Efficient Compression of PMU Data in WAMS

Gadde, Phani; Biswal, Milan; Brahma, Sukumar; Cao, Huiping

doi:10.1109/tsg.2016.2536718

Cited by 89 publications

(46 citation statements)

References 9 publications

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“…These advanced measurement devices provide centralised and distributed controllers with superior measurements in terms of resolution and accuracy. There are also wide area measurement systems which are capable of very rapid analysis of anomalies over very large geographical areas (Gadde, Biswal, Brahma, & Cao, 2016).…”

Section: Telecommunication Infrastructurementioning

confidence: 99%

Electricity networks

Poudineh

Peng

Mirnezami

2017

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While the economics of low carbon generation technologies is fast improving due to a mix of policy and market driven incentives, innovation in electricity networks has been relatively sluggish. This slow adaptation of electricity networks is challenging as they are key to the energy transition. Further electrification of the economy requires significant investment and innovation in the grid segment of the electricity supply chain. Traditional regulatory models of natural monopoly network utilities are designed to incentivise cost efficiency, with the assumption that network business is costly and the task of regulation is to encourage cost reduction subject to firm achieving a certain level of reliability. A feature of innovation activities is that they are riskier in comparison with the business-as-usual activities of network firms. This paper reviews the evolution of electricity grids from the technological and organisational perspectives and analyses the efficacy of existing incentive models in encouraging innovation. We show that incentive mechanisms that do not take uncertainty into account in the outcome of innovation efforts divert the attention of network utilities from innovation to normal efficiency gains. We also demonstrate that the issue of risk can distort the outcome of a competitive scheme for innovation funds when bidders are heterogeneous in their risk tolerance. Finally, based on the results of our analysis about the role of risk in innovation activities and a review of innovation incentive mechanisms in the UK and Italy, we provide recommendations for addressing the problem of innovation under regulation.

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Section: Telecommunication Infrastructurementioning

confidence: 99%

Electricity networks

Poudineh

Peng

Mirnezami

2017

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“…When it comes to normal data compression, the compression operation is carried in the sending terminals or equipment to decrease the data redundancy so that the volume of data can be reduced for convenient data transmission in the communication systems; In the receiving terminals, the received and compressed data is decompressed on retaining original fidelity and looking for higher compression ratio ( CR ) as denoted in (1).…”

Section: Challenges Of Pmu Data Compressionmentioning

confidence: 99%

“…For instance, more than 584 PMUs have been installed in Western Electricity Coordination Council(WECC) until April, 2015 [1] . In China, the amount of PMU is reported to reach 2000 by 2014, specifically speaking, a regional power company with 100 PMUs will generate more than 50GB data each day with sampling rate at 30Hz, and over 120GB with higher rate of 100Hz which is widely applied in China power grid [2] .…”

Section: Introductionmentioning

confidence: 99%

Three-Stage Lossless Compression Technique For Processing PMU Big Data In Modern Smart Grid

Li¹,

Chen²,

Lu³

et al. 2017

Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC

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With the widespread proliferation and application of high data sampling rate device-Phasor Measurement Units (PMUs) in modern smart grid, large volumes of data are produced in the wide-area monitoring system, which results in increasing challenge in real-time analysis, data storage and data transmission. This paper proposes an improved lossless compression technique which is fully based on the analysis of PMU data structure and consists by three stages algorithm for handling massive data. In the first stage, adjacent coordinate data of one period are operated subtraction and the waveform difference method is adopted to simplify data of other periods. Then, adaptive dynamic Huffman algorithm is selected to compress the processed data. Finally, Run Length Encoding method is employed to decrease furthermore the redundancy. The performance of the improved approach was evaluated under simulation using field PMU data. Experimental results under both dynamic and steady states presented at the end of the paper prove the efficiency of the proposed technique.

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“…The algorithms can achieve both high compression ratios and high accuracy, but they require data buffering and are thus not suitable for real-time applications. Rather than processing the signal itself, principal component analysis (PCA) can be used for data compression by reducing the redundancy between multidimensional data such as the measurement data of multiple PMUs [12] and multiple data channels [13]. The compression performance and reconstruction accuracy depend on the number of principal components selected.…”

Section: Introductionmentioning

confidence: 99%

“…The compression performance and reconstruction accuracy depend on the number of principal components selected. The compression ratio of PCA is not very high when high accuracy is achieved [12]. The PCA algorithm can be combined with other algorithms to achieve higher compression ratios.…”

Section: Introductionmentioning

confidence: 99%

Wavelet-based data compression for wide-area measurement data of oscillations

Cheng

Zhang

et al. 2018

J. Mod. Power Syst. Clean Energy

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This paper proposes a wavelet-based data compression method to compress the recorded data of oscillations in power systems for wide-area measurement systems. Actual recorded oscillations and simulated oscillations are compressed and reconstructed by the waveletbased data compression method to select the best wavelet functions and decomposition scales according to the criterion of the minimum compression distortion composite index, for a balanced consideration of compression performance and reconstruction accuracy. Based on the selections, the relationship between the oscillation frequency and the corresponding optimal wavelet and scale is discussed, and a piecewise linear model of the base-2 logarithm of the frequency and the order of the wavelet is developed, in which different pieces represent different scales. As a result, the wavelet function and decomposition scale can be selected according to the oscillation frequency. Compared with the wavelet-based data compression method with a fixed wavelet scale for disturbance signals and the real-time data compression method based on exception compression and swing door trending for oscillations, the proposed method can provide high compression ratios and low distortion rates.

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Efficient Compression of PMU Data in WAMS

Cited by 89 publications

References 9 publications

Electricity networks

Electricity networks

Three-Stage Lossless Compression Technique For Processing PMU Big Data In Modern Smart Grid

Wavelet-based data compression for wide-area measurement data of oscillations

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