Instructions Data Compression for Smart Grid Monitoring using Wavelet Domain Singular Value Decomposition

Li, Qin; Zhang, Ming; He, Shaoming; Li, Shaowu

doi:10.1109/ccdc.2018.8408029

Cited by 7 publications

(6 citation statements)

References 25 publications

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“…The most popular wavelet functions are the Haar, Daubechies, and Coiflet families (Figure 5). This balances compression performance and reconstruction accuracy [55]. The wavelet function and decomposition scale can be selected directly according to the oscillation frequency, which is the most significant characteristic of oscillations.…”

Section: Wavelet Transformmentioning

confidence: 99%

Compression Techniques for Real-Time Control and Non-Time-Critical Big Data in Smart Grids: A Review

Prokop,

Bień,

Barczentewicz

2023

Energies

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Significant amounts of data need to be transferred in order to optimize the operation of power grids. The development of advanced metering and control infrastructure ensures a growth in the amount of data transferred within smart grids. Data compression is a strategy to reduce the burden. This paper presents current challenges in the field of time-series data compression. This paper’s novel contribution is the division of data in smart grids to real-time data used for control purposes and big data sets used for non-time-critical analysis of the system. Both of these two applications have different requirements for effective compression. Currently used algorithms are listed and described with their advantages and drawbacks for both of these applications. Details needed for the implementation of an algorithm were also provided. Comprehensive analysis and comparison are intended to facilitate the design of a data compression method tailored for a particular application. An important contribution is the description of the influence of data compression methods on cybersecurity, which is one of the major concerns in modern power grids. Future work includes the development of adaptive compression methods based on artificial intelligence, especially machine learning and quantum computing. This review will offer a solid foundation for the research and design of data compression methods.

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Section: Wavelet Transformmentioning

confidence: 99%

Compression Techniques for Real-Time Control and Non-Time-Critical Big Data in Smart Grids: A Review

Prokop,

Bień,

Barczentewicz

2023

Energies

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“…Gaussian approximation based on dynamic-nonlinear learning technique [20]. Smart meter readings compression Compressive sampling [21] For bandwidth saving between AMI and the data collector Wavelet domain singular value decomposition (WDSVD) [22] Compressing measurement signals for SG monitoring Singular Value Decomposition (SVD)…”

Section: Dimensionality Reduction Technique Applicationmentioning

confidence: 99%

The Paradigm Revolution in the Distribution Grid: The Cutting-Edge and Enabling Technologies

Thasnimol

Rajathy

2020

Open Computer Science

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Bi-directional information and energy flow, renewable energy sources, battery energy storage, electric vehicle, self-healing capability, and demand response programs, etc., revolutionized the traditional distribution network into the smart distribution network. Adoption of modern technologies like intelligent meters such as advanced metering infrastructure & Micro-phasor measurement units, data storage, and analysis techniques and incentive-based electricity trading mechanisms can bring this paradigm shift. This study presents an overview of popular technologies that facilitate this transformation, giving focus on some prime technologies such as real-time monitoring based on Micro-phasor measurement units, data storage and analytics, blockchain technology, multi-agent systems, and incentive-based energy trading mechanisms

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“…The dimensionality reduction technique is used to verify validity of SVD by establishing a threshold value, and the progressive partitioning algorithm divides the synchrophasor data into partitions with desirable dimensions for better CR. A data compression method based on wavelet domain SVD has been proposed in [16]. This method divides the power signal into a two-dimensional matrix, the twodimensional DWT is used to decompose the original matrix into sub-matrices, and then SVD is used to compress the submatrices data.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic and Parallel Two-Stage Lossless Data Compression Method for Smart Grid

Wu,

Xu,

et al. 2023

IEEE Access

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With the rapid development of smart grid (SG) technologies, massive system data has been generated for SG for grid operation status monitoring and fault warning, this massive integrated data has brought great challenges for data transmission and storage. Thus, the breakthrough of data compression technology has become more and more important for data processing, this proposal, a lossless data compression method is proposed. The proposed method improves the Lempel-Ziv-Welch (LZW) algorithm. Specifically, the proposed method employs a parallel search approach to search the index of the dictionary globally by dividing the dictionary into several small dictionaries of different sizes and bit widths. In addition, the dynamic variable-length coding method is used as the output code which can offer flexible bit widths instead of fixed values, and the optimal dictionary partition combination and size parameters are selected to construct dictionaries. At last, the improved algorithm is cascaded with Huffman algorithm to form the proposed data compression algorithm. The data compression efficiency has been successfully verified by comparing with conventional Huffman and LZW data compression algorithms through data simulation, and it is observed to offer a better compression ratio than those methods with only LZW algorithm or Huffman algorithm, and save storage space effectively. More than this, the proposed method has realized lossless compression for power system data and guaranteed the integrity of the data, which will have better applicability for dealing with any similar information data.INDEX TERMS Lossless data compression, smart grid, Huffman algorithm, LZW algorithm.

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Instructions Data Compression for Smart Grid Monitoring using Wavelet Domain Singular Value Decomposition

Cited by 7 publications

References 25 publications

Compression Techniques for Real-Time Control and Non-Time-Critical Big Data in Smart Grids: A Review

Compression Techniques for Real-Time Control and Non-Time-Critical Big Data in Smart Grids: A Review

The Paradigm Revolution in the Distribution Grid: The Cutting-Edge and Enabling Technologies

A Dynamic and Parallel Two-Stage Lossless Data Compression Method for Smart Grid

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