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| 1 | Bad Data Detection Algorithm for PMU Based on Spectral Clustering显示文摘Phasor measurement units(PMUs) can provide real-time measurement data to construct the ubiquitous electric of the Internet of Things. However, due to complex factors on site, PMU data can be easily compromised by interference or synchronization jitter. It will lead to various levels of PMU data quality issues, which can directly affect the PMU-based application and even threaten the safety of power systems. In order to improve the PMU data quality, a data-driven PMU bad data detection algorithm based on spectral clustering using single PMU data is proposed in this paper. The proposed algorithm does not require the system topology and parameters. Firstly, a data identification method based on a decision tree is proposed to distinguish event data and bad data by using the slope feature of each data. Then, a bad data detection method based on spectral clustering is developed. By analyzing the weighted relationships among all the data, this method can detect the bad data with a small deviation. Simulations and results of field recording data test illustrate that this data-driven method can achieve bad data identification and detection effectively. This technique can improve PMU data quality to guarantee its applications in the power systems. | Zhiwei Yang Hao Liu Tianshu Bi Qixun Yang | 2020 | Journal of Modern Power Systems and Clean Energy2020，8，3： | 10 |
| 2 | Subsynchronous oscillation monitoring and alarm method based on phasor measurements显示文摘Owing to the large-scale grid connection of new energy sources, several installed power electronic devices introduce sub-/supersynchronous inter-harmonics into power signals, resulting in the frequent occurrence of subsynchronous oscillations(SSOs). The SSOs may cause significant harm to generator sets and power systems;thus, online monitoring and accurate alarms for power systems are crucial for their safe and stable operation. Phasor measurement units(PMUs) can realize the dynamic real-time monitoring of power systems. Based on PMU phasor measurements, this study proposes a method for SSO online monitoring and alarm implementation for the main station of a PMU. First, fast Fourier transform frequency spectrum analysis is performed on PMU current phasor amplitude data to obtain subsynchronous frequency components. Second, the support vector machine learning algorithm is trained to obtain the amplitude threshold and subsequently filter out safe components and retain harmful ones. Finally, the adaptive duration threshold is determined according to frequency susceptibility, amplitude attenuation, and energy accumulation to decide whether to transmit an alarm signal. Experiments based on field data verify the effectiveness of the proposed method. | Yuan Qi Jiaxian Li Hao Liu Tianshu Bi | 2020 | Global Energy Interconnection2020，3，5： | 5 |
| 3 | Observation and optimization of 2 μm mode‐locked pulses in all‐fiber net anomalous dispersion laser cavity显示文摘We integrally demonstrate 2μm mode-locked pulses performances in all-fiber net anomalous dispersion cavity.Stable mode-locking operations with the center wavelength around 1950–1980 nm can be achieved by using the nonlinear polarization rotation structure and properly designing the dispersion management component.Conventional soliton is firstly obtained with a total anomalous dispersion cavity.Due to the contribution of commercial ultra-high numerical aperture fibers,net dispersion is reduced to-0.077 ps2.So that stretched pulse with 19.4 nm optical bandwidth is obtained and the de-chirped pulse-width can reach 312 fs using extra-cavity compression.Under pump power greater than 890 mW,stretched pulse can evolve into noise-like pulse with 41.3 nm bandwidth.The envelope and peak of such broadband pulse can be compressed with up to 2.2 ps and 145 fs,respectively.The single pulse energy of largely chirped stretched and noise-like pulse can reach 1.785 nJ and 1.53 nJ,respectively.Furthermore,extra-cavity compression can also contribute to a significant increase of peak power. | Wanzhuo Ma Desheng Zhao Runmin Liu Tianshu Wang Quan Yuan Hao Xiong Haiying Ji Huilin Jiang | 2020 | Opto-Electronic Advances2020，3，11： | 2 |
| 4 | Data network traffic analysis and optimization strategy of real-time power grid dynamic monitoring system for wide-frequency measurements显示文摘The application and development of a wide-area measurement system(WAMS)has enabled many applications and led to several requirements based on dynamic measurement data.Such data are transmitted as big data information flow.To ensure effective transmission of wide-frequency electrical information by the communication protocol of a WAMS,this study performs real-time traffic monitoring and analysis of the data network of a power information system,and establishes corresponding network optimization strategies to solve existing transmission problems.This study utilizes the traffic analysis results obtained using the current real-time dynamic monitoring system to design an optimization strategy,covering the optimization in three progressive levels:the underlying communication protocol,source data,and transmission process.Optimization of the system structure and scheduling optimization of data information are validated to be feasible and practical via tests. | Jinsong Li Hao Liu Wenzhuo Li Tianshu Bi Mingyang Zhao | 2022 | Global Energy Interconnection2022，5，2： | 2 |
