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Title: Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

Abstract

Big data has a potential to unlock novel, groundbreaking opportunities in the power grid sector that enhances a multitude of technical, social, and economic gains. The currently untapped potential of applying the science of big data for better planning and operation of the power grid is a very challenging task and needs significant efforts all-around. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data sets from diverse sources. In particular, computational complexity, data security, and operational integration of big data into utility decision frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. Moreover, due to the complex nature of power grids along with the need to balance power in real-time, seamless integration of big data into utility operations is very critical. In this context, big data analytics combined with grid visualization can lead to better predictive decisions and situational awareness. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids; also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps, and presents insights on future research directions to integrate bigmore » data analytics into electric utility decision framework. Detailed information for utilities looking to apply big data analytics and details insights on how utilities can enhance revenue streams and bring disruptive innovation in the industry is discussed. More importantly, general guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations is provided.« less

Authors:
 [1];  [2]; ORCiD logo [3]; ORCiD logo [3];  [4];  [5]; ORCiD logo [3]; ORCiD logo [3];  [6];  [7];  [8];  [9];  [10]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Michigan Technological Univ., Houghton, MI (United States)
  3. Idaho National Lab. (INL), Idaho Falls, ID (United States)
  4. GE Grid Solutions, Redmond, WA (United States)
  5. South Dakota State Univ., Brookings, SD (United States)
  6. IBM Research, Almaden, CA (United States)
  7. Oncor Electric Delivery, Dallas, TX (United States)
  8. Virginia Commonwealth Univ., Richmond, VA (United States)
  9. Independent System Operator New England, Holyoke, MA (United States)
  10. California Independent System Operator, Folsom, CA (United States)
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1559939
Report Number(s):
INL/JOU-17-42462-Rev000
Journal ID: ISSN 2515-2947
Grant/Contract Number:  
AC07-05ID14517
Resource Type:
Accepted Manuscript
Journal Name:
IET Smart Grid
Additional Journal Information:
Journal Volume: 2; Journal Issue: 2; Journal ID: ISSN 2515-2947
Country of Publication:
United States
Language:
English
Subject:
13 HYDRO ENERGY; 24 POWER TRANSMISSION AND DISTRIBUTION; 14 SOLAR ENERGY; Big data; data analytics; grid modernization; high performance computing; Smart Grid; visualization

Citation Formats

Bhattarai, Bishnu P., Paudyal, Sumit, Luo, Yusheng, Mohanpurkar, Manish, Cheung, Kwok, Tonkoski, Reinaldo, Hovsapian, Rob, Myers, Kurt S., Zhang, Rui, Zhao, Power, Manic, Milos, Zhang, Song, and Zhang, Xiaping. Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions. United States: N. p., 2019. Web. doi:10.1049/iet-stg.2018.0261.
Bhattarai, Bishnu P., Paudyal, Sumit, Luo, Yusheng, Mohanpurkar, Manish, Cheung, Kwok, Tonkoski, Reinaldo, Hovsapian, Rob, Myers, Kurt S., Zhang, Rui, Zhao, Power, Manic, Milos, Zhang, Song, & Zhang, Xiaping. Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions. United States. doi:10.1049/iet-stg.2018.0261.
Bhattarai, Bishnu P., Paudyal, Sumit, Luo, Yusheng, Mohanpurkar, Manish, Cheung, Kwok, Tonkoski, Reinaldo, Hovsapian, Rob, Myers, Kurt S., Zhang, Rui, Zhao, Power, Manic, Milos, Zhang, Song, and Zhang, Xiaping. Thu . "Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions". United States. doi:10.1049/iet-stg.2018.0261. https://www.osti.gov/servlets/purl/1559939.
@article{osti_1559939,
title = {Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions},
author = {Bhattarai, Bishnu P. and Paudyal, Sumit and Luo, Yusheng and Mohanpurkar, Manish and Cheung, Kwok and Tonkoski, Reinaldo and Hovsapian, Rob and Myers, Kurt S. and Zhang, Rui and Zhao, Power and Manic, Milos and Zhang, Song and Zhang, Xiaping},
abstractNote = {Big data has a potential to unlock novel, groundbreaking opportunities in the power grid sector that enhances a multitude of technical, social, and economic gains. The currently untapped potential of applying the science of big data for better planning and operation of the power grid is a very challenging task and needs significant efforts all-around. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data sets from diverse sources. In particular, computational complexity, data security, and operational integration of big data into utility decision frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. Moreover, due to the complex nature of power grids along with the need to balance power in real-time, seamless integration of big data into utility operations is very critical. In this context, big data analytics combined with grid visualization can lead to better predictive decisions and situational awareness. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids; also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps, and presents insights on future research directions to integrate big data analytics into electric utility decision framework. Detailed information for utilities looking to apply big data analytics and details insights on how utilities can enhance revenue streams and bring disruptive innovation in the industry is discussed. More importantly, general guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations is provided.},
doi = {10.1049/iet-stg.2018.0261},
journal = {IET Smart Grid},
number = 2,
volume = 2,
place = {United States},
year = {2019},
month = {5}
}

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