Energy Efficiency in Smart Grid: A Prospective Study on Energy Management Systems


The term Smart Grid has become a term to represent the benefits of a smart and sophisticated electrical grid, which can meet various social expectations related to sustainability and energy efficiency. The Smart Grid promises to enable a better power management for energy utilities and consumers, to provide the ability to integrate the power grid, to support the development of micro grids, and to involve citizens in energy management with higher levels of responsibility. However, this context comes with potential pitfalls, such as vulnerabilities to cyber-security and privacy risks. In this article, a prospective study about energy management, and exploring critical issues of modeling of energy management systems in a context Smart. Grid is presented along with background of energy management systems. An analysis of the demand response condition is also presented. Finally, the advantages and disadvantages of the implementation of energy management systems, and a comparison with the Brazilian electricity system are discussed.

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Loschi, H. , Leon, J. , Iano, Y. , Filho, E. , Conte, F. , Lustosa, T. and Freitas, P. (2015) Energy Efficiency in Smart Grid: A Prospective Study on Energy Management Systems. Smart Grid and Renewable Energy, 6, 250-259. doi: 10.4236/sgre.2015.68021.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Eissa, M. (2012) Energy Efficiency—The Innovative Ways for Smart Energy, the Future towards Modern Utilities.
[2] Ireshika, M.A.S.T. (2014) Home Energy Management System. Universitetet I Agder, Kristiansand & Grimstad.
[3] Khodaei, A., Shahidehpour, M. and Bahramirad, S. (2011) SCUC with Hourly Demand Response Considering Inter-temporal Load Characteristics. IEEE Transactions on Smart Grid, 2, 564-571.
[4] Du, P. and Lu, N. (2011) Appliance Commitment for Household Load Scheduling. IEEE Transactions on Smart Grid, 2, 411-419.
[5] Gatsis, N. and Giannakis, G.B. (2012) Residential Load Control: Distributed Scheduling and Convergence with Lost AMI Messages. IEEE Transactions on Smart Grid, 3, 770-786.
[6] Li, J., Chung, J.Y., Xiao, J., Hong, J.W.-K. and Boutaba, R. (2011) On the Design and Implementation of a Home Energy Management System. Proceedings of the 6th International Symposium on Wireless and Pervasive Computing, Hong Kong, 23-25 February 2011, 1-6.
[7] Stephens, J., Wilson, E.J. and Peterson, T.R. (2015) Smart Grid (R) Evolution. Cambridge University Press, Cambri-dge.
[8] Jiang, T., Yu, L. and Cao, Y. (2015) Energy Management of Internet Data Centers in Smart Grid.
[9] Choi, C.-S., Ian, J.I., Park, W.-K., Jeong, Y.-K. and Lee, I.-W. (2011) Proactive Energy Management System Archi-tecture Interworing with Smart Grid. Proceedings of the IEEE 15th International Symposium on Consumer Electronics, Singapore, 14-17 June 2011, 1-4.
[10] Park, K., Kim, Y., Kim, S., Kim, K., Lee, W. and Park, H. (2011) Building Energy Management System based on Smart Grid. Proceedings of the IEEE 33rd International Telecommunications Energy Conference, Amsterdam, 9-13 October 2011, 1-4.
[11] Balijepalli, V.S.K.M., Pradhan, V., Khaparde, S.A. and Shereef, R.M. (2011) Review of Demand Response under Smart Grid Paradigm. Proceedings of the 2011 IEEE PES International Conference on Innovative Smart Grid Techno-logies-India, Kollam, 1-3 December 2011, 236-243.
[12] Paracha, Z.J. and Doulai, P. (1998) Load Management: Techniques and Methods in Electric Power System. Proceedings of the International Conference on Energy Management and Power Delivery, Singapore, 3-5 March 1998, 213-217.
[13] Medina, J., Muller, N. and Roytelman, I. (2010) Demand Response and Distribution Grid Operations: Opportunities and Challenges. IEEE Transactions on Smart Grid, 1, 193-198.
[14] Bashir, A.K., Ohsita, Y. and Murata, M. (2015) Abstraction Layer Based Distributed Architecture for Virtualized Data Centers. Proceedings of the Sixth International Conference on Cloud Computing, GRIDs, and Virtualization, Nice, 22-27 March 2015, 62-67.
[15] Frey, S., Disch, S., Reich, C., Knahl, M. and Clarke, N. (2015) Cloud Storage Prediction with Neural Networks. Proceedings of the Sixth International Conference on Cloud Computing, GRIDs, and Virtualization, Nice, 22-27 March 2015, 68-72.
[16] Mcilvride, B. (2012) Will SCADA Envolve to the Cloud?
[17] Combs, L. (2011) Cloud Computing for SCADA.
[18] Conway, G., Carcary, M. and Doherty, E. (2015) A Conceptual Framework to Implement and Manage a Cloud Computing Environment. Proceedings of the Sixth International Conference on Cloud Computing, GRIDs, and Vir-tualization, Nice, 22-27 March 2015, 138-142.
[19] Markovic, D.S., Zivkovic, D., Branovic, I., Popovic, R. and Cvetkovic, D. (2013) Smart Power Grid and Cloud Com-puting. Renewable & Sustainable Energy Reviews, 24, 566-577.
[20] Albadi, M.H. and El-Saadany, E.F. (2007) Demand Response in Electricity Markets: An Overview. Proceedings of the 2007 IEEE Power Engineering Society General Meeting, Tampa, 24-28 June 2007, 1-5.

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