Big data usage in electrical distribution systems: A review

Authors

Keywords:

Distribution System, Dynamic Energy Management, Smart Grid, Data Analytics, Big-data

Abstract

By this study, author aims for reader to get basic knowledge about relation between data and distribution systems and big-data analytics concept on energy distribution systems. Concept of intelligent energy systems, namely smart grid is described. Big-data basics is explained. Benefits of data-driven systems are searched. A detailed information about applications of big-data on distribution systems is given. Sources of energy big-data is mentioned. Finally, we point out the challenges of managing big data-driven distribution systems. Affect of big-data analytics of energy efficiency. A comprehensive review on big data driven smart energy management applications is presented.

References

[1] Zhang, Y., Huang, T., Bompard, E. F., “Big data analytics in smart grids a review”, Energy Informatics, pp. 1-8, 2018

[2] Abhisek, U., Zivanovic, R., “Automated Analysis of Power Systems Disturbance Records: Smart Grid Big Data Perspective”, IEEE Innovative Smart Grid Technologies, 2015.

[3] Sagiroglu, S., Terzi, R., Canbay, Y., Colak, I., “Big Data Issues in Smart Grid Systems”, IEEE International Conference on Renewable Energy Research and Applications (ICRERA), 2016.

[4] Günther, W. A., Mehrizi, M. H. R., Huysman, M., Feldberg, F., “Debating big data: a literature review on realizing value from big data”, Journal of Strategic Information Systems, 26:191–209, 2017.

[5] Yu, N., Shah, S., Johnson, R., Sherick, R., Hong, M., Loparo, K., “Big Data Analytics in Power Distribution Systems” IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2016.

[6] Lai, C. S., Lai, L. L., “Application of Big Data in Smart Grid”, IEEE International Conference on Systems, Man, and Cybernetics, 2015.

[7] “Big data in the cloud: Converging technologies”, IT Center, Intel, 2015.

[8] http://en.wikipedia.org/wiki/Quantum_computing, 2015.

[9] https://www.smartgrid.gov/the_smart_grid/smart_gri

d.html, 2019.

[10] Feng, G., “Frameworks for Big Data Integration, Warehousing, and Analytics”, chapter 4 in “Big Data Application in Power Systems”, edited by Arghandeh, R. and Zhou, Y., Elsevier, 2018.

[11] Liu Q., Cui L., Chen H., “Key technologies and applications of internet of things”, Computer Science 37 (6), 2010.

[12] Yu, N., Shah, S., Johnson, R., Sherick, R., Hong, M. & Loparo, K., “Big Data Analytics in Power Distribution Systems”, IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2016.

[13] Peppanen, J., Reno, M. J., Broderick, R. J., Grijalva, S., “Distribution System Model Calibration With Big Data From AMI and PV Inverters”, IEEE Transactions on Smart Grid, Vol 7, No 5, 2016.

[14] Nasiakou, A., Alamaniotis, M., Tsoukala, L. H., “Power distribution network partitioning in big data environment using k-means and fuzzy logic”, Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, 2016.

[15] Lydia, E. L., Kumar, B. P., Ramya, D., “Generation of dynamic energy management using data mining techniques basing on big data analytics issues in smart grids”, International Journal of Engineering & Technology, pp. 85-89, 2018.

[16] Flick, D., Kuschicke, F., Schweikert, M., Thiele, T., Herrmann, C., “Ascertainment of Energy Consumption Information in the Age of Industrial Big Data”, Procedia CIRP, V.72, pp. 202-208, 2018.

[17] Mujeeb, S., Javaid, N., Khalid, R., Nazeer, O., Sha, I. & Khan, M., “Big Data Analytics for Price and Load Forecasting in Smart Grids”, 13th International Conference on Broad-Band Wireless Computing, Communication and Applications (BWCCA), 2018.

[18] Ukil, A., Zivanovic, R., “Automated Analysis of Power Systems Disturbance Records: Smart Grid Big Data Perspective”, IEEE Innovative Smart Grid Technologies, 2015.

[19] Park, E., “Positive or negative? Public perceptions of nuclear energy in South Korea: Evidence from Big Data”, Nuclear Engineering and Technology, V.51, pp. 626-630, 2019.

[20] Chen, J., Chen, H. Y., Wen, M. & Sun, S., “Industrial power demand forecasting based on big data technology orienting to energy internet: A case study of Hunan Province”, IOP Conference Series: Earth and Environmental Science 188, 2018.

[21] Batra, N., Singh, A., Whitehouse, K., “Neighbourhood NILM: A Big-data Approach to Household Energy Disaggregation”, Computer Science Machine Learning, 2015.

[22] Wu, W., Lin, W., Hsu, C. H., He, L., “Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights”, Future Generation Computer Systems, cilt 86, pp. 1351-1367, 2018.

[23] Tu, C., He, Xi., Shuai, Z., Jiang, F., “Big data issues in smart grid – A review”, Renewable and Sustainable Energy Reviews, V.79, pp. 1099-1107, 2017.

[24] Kennedy, S., J., “Transforming big data into knowledge: experimental techniques in dynamic visualization”, Massachusetts Institute of Technology, 2012.

[25] Cuzzocrea, A., “Privacy and security of big data: current challenges and future research perspectives”, Proceedings of the international workshop on privacy & security of big data, p. 45–7, 2014.

[26] Bertino, E., “Big data – security and privacy”, Proceedings of the IEEE international congress on big data, 2015.

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Published

2019-07-06

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Section

Review Articles

How to Cite

Big data usage in electrical distribution systems: A review. (2019). International Journal of Applied Business and Management Studies, 4(2), 43-53. https://journal.bauderpress.org.tr/index.php/ijabms/article/view/236