Cloud-Based Software Platform for Big Data Analytics in Smart Grids
Abstract
This article focuses on a scalable software platform for the Smart Grid cyber-physical system using cloud technologies. Dynamic Demand Response (D2R) is a challenge-application to perform intelligent demand-side management and relieve peak load in Smart Power Grids. The platform offers an adaptive information integration pipeline for ingesting dynamic data; a secure repository for researchers to share knowledge; scalable machine-learning models trained over massive datasets for agile demand forecasting; and a portal for visualizing consumption patterns, and validated at the University of Southern California's campus microgrid. The article examines the role of clouds and their tradeoffs for use in the Smart Grid Cyber-Physical Sagileystem.
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OSSIM can correlate events from different sources such as firewalls, anomaly detectors, IDS/IPS, and network switches and combine these with known vulnerabilities.
“OSSIM can correlate events from different sources such as firewalls, anomaly detectors, IDS/IPS, and network switches and combine these with known vulnerabilities.”
From Assessing and augmenting SCADA cyber security: A survey of techniques (2017) · cites this paper as [93]
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Antonopoulos, I., Robu, V., Couraud, B., Kirli, D., Norbu, S., Kiprakis, A., Flynn, D., Elizondo-Gonzalez, S., & Wattam, S. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2020.109899 · Cited by 656 · see citing works
Cybersecurity for industrial control systems: A survey
Bhamare, D., Zolanvari, M., Erbad, A., Jain, R., Khan, K., & Meskin, N. (2020) · Computers & Security · doi:10.1016/j.cose.2019.101677 · Cited by 394 · see citing works
Big data analytics for dynamic energy management in smart grids
Diamantoulakis, P. D., Kapinas, V. M., & Karagiannidis, G. K. (2015) · Big Data Research · doi:10.1016/j.bdr.2015.03.003 · Cited by 349 · see citing works
Artificial Intelligence Enabled Demand Response: Prospects and Challenges in Smart Grid Environment
Khan, M. A., Saleh, A. M., Waseem, M., & Sajjad, I. A. (2023) · IEEE Access · doi:10.1109/access.2022.3231444 · Cited by 179 · see citing works
Assessing and augmenting SCADA cyber security: A survey of techniques
Nazir, S., Patel, S., & Patel, D. (2017) · Computers & Security · doi:10.1016/j.cose.2017.06.010 · Cited by 167 · see citing works
“A cloud based data analysis system for Los Angeles Smart Grid Project is described by Simmhan et al. [101].”
BackgroundMethodHabibzadeh, H., Boggio-Dandry, A., Qin, Z., Soyata, T., Kantarci, B., & Mouftah, H. T. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700304 · Cited by 64 · see citing works
Jiang, H., Dai, X., Gao, D. W., Zhang, J. J., Zhang, Y., & Muljadi, E. (2016) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2552229 · Cited by 56 · see citing works
Asset health management using predictive and prescriptive analytics for the electric power grid
Goyal, A., Aprilia, E., Janssen, G., Kim, Y., Kumar, T., Mueller, R., Phan, D., Raman, A., Schuddebeurs, J., Xiong, J., et al. (2016) · IBM Journal of Research and Development · doi:10.1147/jrd.2015.2475935 · Cited by 43 · see citing works
- Authors
- Simmhan, Y., Aman, S., Kumbhare, A., Liu, R., Stevens, S., Zhou, Q., & Prasanna, V.
- Affiliations
- University of Southern California (US)
- Venue
- Computing in Science & Engineering
- Published
- 2013-07
- Volume
- 15
- Issue
- 4
- Pages
- 38-47
- ISSN
- 1521-9615 (ISSN-L)
- OpenAlex
- W2135846084
- Cited by
- 306
- References
- 0
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 4 · 2023: 9 · 2022: 19 · 2021: 23 · 2020: 27 · 2019: 30 · 2018: 42 · 2017: 47 · 2016: 42 · 2015: 33 · 2014: 20 · 2013: 3
- FWCI
- 19.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computing in Science & Engineering (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Keywords
- smart grid, cloud computing, big data analytics, dynamic demand response, demand-side management, peak shaving, cyber-physical systems, demand forecasting, machine learning, data ingestion pipeline, microgrids, campus microgrid
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