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Enhanced Denoising Autoencoder-aided Bad Data Filtering for Synchrophasor-based State Estimation

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CSEE Journal of Power and Energy Systems 2022年第2期8卷 640-651页

作者： guanyu Tian Yingzhong Gu Zhe yu Qibing Zhang Di Shi Qun Zhou Zhiwei Wang GEIRI North America San JoseCA 95134 USA GEIRI North America San JoseCA 95134 USA on leave from Department of Electrical and Computer EngineeringUniversity of Central FloridaOrlandoFL 32816 USA Grid Dispatch Center State Grid Jiangsu Electric Power Company Ltd.Nanjing 210024China Department of Electrical and Computer Engineering University of Central FloridaOrlandoFL 32816 USA

Due to its high accuracy and ease of calculation,synchrophasor-based linear state estimation(LSE)has attracted a lot of attention in the last decade and has formed the cornerstone of many wide area monitor system(WAMS)applications.However,an increasing number of data quality concerns have been reported,among which bad data can significantly undermine the performance of LSE and many other WAMS applications it supports.Bad data filtering can be difficult in practice due to a variety of issues such as limited processing time,non-uniform and changing patterns,and etc.To pre-process phasor measurement unit(PMU)measurements for LSE,we propose an improved denoising autoencoder(DA)-aided bad data filtering strategy in this paper.Bad data is first identified by the classifier module of the proposed DA and then recovered by the autoencoder module.Two characteristics distinguish the proposed methodology:1)The approach is lightweight and can be implemented at individual PMU level to achieve maximum parallelism and high efficiency,making it suited for real-time processing;2)the system not only identifies bad data but also recovers it,especially for critical measurements.We use numerical experiments employing both simulated and real-world phasor data to validate and illustrate the effectiveness of the proposed method.

关键词： Autoencoder bad data processing linear state estimation PMU

LotusSQL:SQL Engine for High-Performance Big Data Systems

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Big Data Mining and Analytics 2021年第4期4卷 252-265页

作者： Xiaohan Li Bowen yu guanyu Feng Haojie Wang Wenguang Chen Department of Computer Science and Technology Tsinghua UniversityChina

In recent years,Apache Spark has become the de facto standard for big data processing.SparkSQL is a module offering support for relational analysis on Spark with Structured Query Language(SQL).SparkSQL provides convenient data processing interfaces.Despite its efficient optimizer,SparkSQL still suffers from the inefficiency of Spark resulting from Java virtual machine and the unnecessary data serialization and deserialization.Adopting native languages such as C++could help to avoid such bottlenecks.Benefiting from a bare-metal runtime environment and template usage,systems with C++interfaces usually achieve superior performance.However,the complexity of native languages also increases the required programming and debugging efforts.In this work,we present LotusSQL,an engine to provide SQL support for dataset abstraction on a native backend Lotus.We employ a convenient SQL processing framework to deal with frontend jobs.Advanced query optimization technologies are added to improve the quality of execution plans.Above the storage design and user interface of the compute engine,LotusSQL implements a set of structured dataset operations with high efficiency and integrates them with the frontend.Evaluation results show that LotusSQL achieves a speedup of up to 9 in certain queries and outperforms Spark SQL in a standard query benchmark by more than 2 on average.

关键词： big data C++ Structured Query Language(SQL) query optimization

Integrated proteomic and phosphoproteomic data-independent acquisition data evaluate the personalized drug responses of primary and metastatic tumors in colorectal cancer

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Biophysics Reports 2023年第2期9卷 67-81页

作者： Xumiao Li Yiming Huang Kuo Zheng Guanyu Yu Qinqin Wang Lei Gu Jingquan Li Hui Wang Wei Zhang Yidi Sun Chen Li Center for Single-Cell Omics School of Public Health Shanghai Jiao Tong University School of Medicine Institute of Neuroscience CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Colorectal Surgery Department Changhai Hospital Naval Medical University

