Hybrid State Estimation using Distributed Compressive Sensing

被引:0
|
作者
Hamidi, Reza J.
Khodabandelou, H.
Livani, H.
Sami-Fadali, M.
机构
基金
美国国家科学基金会;
关键词
Compressive sensing; hybrid state estimation; PMU; SCADA; and WLS; INCLUDING PHASOR MEASUREMENTS;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this paper, a hybrid state estimation (HSE) method is proposed for the integration of Phasor Measurement Unit (PMU) data into conventional weighted least square state estimators. PMU measurements are not easily compatible with conventional state estimators because PMUs provide different measurement types at a much faster rate than SCADA measurements. However, the vast majority of state estimators are SCADA-based and they cannot utilize PMU data. In the proposed method, PMU data are converted into the SCADA form based on their statistical properties, and the difference between the refreshing rates is compensated using the distributed Compressive Sensing (CS) which exploits the spatial-temporal correlation of PMU data. Simulations are carried out on the IEEE 14- and 57-bus systems to evaluate the proposed hybrid SE. The simulation results are used to discuss the pros and cons of the proposed method.
引用
收藏
页数:5
相关论文
共 50 条
  • [21] An Improved Quantum State Estimation algorithm via Compressive Sensing
    Cong, S.
    Zhang, H.
    Li, K.
    2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS IEEE-ROBIO 2014, 2014, : 2338 - 2343
  • [22] DISTRIBUTED COMPRESSIVE VIDEO SENSING
    Kang, Li-Wei
    Lu, Chun-Shien
    2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, 2009, : 1169 - 1172
  • [23] A review of the state-of-the-art distributed compressive video sensing architectures
    Imran, Noreen
    Seet, Boon-Chong
    Fong, A. C. M.
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2014, 50 (1-2) : 3 - 17
  • [24] Distributed Compressive Video Sensing: A Review of the State-of-the-Art Architectures
    Imran, Noreen
    Seet, Boon-Chong
    Fong, A. C. M.
    2012 19TH INTERNATIONAL CONFERENCE MECHATRONICS AND MACHINE VISION IN PRACTICE (M2VIP), 2012, : 68 - 73
  • [25] MOBILE DISTRIBUTED COMPRESSIVE SENSING FOR SPECTRUM SENSING
    Havary-Nassab, Veria
    Valaee, Shahrokh
    Shahbazpanahi, Shahram
    2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2014,
  • [26] Distributed State Estimation for Stochastic Linear Hybrid Systems
    Du, Bin
    Yuan, Lian
    Sun, Dengfeng
    Hwang, Inseok
    2020 59TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2020, : 5761 - 5766
  • [27] Target Parameter Estimation of Compressive Sensing Radar Using Sensing Matrix Optimization
    Li, Hong-Tao
    Yuan, Ze-Shi
    Wang, Ke
    Wang, Chao-Yu
    2015 INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND AUTOMATION (ICMEA 2015), 2015, : 144 - 149
  • [28] Optimal Quantization for Distributed Compressive Sensing
    Yamac, Mehmet
    Altay, Can
    Sankur, Bulent
    2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2017,
  • [29] Dictionary Design for Distributed Compressive Sensing
    Chen, Wei
    Wassell, Ian J.
    Rodrigues, Miguel R. D.
    IEEE SIGNAL PROCESSING LETTERS, 2015, 22 (01) : 95 - 99
  • [30] Distributed compressive sensing of light field
    Lei, Rui
    Shen, Wei
    Zhang, Zhi-jiang
    Zhou, Ying
    NINTH INTERNATIONAL SYMPOSIUM ON PRECISION ENGINEERING MEASUREMENTS AND INSTRUMENTATION, 2015, 9446