Optimal Filtering for Grid Event Detection from Real-time Synchrophasor Data

Konakalla, Sai Akhil R.; Callafon, Raymond de

doi:10.1016/j.procs.2016.05.383

Cited by 10 publications

(4 citation statements)

References 12 publications

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“…Konakalla and Callafon presented a signal processing approach for online event detection based on synchrophasor data [90]. A discrete time filter of phasors was estimated to create optimal filtered rate of change signals based on phasor data where no disturbance exists by formulating least square optimization.…”

Section: B Rq2: What Are the Current Methods Used For Event Detection...mentioning

confidence: 99%

“…Moreover, the results depend highly on changes in the window size, since window size shapes the range of coefficient energy. Similarly, the requirement of a user-defined threshold also dictates the performance of many signal processing method [86], [90], [92]. The challenging task of setting a threshold for each PMU in the network due to the dependence of threshold on the quality and nature of PMU data limits the performance of these methods.…”

Section: B Rq2: What Are the Current Methods Used For Event Detection...mentioning

confidence: 99%

“…Event Detection Category Applied Technique [70], [80], [83], [85], [86], [136] Signal Processing Wavelet Transform [70], [72], [75], [79], [90]- [92], [138], [139] Filtering [81], [89], [140], [141] Fourier Transform [94], [100], [104]- [107], [116], [120], [142] Statistical Analysis PCA [95], [99], [103], [110], [113], [115], [121] Clustering and Correlation [123], [127], [131]- [133] Machine Learning/Deep Learning CNN [125], [128], [134] LSTM Among these requirements, frequency response and active power control are critically important. Figure 6 shows the deterioration of the U.S Eastern Interconnection (EI) frequency response to a 4.5 GW generator loss under different levels of PV penetration [148]*.…”

Section: Referencementioning

confidence: 99%

See 2 more Smart Citations

Frequency Event Detection and Mitigation in Power Systems: A Systematic Literature Review

Farooq

Bass

2022

IEEE Access

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Modern power systems characterized by complex topologies require accurate situational awareness to maintain an adequate level of reliability. Since they are large and spread over wide geographical areas, it is inevitable that failures will occur. Various generation and transmission disturbances, such as generator and transmission line tripping and load disconnection, give rise to a mismatch between generation and demand, which manifest as frequency events. These events can take the form of negligible frequency deviations or more severe emergencies that can precipitate cascading outages, depending on the severity of the disturbance and efficacy of remedial action schema. The impacts of such events have become more critical recently due to increased levels of renewable penetration and distributed energy resources, which have caused a decline in system synchronous inertia. Due to the repercussions, it is indispensable to arrest such disturbances on time by activating primary frequency control measures. In this paper, a comprehensive systematic literature review is presented on the techniques used for event detection in power systems and the methods of primary frequency response in modern power systems. The paper also highlights the impacts of severe frequency events within power systems.

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Section: B Rq2: What Are the Current Methods Used For Event Detection...mentioning

confidence: 99%

Section: B Rq2: What Are the Current Methods Used For Event Detection...mentioning

confidence: 99%

Section: Referencementioning

confidence: 99%

See 1 more Smart Citation

Frequency Event Detection and Mitigation in Power Systems: A Systematic Literature Review

Farooq

Bass

2022

IEEE Access

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“…Microgrid operations and controls can be significantly improved by utilizing Phasor Measurement Units (PMUs). PMUs provide synchronized real-time measurements (synchrophasors) of various quantities at multiple points across the microgrid [7], [8]. Control strategies can be implemented by feedback loops that use such PMU measurements.…”

Section: Introductionmentioning

confidence: 99%

Microgrid control using remote controller hardware-in-the-loop over the Internet

Valibeygi

Callafon

Stanovich

et al. 2018

2018 IEEE Power &Amp; Energy Society Innovative Smart Grid Technologies Conference (ISGT)

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A centralized microgrid power management and control system is developed and tested with a Hardware-Inthe-Loop (HIL) Real-Time Digital Simulator (RTDS) model of an existing microgrid that communicates in real-time with the controller over the Internet. The controller leverages Phasor Measurement Units (PMUs) for measuring power flow and adjusting inverter power references in real-time. The control objectives are power and State-of-Charge (SoC) control, subject to inverter power amplitude and rate limits and communication constraints. The controller incorporates units of power control, SoC control, and adaptive reference scheduling to achieve seamless microgrid operation. Real-time, over the internet, hardwarein-the-loop tests between the controller and the simulator are realized and indicate stability and performance of the microgrid control system.

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Data Mining and Machine Learning for Power System Monitoring, Understanding, and Impact Evaluation

Ren

Huang

et al. 2022

Intelligent Data Mining and Analysis in Power and Energy Systems

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Optimal Filtering for Grid Event Detection from Real-time Synchrophasor Data

Cited by 10 publications

References 12 publications

Frequency Event Detection and Mitigation in Power Systems: A Systematic Literature Review

Frequency Event Detection and Mitigation in Power Systems: A Systematic Literature Review

Microgrid control using remote controller hardware-in-the-loop over the Internet

Data Mining and Machine Learning for Power System Monitoring, Understanding, and Impact Evaluation

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