| 5 | Toripalimab in advanced biliary tract cancer显示文摘Gemcitabine combined with platinum/fluorouracil drugs is the standard firstline treatment for advanced biliary tract cancers(BTCs).We explored the safety and efficacy of toripalimab plus gemcitabine and S-1(GS)as the first-line treatment for advanced BTCs.At a one-sided significance level of 0.025,a total of 50 patients could provide 80%power to show the efficacy at targeted progression-free survival(PFS)rate at 6 months of 70%versus 40%for the combined treatment.This single-arm,phase II study enrolled 50 patients with advanced BTCs who previously received no systemic treatment.The regimen was as follows:toripalimab(240 mg,i.v.,d1),gemcitabine(1,000 mg/m2,i.v.,d1 and d8),and S-1(40–60 mg bid p.o.,d1–14,Q21d).The primary endpoint was progression-free survival.The secondary endpoints included overall survival(OS),objective response rate(ORR),duration of response(DOR),and safety.The associations between response with PDL1 expression,tumor mutational burden(TMB),and genetic variations were explored.Patients were enrolled from January 2019 to August 2020,with a median follow-up time of 24.0 months(IQR:4.3–31.0 months). | Wei Li Yueqi Wang Yiyi Yu Qian Li Yan Wang Chenlu Zhang Xiaojing Xu Xi Guo Yu Dong Yuehong Cui Qing Hao Lujia Huang Houbao Liu Tianshu Liu | 2022 | The Innovation2022，3，4： | 1 |
| 6 | Synthesis of 15P-Conjugated PPy-modified Gold Nanoparticles and Their Application to Photothermal Therapy of Ovarian Cancer显示文摘 | WANG Li WANG Liping XU Tianshu GUO Changrun LIU Chuanzhi ZHANG Hao LI Jing LIANG Zhiqing | 2014 | Chemical Research in Chinese Universities2014，30，6： | 1 |
| 7 | GCN-LSTM spatiotemporal-network-based method for post-disturbance frequency prediction of power systems显示文摘Owing to the expansion of the grid interconnection scale,the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.These characteristics can provide effective support in coordinated security control.However,traditional model-based frequencyprediction methods cannot satisfactorily meet the requirements of online applications owing to the long calculation time and accurate power-system models.Therefore,this study presents a rolling frequency-prediction model based on a graph convolutional network(GCN)and a long short-term memory(LSTM)spatiotemporal network and named as STGCN-LSTM.In the proposed method,the measurement data from phasor measurement units after the occurrence of disturbances are used to construct the spatiotemporal input.An improved GCN embedded with topology information is used to extract the spatial features,while the LSTM network is used to extract the temporal features.The spatiotemporal-network-regression model is further trained,and asynchronous-frequency-sequence prediction is realized by utilizing the rolling update of measurement information.The proposed spatiotemporal-network-based prediction model can achieve accurate frequency prediction by considering the spatiotemporal distribution characteristics of the frequency response.The noise immunity and robustness of the proposed method are verified on the IEEE 39-bus and IEEE 118-bus systems. | Dengyi Huang Hao Liu Tianshu Bi Qixun Yang | 2022 | Global Energy Interconnection2022，5，1： | 1 |
| 8 | A PMU data recovering method based on preferred selection strategy显示文摘Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work. | Zhiwei Yang Hao Liu Tianshu Bi Qixun Yang Ancheng Xue | 2018 | Global Energy Interconnection2018，1，1： | 1 |
| 9 | Field PMU Test and Calibration Method–Part I:General Framework and Algorithms for PMU Calibrator显示文摘Laboratory testing of phasor measurement units(PMUs)guarantees their performance under laboratory conditions.However,many factors may cause PMU measurement problems in actual power systems,resulting in the malfunction of PMU-based applications.Therefore,field PMUs need to be tested and calibrated to ensure their performance and data quality.In this paper(Part I),a general framework for the field PMU test and calibration in different scenarios is proposed.This framework consists of a PMU calibrator and an analysis center,where the PMU calibrator provides the reference values for PMU error analysis.Two steps are implemented to ensure the calibrator accuracy for complex field signals:①by analyzing the frequency-domain probability distribution of random noise,a Fourier-transform-based signal denoising method is proposed to improve the anti-interference capability of the PMU calibrator;and②a general synchrophasor estimation method based on complex bandpass filters is presented for accurate synchrophasor estimations in multiple scenarios.Simulation and experimental test results demonstrate that the PMU calibrator has a higher accuracy than that of other calibrator algorithms and is suitable for field PMU test.The analysis center for evaluating the performance of field PMUs and the applications of the proposed field PMU test system are provided in detail in Part II of the next-step research. | Sudi Xu Hao Liu Tianshu Bi | 2022 | Journal of Modern Power Systems and Clean Energy2022，10，6： | 0 |
| 10 | Clustering residential electricity load curve via community detection in network显示文摘Performing analytics on the load curve(LC)of customers is the foundation for demand response which requires a better understanding of customers'consumption pattern(CP)by analyzing the load curve.However,the performances of previous widely-used LC clustering methods are poor in two folds:larger number of clusters,huge variances within a cluster(a CP is extracted from a cluster),bringing huge difficulty to understand the electricity consumption pattern of customers.In this paper,to improve the performance of LC clustering,a clustering framework incorporated with community detection is proposed.The framework includes three parts:network construction,community detection,and CP extraction.According to the cluster validity index(CVI),the integrated approach outperforms the previous state-of-the-art method with the same amount of clusters.And the approach needs fewer clusters to achieve the same performance measured by CVI. | 黄运有 Wang Nana Hao Tianshu Guo Xiaoxu Luo Chunjie Wang Lei Ren Rui Zhan Jianfeng | 2021 | High Technology Letters2021，27，1： | 0 |
