后反投影到三维点云后,利用高斯混合模型对道路标线精细优化,从而提取出完整的道路标线点云;最后通过模板匹配分类,对道路标线点云进行分类提取。实验结果表明,该方法对不同道路环境下道路标线提取的准确度、完整度以及综合评价都超过90%。

面向农机产品服务供应链采购模式匹配评价

随着制造业数字化转型和农机产品服务供应链的应用,突显出农机制造企业产品零部件采购模式,在选择匹配过程中存在主观性与模糊性的问题,提出一种基于物元可拓优度结合可拓层次分析法和CRITIC综合赋权法的采购模式匹配评价方法。从农机制造企业产品自身特征和产品服务供应链影响因素为切入点,构建产品服务供应链视角下的农机制造装备采购模式匹配评价体系,并通过关联函数计算,得到采购模式综合优度排序和单项指标的关联度对比,输出最优采购匹配模式和模式识别度。结果表明,最优采购模式匹配度为0.118,所对应的模式可以作为产供销阶段的核心采购模式。实例计算表明,建立的评价模型与企业匹配度很高,该方法将定性预测和定量决策结合起来,可以为农机制造企业的产品采购模式提供系统科学的匹配工具。

基于多链存储优化的水产品交易匹配模型研究

区块链技术应用到水产品线上交易架构中可以使交易双方隐私信息得到基本保障,然而,目前区块链水产品线上交易模型和系统存在海量数据存储负载大、维护成本高、数据查询效率低等问题。为进一步缓解以上问题,在梳理和分析水产品交易流程基础上,根据水产品交易业务技术需求,提出了基于多链存储优化的水产品交易匹配模型。该模型在智能合约中通过贪心算法实现了效率较高的多属性水产品线上交易匹配过程,通过区块链多通道技术构建了水产品交易多链架构,实现了用户交易信息分布式存储,提高了交易信息查询效率,同时,采用区块链与本地数据库双模式存储技术,缓解了区块链网络中各个节点海量数据存储的负载。基于Hyperledger Fabric平台实现了基于多链存储优化的水产品交易原型系统。该原型系统测试结果表明,临界值900s平均最多可以完成1296笔交易,说明系统在处理千条交易数据量时可以正常运行,满足水产品线上交易平台日常实际交易业务需求,同时在链上存储1600条合同信息时查询1条用户合同信息平均时间为4.018s,多链存储结构提高了链上数据查询速度。

海上CCS/CCUS作业模式探讨与分析

CO_(2)地质封存与利用是应对温室气体排放、实现碳达峰碳中和目标的关键技术。从CCS/CCUS作业类型、CO_(2)来源等角度对全球海上CCS/CCUS项目进行分析,总结形成4类海上CCS/CCUS作业模式。通过对CO_(2)相态变化、杂质含量等因素对CO_(2)性能的影响研究,分析了海上CO_(2)源汇匹配、运输、注入的难点。结合国内海上CCS/CCUS业务现状与发展需求,从海上CO_(2)集群枢纽式源汇匹配模式探索、注入模式优化及配套设备研发、流动保障技术能力建设3个方向明确今后海上CCS/CCUS作业技术发展方向。

铝合金细化剂细化行为研究现状与展望

晶粒细化处理能够显著改善铝合金的综合性能,对拓展其应用领域意义重大。本文基于异质形核,探讨了点阵错配模型、边边匹配模型以及自由生长模型,肯定了边边匹配模型在筛选潜在晶粒细化剂方面的高效性;根据自由生长模型关于异质相尺寸、形态、分布等对晶粒细化效果影响的理论研究,归纳了物理、化学方法调控第二相进而优化细化效果的研究进展,并且对第二相尺寸影响细化效果的原因进行了理论阐述,最后对优化晶粒细化剂的方向做了展望。

气候变化适应性行为对茶农收入的影响——基于福建312份农户调查数据

为探究农户适应性行为及其对农业产出的影响效应,基于福建省6个县市19个乡镇312户茶农的微观调研数据,采取倾向得分匹配模型,实证分析气候变化适应性行为对茶农收入的影响.研究表明:①面对气候变化及其影响,58.65%的茶农会采取应对措施,41.35%的茶农未采取任何措施.②控制适应性行为内生性后,相较于未采取组茶农而言,采取组茶农茶叶收入水平平均提高了29.01%.基于收入依赖与经营规模的异质性分析,发现相较于全样本而言,收入完全依赖组和经营大规模组茶农具有更高的平均效应值(ATT)值,且不同组间适应性行为对茶农茶叶收入的作用效果从大到小依次为收入完全依赖、大规模、全样本.

基于三边匹配理论的应急救援分配决策

为解决大型地质灾害背景下应急救援初期救援人员、应急救援装备与受灾地点的分配问题,提高应急救援的效率和质量,首先,将应急救援三方主体之间的选择过程描述为三边匹配问题;然后,标准化处理匹配三方主体的多属性偏好评价信息,构造多属性综合偏好得分矩阵,并以系统稳定性和总偏好效用最大化为目标,建立应急救援初期背景下的三边匹配满意稳定模型;最后,通过算例验证模型的可行性和有效性。结果表明:该模型考虑各主体偏好对于资源分配的影响,能实现应急救援背景下救援人员、应急救援装备与受灾地点三方主体的合理匹配,有助于缩短应急救援部署时间,提高应急救援的效率和质量。

基于动态哈夫模型及双边匹配的电动汽车充电引导策略

由于充电站中充电桩数目有限且电动汽车充电耗时长,陆续产生充电需求的各电动汽车用户存在对充电站资源的竞争。这不仅增加了用户排队概率,降低了充电站收益和利用率,而且使得用户在充电站规模、价格、评价等方面的个性化需求得不到充分满足。为此,提出了一种动态哈夫模型与双边匹配方法相结合的电动汽车充电引导策略。首先,对充电站客流、充电订单和充电桩详情等真实数据集进行大数据挖掘,分析公共充电站用户的充电站选择偏好和充电行为特征;然后,基于动态哈夫模型,结合用户充电站选择偏好量化不同区域用户前往不同充电站的概率,并生成充电站推荐列表;最后,将前景理论与双边匹配策略相结合,进行充电引导。算例分析表明,所提策略大幅降低了用户的排队概率,在满足用户个性化充电需求的同时,保障了充电站利益。