Power systems big data analytics: An assessment of paradigm shift barriers and prospects

Akhavan-Hejazi, Hossein; Mohsenian-Rad, Hamed

doi:10.1016/j.egyr.2017.11.002

Title: Power systems big data analytics: An assessment of paradigm shift barriers and prospects

Journal Article · 31 October 2018 · Energy Reports

DOI: https://doi.org/10.1016/j.egyr.2017.11.002 · OSTI ID:1633483

Akhavan-Hejazi, Hossein; Mohsenian-Rad, Hamed

Not Available

View Journal Article

Cite

Export

Save

Research Organization:: Univ. of California, Riverside, CA (United States)

Sponsoring Organization:: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

Grant/Contract Number:: EE0008001

OSTI ID:: 1633483

Journal Information:: Energy Reports, Journal Name: Energy Reports Journal Issue: C Vol. 4; ISSN 2352-4847

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (39)

Monitoring wind turbine gearboxes: Monitoring wind turbine gearboxes Feng, Yanhui; Qiu, Yingning; Crabtree, Christopher J. Wind Energy, Vol. 16, Issue 5 https://doi.org/10.1002/we.1521	journal	July 2012
Wind turbine SCADA alarm analysis for improving reliability: Improving wind turbine reliability Qiu, Yingning; Feng, Yanhui; Tavner, Peter Wind Energy, Vol. 15, Issue 8 https://doi.org/10.1002/we.513	journal	December 2011
Accelerating the Benders decomposition for network-constrained unit commitment problems Wu, Lei; Shahidehpour, Mohammad Energy Systems, Vol. 1, Issue 3 https://doi.org/10.1007/s12667-010-0015-4	journal	June 2010
ScaLAPACK: a portable linear algebra library for distributed memory computers — design issues and performance Choi, J.; Demmel, J.; Dhillon, I. Computer Physics Communications, Vol. 97, Issue 1-2 https://doi.org/10.1016/0010-4655(96)00017-3	journal	August 1996
An unsupervised training method for non-intrusive appliance load monitoring Parson, Oliver; Ghosh, Siddhartha; Weal, Mark Artificial Intelligence, Vol. 217 https://doi.org/10.1016/j.artint.2014.07.010	journal	December 2014
A decomposition method for network-constrained unit commitment with AC power flow constraints Bai, Yang; Zhong, Haiwang; Xia, Qing Energy, Vol. 88 https://doi.org/10.1016/j.energy.2015.05.082	journal	August 2015
The Internet of Energy: Smart Sensor Networks and Big Data Management for Smart Grid Jaradat, Manar; Jarrah, Moath; Bousselham, Abdelkader Procedia Computer Science, Vol. 56 https://doi.org/10.1016/j.procs.2015.07.250	journal	January 2015
Mobile social media for smart grids customer engagement: Emerging trends and challenges Moreno-Munoz, A.; Bellido-Outeirino, F. J.; Siano, P. Renewable and Sustainable Energy Reviews, Vol. 53 https://doi.org/10.1016/j.rser.2015.09.077	journal	January 2016
Forecasting of preprocessed daily solar radiation time series using neural networks Paoli, Christophe; Voyant, Cyril; Muselli, Marc Solar Energy, Vol. 84, Issue 12 https://doi.org/10.1016/j.solener.2010.08.011	journal	December 2010
Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed Chow, Chi Wai; Urquhart, Bryan; Lave, Matthew Solar Energy, Vol. 85, Issue 11 https://doi.org/10.1016/j.solener.2011.08.025	journal	November 2011
Applying thermophysics for wind turbine drivetrain fault diagnosis using SCADA data Qiu, Yingning; Feng, Yanhui; Sun, Juan IET Renewable Power Generation, Vol. 10, Issue 5 https://doi.org/10.1049/iet-rpg.2015.0160	journal	May 2016
A formal definition of Big Data based on its essential features De Mauro, Andrea; Greco, Marco; Grimaldi, Michele Library Review, Vol. 65, Issue 3 https://doi.org/10.1108/LR-06-2015-0061	journal	April 2016
