Tensor-Based Big Data Management Scheme for Dimensionality Reduction Problem in Smart Grid Systems: SDN Perspective

Purpose The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly. Design/methodology/approach In this paper, the authors proposed a big data management and analytic approach for disability datasets. Findings By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach. Originality/value The proposed approach can enable data-driven decision-making for professionals who work with disabled populations.

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A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid

Sustainability ◽

10.3390/su132313322 ◽

2021 ◽

Vol 13 (23) ◽

pp. 13322

Author(s):

Vinoth Kumar Ponnusamy ◽

Padmanathan Kasinathan ◽

Rajvikram Madurai Elavarasan ◽

Vinoth Ramanathan ◽

Ranjith Kumar Anandan ◽

...

Keyword(s):

Big Data ◽

Smart Grid ◽

Data Management ◽

Smart Grids ◽

Data Analytics ◽

Management Practices ◽

Research Work ◽

Big Data Analytics ◽

Energy Data ◽

The Sustainable Development

The role of energy is cardinal for achieving the Sustainable Development Goals (SDGs) through the enhancement and modernization of energy generation and management practices. The smart grid enables efficient communication between utilities and the end- users, and enhances the user experience by monitoring and controlling the energy transmission. The smart grid deals with an enormous amount of energy data, and the absence of proper techniques for data collection, processing, monitoring and decision-making ultimately makes the system ineffective. Big data analytics, in association with the smart grid, enable better grid visualization and contribute toward the attainment of sustainability. The current research work deals with the achievement of sustainability in the smart grid and efficient data management using big data analytics, that has social, economic, technical and political impacts. This study provides clear insights into energy data generated in the grid and the possibilities of energy theft affecting the sustainable future. The paper provides insights about the importance of big data analytics, with their effects on the smart grids’ performance towards the achievement of SDGs. The work highlights efficient real-time energy data management involving artificial intelligence and machine learning for a better future, to short out the effects of the conventional smart grid without big data analytics. Finally, the work discusses the challenges and future directions to improve smart grid technologies with big data analytics in action.

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Multi-Attribute based on Data Management Scheme in Big Data Environment

Journal of Digital Convergence ◽

10.14400/jdc.2015.13.1.263 ◽

2015 ◽

Vol 13 (1) ◽

pp. 263-268

Author(s):

Yoon-Su Jeong ◽

Yong-Tae Kim ◽

Gil-Cheol Park

Keyword(s):

Big Data ◽

Data Management ◽

Management Scheme ◽

Data Environment

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Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study

Complexity ◽

10.1155/2018/8496187 ◽

2018 ◽

Vol 2018 ◽

pp. 1-21 ◽

Cited By ~ 7

Author(s):

Yuanjun Guo ◽

Zhile Yang ◽

Shengzhong Feng ◽

Jinxing Hu

Keyword(s):

Machine Learning ◽

Big Data ◽

Smart Grid ◽

Power System ◽

Data Management ◽

Power Grid ◽

Technical Solution ◽

Data Platform ◽

Complex Power ◽

Big Data Technology

Efficient and valuable strategies provided by large amount of available data are urgently needed for a sustainable electricity system that includes smart grid technologies and very complex power system situations. Big Data technologies including Big Data management and utilization based on increasingly collected data from every component of the power grid are crucial for the successful deployment and monitoring of the system. This paper reviews the key technologies of Big Data management and intelligent machine learning methods for complex power systems. Based on a comprehensive study of power system and Big Data, several challenges are summarized to unlock the potential of Big Data technology in the application of smart grid. This paper proposed a modified and optimized structure of the Big Data processing platform according to the power data sources and different structures. Numerous open-sourced Big Data analytical tools and software are integrated as modules of the analytic engine, and self-developed advanced algorithms are also designed. The proposed framework comprises a data interface, a Big Data management, analytic engine as well as the applications, and display module. To fully investigate the proposed structure, three major applications are introduced: development of power grid topology and parallel computing using CIM files, high-efficiency load-shedding calculation, and power system transmission line tripping analysis using 3D visualization. The real-system cases demonstrate the effectiveness and great potential of the Big Data platform; therefore, data resources can achieve their full potential value for strategies and decision-making for smart grid. The proposed platform can provide a technical solution to the multidisciplinary cooperation of Big Data technology and smart grid monitoring.

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