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AUTHOR(S):

Benjamín Zayas, Alfredo Espinosa, Vicky Sanchez, Javier Perez

 

TITLE

Getting ready for data analytics of electric power distribution systems

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ABSTRACT

The modernization of power utilities through the deployment of emergent technologies across the grid and advanced information systems are producing large amount of data that have to be managed with new approaches and technologies using existing and new analytical techniques. Data analysis is taking an important role in supporting decision making, big data technologies enable the analysis of data that was not possible using conventional systems for managing data. Analytical models have also evolved from descriptive to advanced analytics. Advanced analytics refer to the analysis of the data that produce results in which traditional business intelligence approaches are not appropriate. Therefore, an analytical platform has to be adopted by the utilities that better fit to the analytics needs in order to extract remarkable values for efficiently and effectively driven decisions while saving implementation cost.

KEYWORDS

big data; analytics; power utilities; analytics models

REFERENCES

[1] International Energy Agency, “Technology Roadmap Smart Grids”, IEA, Paris, 2011.

[2] K. Zhou, C. Fu and S. Yang, “Big data driven smart energy management: from big data to big insights”, Renewable and Sustainable Energy Reviews, vol. 56, pp. 215-225, 2016.

[3] C. L. Stimmel, Big Data Analytics Strategies for The Smart Grid, London: CRS Press, 2015.

[4] D. Loshin, Big Data Analytics, London: Elsevier, 2013.

[5] P. C. Zikopoulos, C. Eaton, D. deRoos, T. Deutsch y G. Lapis, Understanding Big Data, London: McGraw-Hill, 2012.

[6] P. Russom, “Big Data Analytics”, The Data Warehousing Institute, Renton, WA, 2011.

[7] O’Reilly Media, Inc., Big Data Now, Cambridge: O’Reilly Media, 2012.

[8] Halo, “Descriptive, Predictive, and Prescriptive Analytics Explained”. Accessed 29 06 2016.
[Online]. Available: https://halobi.com/2014/10/descriptive-predictive-and-prescriptive-analytics-explained/.

[9] EPRI, “Program on Technology Innovation: Data Analytics and Customer Insights”, The Electric Power Research Institute, Palo Alto, 2014.

[10] Utility Analytics Institute, "Customer Analytics Report," Aurora, CO, 2014.

[11] C. Sing Lai y M. D. McCulloch, “Big Data Analytics for Smart Grid” IEEE Smart Grid Newsletter, 2015.

[12] S. Callaghan y G. Gauthier, “Driving Operational Excellence Using Analytics “Apps” on a Common Foundation” Utility Analytics Summit Conference, Phoenix, 2015.

[13] M. Angalakudati, “Optimize Asset Maintenance Risk Models Enable Better Decisions” The Utility Analytics Institute, Phoenix, 2015.

[14] A. Espinosa-Reza, M. L. Torres Espíndola, M. Molina-Marín, E. Granados-Gómez y H. R. Aguilar-Valenzuela, “Semantic Interoperability for Historical and Real Time Data Using CIM and OPC-UA for the Smart Grid in Mexico” X, Unpublished.

[15] M. Molina-Marín, E. Granados-Gómez y H. R. Aguilar-Valenzuela, “CIM-Based System for Implementing a Dynamic Dashboard and Analysis Tool for Losses Reduction in the Distribution Power Systems in México” XX, Unpublished.

[16] I. Parra, A. Espinosa, G. Arroyo y S. González, “Innovative Architecture for Information Systems for a Mexican Electricity Utility” de CIGRE 2012 General Meeting, Paris, 2012.

[17] The Apache Software Foundation. (21 06 2016) “Welcome to Apache™ Hadoop®!”, The Apache Software Foundation, 2016. Accessed 15 07 2016.
[Online]. Available: http://hadoop.apache.org/.

[18] T. White, in Hadoop: The Definitive Guide, Sebastopol, O'Reilly Media Inc., 2012, p. 657.

[19] The Apache Software Foundation, (21 06 2016) “Apache Sqoop,” The Apache Software Foundation, 2016. Accessed 16 07 2016
[Online]. Available: http://sqoop.apache.org/.

[20] The Apache Software Foundation, (25 07 2016.) “Apache Spark: Lightning-fast cluster computing” 2016, Accessed 16 07 2016
[Online]. Available: http://spark.apache.org/.

[21] The Apache Software Foundation, “APACHE HIVE TM” The Apache Software Foundation, 2014. Accessed 16 07 2016
[Online]. Available: https://hive.apache.org/.

Cite this paper

Benjamín Zayas, Alfredo Espinosa, Vicky Sanchez, Javier Perez. (2017) Getting ready for data analytics of electric power distribution systems. International Journal of Computers, 2, 179-186

 

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