Mass spectrometry(MS)-based proteomics and phosphoproteomics are powerful methods to study the biological mechanisms, diagnostic biomarkers, prognostic analysis, and drug therapy of tumors. Dataindependent acquisition(DIA) mode is considered to perform better than data-dependent acquisition(DDA) mode in terms of quantitative reproducibility, specificity, accuracy, and identification of low-abundance proteins. Mini patient derived xenograft(Mini PDX) model is an effective model to assess the response to antineoplastic drugs in vivo and is helpful for the precise treatment of cancer patients.Kinases are favorable spots for tumor-targeted drugs, and their functional completion relies on signaling pathways through phosphorylating downstream substrates. Kinase-phosphorylation networks or edge interactions are considered more credible and permanent for characterizing complex diseases.Here, we provide a workflow for personalized drug response assessment in primary and metastatic colorectal cancer(CRC) tumors using DIA proteomic data, DIA phosphoproteomic data, and Mini PDX models. Three kinase inhibitors, afatinib, gefitinib, and regorafenib, are tested pharmacologically. The process mainly includes the following steps: clinical tissue collection, sample preparation, hybrid spectral libraries establishment, MS data acquisition, kinase-substrate network construction, in vivo drug test, and elastic regression modeling. Our protocol gives a more direct data basis for individual drug responses, and will improve the selection of treatment strategies for patients without the druggable mutation.

关键词： Proteomics Phosphoproteomics Data-independent acquisition (DIA) Mini patient derived xenograft (MiniPDX) Kinase-substrate network Personalized drug responses

Neural-network-based Power System State Estimation with Extended Observability

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Journal of Modern Power Systems and Clean Energy 2021年第5期9卷 1043-1053页

作者： guanyu Tian Yingzhong Gu Di Shi Jing Fu Zhe yu Qun Zhou Department of Electrical and Computer Engineering University of Central FloridaOrlandoFL 32816USA GEIRI North America San JoseCA 95134USA State Grid Jiangsu Electric Power Company NanjingChina

This paper proposes a neural-network-based state estimation(NNSE)method that aims to achieve higher time efficiency,improved robustness against noise,and extended observability when compared with the conventional weighted least squares(WLS)state estimation method.NNSE consists of two parts,the linear state estimation neural network(LSE-net)and the unobservable state estimation neural network(USE-net).The LSE-net functions as an adaptive approximator of linear state estimation(LSE)equations to estimate the nominally observable states.The inputs of LSE-net are the vectors of synchrophasors while the outputs are the estimated states.The USE-net operates as the complementary estimator on the nominally unobservable states.The inputs are the estimated observable states from LSE-net while the outputs are the estimation of nominally unobservable states.USE-net is trained off-line to approximate the veiled relationship between observable states and unobservable states.Two test cases are conducted to validate the performance of the proposed approach.The first case,which is based on the IEEE 118-bus system,shows the comprehensive performance of convergence,accuracy,and robustness of the proposed approach.The second case study adopts real-world synchrophasor measurements,and is based on the Jiangsu power grid,which is one of the largest provincial power systems in China.

关键词： State estimation linear state estimation stochastic gradient descent neural network wide area management system(WAMS).

Impacts of El Nino on the somatic condition of Humboldt squid based on the beak morphology

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Journal of Oceanology and Limnology 2019年第4期37卷 1440-1448页

作者： HU guanyu yu Wei LI Bai HAN Dongyan CHEN Xinjun CHEN Yong LI Jianhua College of Marine Sciences Shanghai Ocean UniversityShanghai 201306China National Distant-water Fisheries Engineering Research Center Shanghai Ocean UniversityShanghai 201306China Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources Ministry of EducationShanghai Ocean UniversityShanghai 201306China School of Marine Sciences University of MaineOronoMaine 04469USA Collaborative Innovation Center for National Distant-water Fisheries Shanghai 201306China College of Fisheries Ocean University of ChinaQingdao 266003China

