Wanted: A more intelligent grid

Giri, J.; Sun, Danfeng; Avila-Rosales, R.

doi:10.1109/mpe.2008.931391

Cited by 48 publications

(9 citation statements)

References 2 publications

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“…Depending upon the nature of these events, actions can be preventive, corrective or restorative [15]. Therefore it Energies 2016, 9, 315 3 of 15 is very important that the PMU applications that are used to identify these type of dynamic process are provided with "clean" data so that no false actions can be taken based on an application's results.…”

Section: Tap Changer Operation (Voltage Stability)~minutesmentioning

confidence: 99%

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Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

2016

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Data from phasor measurement units (PMUs) may be exploited to provide steady state information to the applications which require it. As PMU measurements may contain errors and missing data, the paper presents the application of a Kalman Filter technique for real-time data processing. PMU data captures the power system's response at different time-scales, which are generated by different types of power system events; the presented Kalman Filter methods have been applied to extract the steady state components of PMU measurements that can be fed to steady state applications. Two KF-based methods have been proposed, i.e., a windowing-based KF method and "the modified KF". Both methods are capable of reducing noise, compensating for missing data and filtering outliers from input PMU signals. A comparison of proposed methods has been carried out using the PMU data generated from a hardware-in-the-loop (HIL) experimental setup. In addition, a performance analysis of the proposed methods is performed using an evaluation metric.

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Section: Tap Changer Operation (Voltage Stability)~minutesmentioning

confidence: 99%

“…If I nov-norm ě t Q , it indicates that there exists either process noise or bad data in the measurements that has caused I nov-norm to exceed τ Q . Assume that the problem is originating from the process noise, so reduce I nov-norm back to τQ through inflating Q by ∆Q, as shown in Equations (13)- (15).…”

Section: Algorithmmentioning

confidence: 99%

Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

2016

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“… Distributed operation : because a large amount of data will be generated and processed in the smart grid, a traditional centralized communication architecture can create a bottleneck in the system. For instance, a PMU (i.e., a smart sensor that measures the electrical waves on an electricity grid) can generate up to 50/60 phasor measurements per second that can easily generate large amount of data within few minutes . Transmitting all these phasor data in a centralized network can create a congestion easily, and a congestion control mechanism would be required .…”

Section: Requirements For Data Sensing and Communication In Smart Gridmentioning

confidence: 99%

Smart grid sensor data collection, communication, and networking: a tutorial

Kayastha

Niyato

Hossain

et al. 2012

Wireless Communications

120

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The smart grid is an innovative energy network that will improve the conventional electrical grid network to be more reliable, cooperative, responsive, and economical. Within the context of the new capabilities, advanced data sensing, communication, and networking technology will play a significant role in shaping the future of the smart grid. The smart grid will require a flexible and efficient framework to ensure the collection of timely and accurate information from various locations in power grid to provide continuous and reliable operation. This article presents a tutorial on the sensor data collection, communications, and networking issues for the smart grid. First, the applications of data sensing in the smart grid are reviewed. Then, the requirements for data sensing and collection, the corresponding sensors and actuators, and the communication and networking architecture are discussed. The communication technologies and the data communication network architecture and protocols for the smart grid are described. Next, different emerging techniques for data sensing, communications, and sensor data networking are reviewed. The issues related to security of data sensing and communications in the smart grid are then discussed. To this end, the standardization activities and use cases related to data sensing and communications in the smart grid are summarized. Finally, several open issues and challenges are outlined. Copyright © 2012 John Wiley & Sons, Ltd.

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“…With typical sampling rates from 10 to 50 or 60 samples per second, PMUs have the ability to identify and track the phasor values of voltage and current synchronously on a power system. [5] PMU data are transmitted to a central data concentrator, where they are compared, analyzed, processed, and archived. These measurements are crucial to the fast detection and monitoring of system security indices and to triggering a dynamic security assessment process.…”

Section: Pmu/wams Assessmentmentioning

confidence: 99%

Comprehensive situation awareness in a very large power grid control center

et al. 2012

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This paper presents a comprehensive security monitoring and warning system implemented at North China Grid, which has significantly improved the operator's situation awareness to operate a very large power grid by applying innovative visualization technology to power system analytical applications. It is concluded that visualization is not just about building better graphical displays; instead, visualization is becoming a driving force for emerging power system applications and future system integration.

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Wanted: A more intelligent grid

Cited by 48 publications

References 2 publications

Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

Extracting Steady State Components from Synchrophasor Data Using Kalman Filters

Smart grid sensor data collection, communication, and networking: a tutorial

Comprehensive situation awareness in a very large power grid control center

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