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Artificial intelligent-based optimization of automated home energy management systems

2016; Wiley; Volume: 26; Issue: 9 Linguagem: Inglês

10.1002/etep.2195

2050-7038

Mahmoud Elkazaz, Ayman Hoballah, Ahmed M. Azmy,

Microgrid Control and Optimization

International Transactions on Electrical Energy SystemsVolume 26, Issue 9 p. 2038-2056 Research Article Artificial intelligent-based optimization of automated home energy management systems Mahmoud H. Elkazaz, Corresponding Author Mahmoud H. Elkazaz mahmoud.elkazaz@f-eng.tanta.edu.eg Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt Correspondence to: Mahmoud H. Elkazaz, Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt. E-mail: mahmoud.elkazaz@f-eng.tanta.edu.egSearch for more papers by this authorAyman Hoballah, Ayman Hoballah Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, EgyptSearch for more papers by this authorAhmed M. Azmy, Ahmed M. Azmy Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, EgyptSearch for more papers by this author Mahmoud H. Elkazaz, Corresponding Author Mahmoud H. Elkazaz mahmoud.elkazaz@f-eng.tanta.edu.eg Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt Correspondence to: Mahmoud H. Elkazaz, Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt. E-mail: mahmoud.elkazaz@f-eng.tanta.edu.egSearch for more papers by this authorAyman Hoballah, Ayman Hoballah Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, EgyptSearch for more papers by this authorAhmed M. Azmy, Ahmed M. Azmy Department of Electrical Power and Machines Engineering, Faculty of Engineering, Tanta University, Tanta, EgyptSearch for more papers by this author First published: 23 February 2016 https://doi.org/10.1002/etep.2195Citations: 16Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Summary With the tendency to move toward automated home energy management systems, the cooperative capacity of the smart grid "SG" became more and more significant. Distributed generation "DG", in addition to the novel patterns of electricity production, enabled the two-way energy flow. The concern of this paper is on introducing an automated control technique for optimizing the operational performance of the DG units within the residential applications. This problem is formulated in a constrained-nonlinear optimization structure based on a detailed economic system. Genetic algorithm "GA" technique is used to solve this problem by defining the optimal settings of the DG units. Availability of two-way communication and the use of smart meters will enable online implementation and facilitate data collection within a fully automated system. Based on certain tariffs and realistic load curves, many scenarios of operation are analyzed and assessed. The results show that using optimization technique in cooperative with advanced smart meters can enhance the economic situation of the overall grid significantly. Copyright © 2016 John Wiley & Sons, Ltd. Citing Literature Volume26, Issue9September 2016Pages 2038-2056 RelatedInformation