The Humboldt squid Dosidicus gigas has a short life span, and environmental variability plays a significant role in regulating its population dynamics and distribution. An analysis of 1 096 samples of D. gigas collected by the Chinese commercial fishing vessels during 2013, 2014, and 2016 off the Peruvian Exclusive Economic Zone, was conducted to evaluate the impacts of El Nino events on the somatic condition of D. gigas. This study indicates that the slopes of all beak variables in relation to mantle length (ML) for females were greater than those of males during 2013, 2014, and 2016, and slopes of the upper crest length and the lower rostrum length significantly differed between females and males in 2013 (P0.05). The Fulton's condition coefficients (K) of females and males in 2013 and 2014 were significantly greater than those in 2016 (P<0.01). The K values of females were greater than those of males in 2013, 2014, and 2016, and K values significantly differed between females and males in 2013. In normal years, the chlorophyll a (Chl a) concentration showed an N-shaped variability from January to December. However, in the El Nino period, it tended to weaken the upwelling coupled with warm and low Chl a concentration waters. We suggest that the poor somatic condition of D. gigas during the El Nino year was resulted from the low Chl a concentration in the waters, and the abundance of D. gigas would decrease due to the unfavourable environment and the lack of prey items in the El Nino year.

关键词： El Nino event Dosidicus gigas somatic condition abundance beak morphology

Clipping discrete multi-tone for peak-power-constraint IM/DD optical systems

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Science China(Information Sciences) 2023年第5期66卷 227-237页

作者： Ji ZHOU Liangchuan LI Jiale HE Xiaofeng LU yu BO guanyu WANG yuanda HUANG Gengchen LIU Yanzhao LU Shecheng GAO yuanhua FENG Shancheng ZHAO Weiping LIU Changyuan yu Zhaohui LI Department of Electronic Engineering College of Information Science and Technology Jinan University Optical Research Department Huawei Technologies Co. Ltd. Department of Electronic and Information Engineering The Hong Kong Polytechnic University Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen University Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)

High peak-to-average power ratio(PAPR) is a major drawback of discrete multi-tone(DMT) in peak-power-constraint(PPC) intensity-modulation/direct-detection(IM/DD) optical systems. Symmetric clipping operation is a frequently-used and practical method for mitigating the PAPR of the DMT signal.However, clipping noise is inevitably induced by the symmetric clipping operation, thereby deteriorating the system’s performance. In this paper, we study the statistical characteristics of the clipping noise in detail.Depending on the statistical characteristics, clipping-noise-cancellation(CNC) algorithms are proposed to mitigate the clipping noise in the clipping DMT systems. Theoretically, the clipping noise can be completely removed using the low-density-parity-check-assisted CNC algorithm(LDPC-assisted CNC algorithm). To verify the superiority of the clipping DMT with the CNC algorithm, we conduct an experiment with a50 Gb/s DMT system using 10G-class commercial devices for the scenario of PPC passive optical networks.The receiver sensitivity of the clipping DMT system with the CNC algorithm can reach-24 d Bm at a 20%soft-decision forward-error-correction limit, which is 2.5 d B higher than that of the DMT system without clipping operation. The clipping operation and the CNC algorithm are added after the original digital signal processing, thereby demonstrating the potential to efectively overcome the drawback in DMT signals and other high-PAPR signals.

关键词： discrete multi-tone peak-to-average power ratio peak-power constraint clipping-noise cancellation intensity-modulation/direct-detection optical systems

高精度智能化可见/近红外积分球辐射定标装置

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红外与激光工程 2014年第8期43卷 2520-2525页

作者：林冠宇于向阳中国科学院长春光学精密机械与物理研究所吉林长春130033 中国科学院大学北京100049

设计了由硅光电探测器作为反馈元件,采用DSP控制主光源开口处电动可调光阑大小,实现输出光谱辐亮度值连续可调的高精度程控化可见/近红外波段积分球辐射定标装置。经过理论设计和计算,在该装置内放置挡屏,保证了出射口处输出光谱辐亮度... 详细信息