The US National Lightning Detection Network/sup TM/ and applications of cloud-to-ground lightning data by electric power utilities Cummins, K. L.; Krider, E. P.; Malone, M. D. IEEE Transactions on Electromagnetic Compatibility, Vol. 40, Issue 4 https://doi.org/10.1109/15.736207	journal	January 1998
E-Sketch: Gathering large-scale energy consumption data based on consumption patterns Huang, Zhichuan; Luo, Hongyao; Skoda, David 2014 IEEE International Conference on Big Data (Big Data) https://doi.org/10.1109/BigData.2014.7004289	conference	October 2014
Social networking for Smart Grid users Huang, Yilin; Warnier, Martijn; Brazier, Frances 2015 IEEE 12th International Conference on Networking, Sensing and Control (ICNSC) https://doi.org/10.1109/ICNSC.2015.7116077	conference	April 2015
Optimal Dispatch of Residential Photovoltaic Inverters Under Forecasting Uncertainties Dall'Anese, Emiliano; Dhople, Sairaj V.; Johnson, Brian B. IEEE Journal of Photovoltaics, Vol. 5, Issue 1 https://doi.org/10.1109/JPHOTOV.2014.2364125	journal	January 2015
The internet of energy: a web-enabled smart grid system Bui, Nicola; Castellani, Angelo; Casari, Paolo IEEE Network, Vol. 26, Issue 4 https://doi.org/10.1109/MNET.2012.6246751	journal	January 2012
Modeling and Optimization for Big Data Analytics: (Statistical) learning tools for our era of data deluge Slavakis, Konstantinos; Giannakis, Georgios B.; Mateos, Gonzalo IEEE Signal Processing Magazine, Vol. 31, Issue 5 https://doi.org/10.1109/MSP.2014.2327238	journal	September 2014
A data-driven analysis of lightning-initiated contingencies at a distribution grid with a PV farm using Micro-PMU data Shahsavari, Alireza; Farajollahi, Mohammad; Stewart, Emma 2017 North American Power Symposium (NAPS) https://doi.org/10.1109/NAPS.2017.8107307	conference	September 2017
Addressing the challenges for integrating micro-synchrophasor data with operational system applications Stewart, E. M.; Kiliccote, S.; Shand, C. M. 2014 IEEE Power & Energy Society General Meeting, 2014 IEEE PES General Meeting \| Conference & Exposition https://doi.org/10.1109/PESGM.2014.6938994	conference	July 2014
Event detection and localization in distribution grids with phasor measurement units Ardakanian, Omid; Yuan, Ye; Dobbe, Roel 2017 IEEE Power & Energy Society General Meeting (PESGM) https://doi.org/10.1109/PESGM.2017.8273895	conference	July 2017
Data-Driven Wind Turbine Power Generation Performance Monitoring Long, Huan; Wang, Long; Zhang, Zijun IEEE Transactions on Industrial Electronics, Vol. 62, Issue 10 https://doi.org/10.1109/TIE.2015.2447508	journal	October 2015
Unsupervised Disaggregation of Photovoltaic Production From Composite Power Flow Measurements of Heterogeneous Prosumers Sossan, Fabrizio; Nespoli, Lorenzo; Medici, Vasco IEEE Transactions on Industrial Informatics, Vol. 14, Issue 9 https://doi.org/10.1109/TII.2018.2791932	journal	September 2018
Fuzzy ART Neural Network Algorithm for Classifying the Power System Faults Vasilic, S.; Kezunovic, M. IEEE Transactions on Power Delivery, Vol. 20, Issue 2 https://doi.org/10.1109/TPWRD.2004.834676	journal	April 2005
Zero Duality Gap in Optimal Power Flow Problem Lavaei, Javad; Low, Steven H. IEEE Transactions on Power Systems, Vol. 27, Issue 1 https://doi.org/10.1109/TPWRS.2011.2160974	journal	February 2012
Chance-Constrained AC Optimal Power Flow for Distribution Systems With Renewables DallAnese, Emiliano; Baker, Kyri; Summers, Tyler IEEE Transactions on Power Systems, Vol. 32, Issue 5 https://doi.org/10.1109/TPWRS.2017.2656080	journal	September 2017
Fully Distributed State Estimation for Wide-Area Monitoring Systems Xie, Le; Choi, Dae-Hyun; Kar, Soummya IEEE Transactions on Smart Grid, Vol. 3, Issue 3 https://doi.org/10.1109/TSG.2012.2197764	journal	September 2012