| 11 | Dynamic State Estimation for DFIG with Unknown Inputs Based on Cubature Kalman Filter and Adaptive Interpolation显示文摘Dynamic state estimation(DSE)accurately tracks the dynamics of power systems and demonstrates the evolution of the system state in real time.This paper proposes a DSE approach for a doubly-fed induction generator(DFIG)with unknown inputs based on adaptive interpolation and cubature Kalman filter(AICKF-UI).DFIGs adopt different control strategies in normal and fault conditions;thus,the existing DSE approaches based on the conventional control model of DFIG are not applicable in all cases.Consequently,the DSE model of DFIGs is reformulated to consider the converter controller outputs as unknown inputs,which are estimated together with the DFIG dynamic states by an exponential smoothing model and augmented-state cubature Kalman filter.Furthermore,as the reporting rate of existing synchro-phasor data is not sufficiently high to capture the fast dynamics of DFIGs,a large estimation error may occur or the DSE approach may diverge.To this end,in this paper,a local-truncation-error-guided adaptive interpolation approach is developed.Extensive simulations conducted on a wind farm and the modified IEEE 39-bus test system show that the proposed AICKF-UI can(1)effectively address the divergence issues of existing cubature Kalman filters while being computationally more efficient;(2)accurately track the dynamic states and unknown inputs of the DFIG;and(3)deal with various types of system operating conditions such as time-varying wind and different system faults. | Maolin Zhu Hao Liu Junbo Zhao Bendong Tan Tianshu Bi Samson Shenglong Yu | 2023 | Journal of Modern Power Systems and Clean Energy2023，11，4： | 0 |
| 12 | Field PMU Test and Calibration Method——PartⅡ:Test Signal Identification Methods and Field Test Applications显示文摘Synchrophasor measurement units(PMUs)provide synchronized measurement data for wide-area applications.To improve the effectiveness of synchrophasor-based applications,field PMUs must be tested to ensure their performance and data quality.In the companion paper(Part I),we proposed a field PMU test and calibration framework consisting of a PMU calibrator and analysis center.Part I presents the development and test of the PMU calibrator.This paper focuses on the analysis center and field test applications.First,the critical component of the analysis center is the signal identification module,for which the step and oscillation signal identification methods are proposed.Here,the performance evaluation criteria of PMU in these two cases are different from others.The methods include a step signal detection method based on singular value decomposition(SVD),which has the capability of weak step detection to account for energy leakage of the signal during the step process,and an oscillation signal identification method based on SVD and fast Fourier transform,which can accurately extract oscillation components that benefit from the adaptive threshold setting method.Second,the analysis center software is implemented based on identification results.By integrating the PMU calibrator in Part I with the analysis center in Part II,we can examine in depth the field PMU test applications in three test scenarios,including standard,playback,and field signal test.Results demonstrate the effectiveness and applicability of the proposed field PMU test methods from both Parts I and II. | Sudi Xu Hao Liu Tianshu Bi | 2023 | Journal of Modern Power Systems and Clean Energy2023，11，1： | 0 |
| 13 | High-accuracy and Low-complexity Phasor Estimation Method for PMU Calibration显示文摘Due to the increasing development of renewables in power systems,the requirements for phasor measurement units(PMUs)becomes higher.A PMU calibrator is an important tool to test and calibrate PMUs to ensure their measurement performance.This device can provide accurate reference values for error analysis of PMUs.In this paper,a phasor algorithm with low computational complexity and high accuracy is proposed for the PMU calibrator.This method reduces the processor requirements and development costs of the calibrator,thereby facilitating its popularization.At first,an enhanced discrete Fourier transform(DFT)method is put forward:1)the frequency response of the windowed DFT method is analyzed to reveal its large measurement errors under dynamic conditions;2)the parameter requirements of the DFT window that is regarded as a lowpass filter are analyzed,and thus a lowpass filter with better filtering performance is designed as the window coefficients to improve the estimation accuracy.Then,based on the enhanced DFT algorithm,a calibrator algorithm framework consisting of two-stage filters and a signal recognition module is established.This algorithm can consider the anti-interference ability and dynamic measurement accuracy at a low reporting rate.Simulation and experimental test results show that the proposed calibrator algorithm provides high-accuracy measurements of the static and dynamic signals with low computational complexity. | Jinsong Li Sudi Xu Hao Liu Tianshu Bi | 2021 | CSEE Journal of Power and Energy Systems2021，7，6： | 0 |
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