设计了由硅光电探测器作为反馈元件,采用DSP控制主光源开口处电动可调光阑大小,实现输出光谱辐亮度值连续可调的高精度程控化可见/近红外波段积分球辐射定标装置。经过理论设计和计算,在该装置内放置挡屏,保证了出射口处输出光谱辐亮度值的均匀性。使用PR-655高精度扫描式亮度计测量出该装置的最大输出光谱辐亮度值为23061cd/m2;在直径150mm范围内的光谱辐亮度值的非均匀性为1.04%;输出光谱辐射亮度值的稳定性为0.8%。实验结果表明:该装置完全可以满足可见/近红外光学遥感仪器的地面辐射定标需要,并可实现智能程控化控制,提高了定标测试精度。

关键词：光谱辐射亮度积分球挡屏不确定度

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高效处理油田作业废水技术的研究及应用

石油与天然气化工 2020年第3期49卷 135-138页

作者：黄勇于冠宇中国石油大庆油田有限责任公司第一采油厂

油田作业废水来源分散,种类繁多,成分复杂,一般经收集后混合存放,单独处理,再回注地层。但由于这些混合废水污染物含量高,乳化程度高,絮凝沉降困难,注水处理常用的"絮凝-沉降-过滤"工艺效果较差,导致注水主要指标(悬浮物含量)严重超标,... 详细信息

油田作业废水来源分散,种类繁多,成分复杂,一般经收集后混合存放,单独处理,再回注地层。但由于这些混合废水污染物含量高,乳化程度高,絮凝沉降困难,注水处理常用的"絮凝-沉降-过滤"工艺效果较差,导致注水主要指标(悬浮物含量)严重超标,不仅无法回注,即使混入普通污水中进入常规注水处理站,也会对系统产生严重冲击。采用一种固相催化空气氧化技术对污水先进行曝气氧化处理,同时配合一种复合增强破胶混凝剂改善其絮凝特性,再用普通阳离子聚丙烯酰胺絮凝剂进行絮凝沉降处理,油和悬浮物去除率分别达94.1%和97.9%,净化水水质能够达到油田注水水质标准。该方法具有工艺简单、成本低廉的优点,适合于各油田推广应用。

关键词：作业废水催化氧化污水处理油田注水

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磁控胶囊机器人运行平稳的参数优化设计

机械科学与技术 2022年第6期41卷 862-868页

作者：胡冠昱梁亮刘煜长沙学院机电工程学院长沙410022

磁控胶囊机器人主要应用于人体肠道的诊断和治疗。根据永磁体法,设计制造了一套磁控胶囊机器人旋进时管内流体流场测量系统,采用CFD方法数值计算和PIV技术实验测量机器人周围流体涡量,数值计算和实验测量结果的变化趋势和大小基本相同... 详细信息

磁控胶囊机器人主要应用于人体肠道的诊断和治疗。根据永磁体法,设计制造了一套磁控胶囊机器人旋进时管内流体流场测量系统,采用CFD方法数值计算和PIV技术实验测量机器人周围流体涡量,数值计算和实验测量结果的变化趋势和大小基本相同。更进一步采用均匀设计数值模拟优化方法,数值计算管道直径、机器人平移速度、机器人转速和流体动力粘度对胶囊机器人运行平稳度(即以机器人周围流体湍流强度为指标)的影响规律,建立了胶囊机器人周围流体湍流强度一次回归模型。结果表明:胶囊机器人系统各类参数对机器人周围流体湍流强度的影响程度不同,其中,流体动力粘度>机器人平移速度≈机器人转速>管道直径的影响;胶囊机器人运行最为平稳时的各类参数组合为:管道直径为16 mm,机器人平移速度为0.02 m/s,机器人转速为90 r/min,粘液动力粘度为0.005 Pa·s。

关键词：胶囊机器人优化方法均匀设计运行平稳度湍流强度