Household Energy Consumption Segmentation Using Hourly Data Kwac, Jungsuk; Flora, June; Rajagopal, Ram IEEE Transactions on Smart Grid, Vol. 5, Issue 1 https://doi.org/10.1109/TSG.2013.2278477	journal	January 2014
Data-Driven Targeting of Customers for Demand Response Kwac, Jungsuk; Rajagopal, Ram IEEE Transactions on Smart Grid, Vol. 7, Issue 5 https://doi.org/10.1109/TSG.2015.2480841	journal	September 2016
Energy Big Data Analytics and Security: Challenges and Opportunities Hu, Jiankun; Vasilakos, Athanasios V. IEEE Transactions on Smart Grid, Vol. 7, Issue 5 https://doi.org/10.1109/TSG.2016.2563461	journal	September 2016
Distribution Grid Reliability Versus Regulation Market Efficiency: An Analysis Based on Micro-PMU Data Shahsavari, Alireza; Sadeghi-Mobarakeh, Ashkan; Stewart, Emma M. IEEE Transactions on Smart Grid, Vol. 8, Issue 6 https://doi.org/10.1109/TSG.2017.2718560	journal	November 2017
Exploiting massive PMU data analysis for LV distribution network model validation Shand, Corinne; McMorran, Alan; Stewart, Emma 2015 50th International Universities Power Engineering Conference (UPEC) https://doi.org/10.1109/UPEC.2015.7339798	conference	September 2015
MAD skills: new analysis practices for big data Cohen, Jeffrey; Dolan, Brian; Dunlap, Mark Proceedings of the VLDB Endowment, Vol. 2, Issue 2 https://doi.org/10.14778/1687553.1687576	journal	August 2009
The Smart Grid's Data Generating Potentials Aiello, Marco; Pagani, Giuliano Andrea 2014 Federated Conference on Computer Science and Information Systems, Annals of Computer Science and Information Systems https://doi.org/10.15439/2014F509	conference	September 2014
Contextually Supervised Source Separation with Application to Energy Disaggregation Wytock, Matt; Kolter, J. Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 28, Issue 1 https://doi.org/10.1609/aaai.v28i1.8769	journal	June 2014
Business Intelligence and Analytics: From Big Data to Big Impact MIS Quarterly, Vol. 36, Issue 4 https://doi.org/10.2307/41703503	journal	January 2012
Stochastic Optimal Power Flow Based on Data-Driven Distributionally Robust Optimization Guo, Yi; Baker, Kyri; Dall'Anese, Emiliano 2018 Annual American Control Conference (ACC) https://doi.org/10.23919/ACC.2018.8431542	conference	June 2018
Power System State Estimation and Bad Data Detection by Means of Conic Relaxation Madani, Ramtin; Lavaei, Javad; Baldick, Ross Proceedings of the Annual Hawaii International Conference on System Sciences https://doi.org/10.24251/HICSS.2017.375	conference	January 2017
An Approach of Quantifying Gear Fatigue Life for Wind Turbine Gearboxes Using Supervisory Control and Data Acquisition Data Qiu, Yingning; Chen, Lang; Feng, Yanhui Energies, Vol. 10, Issue 8 https://doi.org/10.3390/en10081084	journal	July 2017

Similar Records

Mapping mineral prospectivity through big data analytics and a deep learning algorithm

Journal Article · 2018 · Ore Geology Reviews · OSTI ID:1636788

Xiong, Yihui; Zuo, Renguang; Carranza, Emmanuel John M.

Big Effect of Small Nanoparticles: A Shift in Paradigm for Polymer Nanocomposites

Journal Article · 2017 · ACS Nano · OSTI ID:1341569

Cheng, Shiwang; Xie, Shi-Jie; Carrillo, Jan-Michael Y.; +8 more

Ophidia: Toward Big Data Analytics for eScience

Journal Article · 2012 · Procedia Computer Science · OSTI ID:1876524

Fiore, S.; D’Anca, A.; Palazzo, C.; +3 more

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
big data analytics
energy
internet of energy
smart grid

Title: Power systems big data analytics: An assessment of paradigm shift barriers and prospects

Citation Formats

References (39)

Similar Records

Related Subjects