Power System Real-Time Event Detection and Associated Data Archival Reduction Based on Synchrophasors

Ge, Yinyin; Flueck, Alexander J.; Kim, Dae-Kyeong; Ahn, Jong-Bo; Lee, Jae-Duck; Kwon, Dae-Yun

doi:10.1109/tsg.2014.2383693

Cited by 81 publications

(25 citation statements)

References 19 publications

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“…where CV k is the percentage cumulative variance (CV) of the k-th PC, λ m is an eigenvalue of the m-th PC, and γ is CV bound, respectively [8,9]. The number of PCs k needed to satisfy Equation (5) are decided from the distribution in each detail matrix.…”

Section: Data Compression Via Mspcamentioning

confidence: 99%

“…Two kinds of power-system conditions, ambient and event state, are considered when compressing PMU data by using PCA [8]. An application of PCA to detect a power-system event and to reduce dimensionality is proposed in Reference [9]. An SVD based approach for missing-data recovery process and data compression is proposed in Reference [10].…”

Section: Introductionmentioning

confidence: 99%

“…The aggregated PMU dataset from a wide-area power system was monitored to detect an event and bad data. The importance of selecting compression interval considering event detection was discussed in References [9,11,22] because abnormal variation caused by an event can yield significant distortion in dimensionality reduction. In this paper, event detection is implemented using modified wavelet energy (MWE), proposed in Reference [15].…”

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confidence: 99%

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Multiscale PMU Data Compression via Density-Based WAMS Clustering Analysis

Lee

Kim

et al. 2019

Energies

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This paper presents a multiscale phasor measurement unit (PMU) data-compression method based on clustering analysis of wide-area power systems. PMU data collected from wide-area power systems involve local characteristics that are significant risk factors when applying dimensionality-reduction-based data compression. Therefore, density-based spatial clustering of applications with noise (DBSCAN) is proposed for the preconditioning of PMU data, except for bad data and the automatic segmentation of correlated local datasets. Clustered PMU datasets of a local area are then compressed using multiscale principal component analysis (MSPCA). When applying MSPCA, each PMU signal is decomposed into frequency sub-bands using wavelet decomposition, approximation matrix, and detail matrices. The detail matrices in high-frequency sub-bands are compressed by using a PCA-based linear-dimensionality reduction process. The effectiveness of DBSCAN for data compression is verified by application of the proposed technique to the real-world PMU voltage and frequency data. In addition, comparisons are made with existing compression techniques in wide-area power systems.

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Section: Data Compression Via Mspcamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Multiscale PMU Data Compression via Density-Based WAMS Clustering Analysis

Lee

Kim

et al. 2019

Energies

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“…where Γ x denotes the absolute normalized deviation in the parameter x which can be tolerated by the microgrid. A centralized detection method based on (17) and (18) performs very well compared to local detection of voltage or frequency disturbances.…”

Section: B the Central Disturbance Detectormentioning

confidence: 99%

Centralized Disturbance Detection in Smart Microgrids With Noisy and Intermittent Synchrophasor Data

Seyedi

Karimi

Guerrero

2017

IEEE Trans. Smart Grid

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Microgrids are prone to network-wide disturbances such as voltage and frequency deviations. Detection of disturbances by a microgrid central controller (MGCC) is therefore necessary for improving the network operation. Motivated by this application, this paper presents a new structure for the centralized detection of disturbances with noisy synchrophasor data and packet delay/dropouts. We build the proposed structure starting from the analysis of noise-delay tradeoff in synchrophasor networks, and developing a new phasor data concentrator (PDC) for compensation of data losses. The statistical performance metrics of the disturbance detector are numerically evaluated in the case of islanding detection, corroborating that the centralized detector counteracts the measurement noise and lowers the detection time.Numerical results show that the proposed structure significantly mitigates the probability of false detection. Moreover, it can achieve the lower bound of average detection time in a wide range of packet drop rates. This study is useful to network designers who need to employ data acquisition systems for reliable and robust microgrid control applications.

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“…Typical PMU devices are able to provide 30 samples per second [7]. This enables the grid operator to be informed from the synchronized time based voltage and current phasor measurements in different nodes of the grid, in order to control and manage the power stability and delivery [8].…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Real-Time Microgrid Simulation Platform Based on Centralized and Distributed Management

et al. 2017

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Demand response and distributed generation are key components of power systems. Several challenges are raised at both technical and business model levels for integration of those resources in smart grids and microgrids. The implementation of a distribution network as a test bed can be difficult and not cost-effective; using computational modeling is not sufficient for producing realistic results. Real-time simulation allows us to validate the business model's impact at the technical level. This paper comprises a platform supporting the real-time simulation of a microgrid connected to a larger distribution network. The implemented platform allows us to use both centralized and distributed energy resource management. Using an optimization model for the energy resource operation, a virtual power player manages all the available resources. Then, the simulation platform allows us to technically validate the actual implementation of the requested demand reduction in the scope of demand response programs. The case study has 33 buses, 220 consumers, and 68 distributed generators. It demonstrates the impact of demand response events, also performing resource management in the presence of an energy shortage.

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Power System Real-Time Event Detection and Associated Data Archival Reduction Based on Synchrophasors

Cited by 81 publications

References 19 publications

Multiscale PMU Data Compression via Density-Based WAMS Clustering Analysis

Multiscale PMU Data Compression via Density-Based WAMS Clustering Analysis

Centralized Disturbance Detection in Smart Microgrids With Noisy and Intermittent Synchrophasor Data

Implementation of a Real-Time Microgrid Simulation Platform Based on Centralized and Distributed Management

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