Wide-Area Frequency Monitoring Network (FNET) Architecture and Applications

Zhang, Yingchen; Markham, Penn; Xia, Tao; Chen, Lang; Ye, Yanzhu; Wu, Zhongyu; Yuan, Zhimin; Wang, Lei; Bank, Jason; Burgett, Joseph M.; Conners, Richard W.; Li, Fangxing

doi:10.1109/tsg.2010.2050345

Cited by 288 publications

(110 citation statements)

References 20 publications

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“…FNET/GridEye, an internet-based WAMS, has been continuously monitoring the power grid for over ten years [16]. It can measure power grid frequency, voltage magnitude and voltage angle with low-cost, reliable performance and high accuracy (±0.0005 Hz for grid frequency and ±0.0002 rad for voltage angle) [17].…”

Section: Wide-area Frequency Monitoring Network Fnet/grideyementioning

confidence: 99%

Impacts of Power Grid Frequency Deviation on Time Error of Synchronous Electric Clock and Worldwide Power System Practices on Time Error Correction

et al. 2017

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Synchronous electric clocks utilize power grid frequency as their timing reference. Power grid frequency deviation away from its nominal value results in synchronous electric clocks running fast or running slow (also known as the time error). In this article, statistical analysis on time error of synchronous electric clocks around the world is firstly presented using the power grid frequency measurements recorded by the wide-area frequency monitoring network FNET/GridEye. Then, the time error correction (TEC) process provided by electric utilities is analyzed and the worldwide TEC practice is investigated. Eventually, regions of the world where electric utilities provide TEC service are differentiated from those without TEC services. Analytical results demonstrate that the average time error of synchronous electric clocks in North America seems to be less than five seconds, and it has not changed very much over the past few years. On the other hand, the identification results present that up to the end of 2016, many electric utilities around the world, especially in North America and Europe, provided the TEC service to periodically remove the accumulative time error of synchronous electric clocks.

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Section: Wide-area Frequency Monitoring Network Fnet/grideyementioning

confidence: 99%

Impacts of Power Grid Frequency Deviation on Time Error of Synchronous Electric Clock and Worldwide Power System Practices on Time Error Correction

et al. 2017

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“…In this section, the IEEE 39 bus system [7] is selected to illustrate the using of the method proposed in this paper. The scheme of IEEE New England39-bus system is illustrated in Figure 2.…”

Section: Case Studymentioning

confidence: 99%

Wavelet-Based Power Network Disturbance Identifying Part I: Theory and Method

Chen¹,

Tang²,

Liu

et al. 2016

Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering

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Abstract. It is important that control center operators be alerted to system disturbances, including where, when and what disturbance occurs, so that proper anticipatory actions can be promptly taken if necessary, avoiding oscillation spreads in the power network. In this paper, the wavelet multi-resolution analysis based method is proposed to identify power system disturbances. Energy of wavelet coefficients are used as a criterion to choose optimal wavelet function and decomposition scale, which are then used for obtaining the maximum wavelet coefficients by identifying the frequency signals from wide area measurement system (WAMS). The maximum wavelet coefficients are then selected to be the indicators for disturbance identifying. The detailed procedure and effectiveness of the proposed method is demonstrated by simulations of a 10-machine 39-bus system.

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“…A total of 49 FNET (Frequency monitoring NETwork [25]) devices distributed across the Eastern Interconnect recorded data at 0.1 second resolution. We were given the rough time of major generator trips.…”

Section: Power Grid Situation Awarenessmentioning

confidence: 99%

Interactive selection of multivariate features in large spatiotemporal data

Wang

Sisneros

Huang

2013

2013 IEEE Pacific Visualization Symposium (PacificVis)

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Selecting meaningful features is central in the analysis of scientific data. Today's multivariate scientific datasets are often large and complex making it difficult to define general features of interest significant to scientific applications. To address this problem, we propose three general, spatiotemporal metrics to quantify the significant properties of data features-concentration, continuity and co-occurrence, named collectively as CO 3 . We implemented an interactive visualization system to investigate complex multivariate time-varying data from satellite remote sensing with great spatial resolutions, as well as from real-time continental-scale power grid monitoring with great temporal resolutions. The system integrates CO 3 metrics with an elegant multi-space user interaction tool to provide various forms of quantitative user feedback. Through these, the system supports an iterative user-driven analysis process. Our findings demonstrate that the CO 3 metrics are useful for simplifying the problem space and revealing potential unknown possibilities of scientific discoveries by assisting users to effectively select significant features and groups of features for visualization and analysis. Users can then comprehend the problem better and design future studies using newly discovered scientific hypotheses.

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Wide-Area Frequency Monitoring Network (FNET) Architecture and Applications

Cited by 288 publications

References 20 publications

Impacts of Power Grid Frequency Deviation on Time Error of Synchronous Electric Clock and Worldwide Power System Practices on Time Error Correction

Impacts of Power Grid Frequency Deviation on Time Error of Synchronous Electric Clock and Worldwide Power System Practices on Time Error Correction

Wavelet-Based Power Network Disturbance Identifying Part I: Theory and Method

Interactive selection of multivariate features in large spatiotemporal data

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