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OPTIMAL SCHEDULING AND MANAGEMENT OF A SMART CITY WITHIN THE SAFE FRAMEWORK

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dc.contributor.author Duan, Qunlong
dc.contributor.author Quynh, Nguyen Vu
dc.contributor.author Abdullah, Heba M.
dc.contributor.author Almalaq, Abdulaziz
dc.contributor.author Duc Do, Ton
dc.contributor.author Abdelkader, Sobhy M.
dc.contributor.author Mohamed, Mohamed A.
dc.date.accessioned 2021-02-23T03:38:03Z
dc.date.available 2021-02-23T03:38:03Z
dc.date.issued 2020-09-02
dc.identifier.citation Duan, Q., Quynh, N. V., Abdullah, H. M., Almalaq, A., Duc Do, T., Abdelkader, S. M., & Mohamed, M. A. (2020). Optimal Scheduling and Management of a Smart City Within the Safe Framework. IEEE Access, 8, 161847–161861. https://doi.org/10.1109/access.2020.3021196 en_US
dc.identifier.issn 2169-3536
dc.identifier.uri https://doi.org/10.1109/ACCESS.2020.3021196
dc.identifier.uri https://ieeexplore.ieee.org/document/9184833
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/5332
dc.description.abstract This paper proposes an enhanced cyber secure energy and data transaction framework for the optimal operation and management of the smart city. Recently, the concept of smart city within the power systems has taken the center stage. Although the power system full monitoring and accessibility is guaranteed through the smart city concept, the risk of cyber-attacks to the system has been promoted, severely. With this in mind, in this paper an effective smart city model including the smart grid, smart transportation systems (STSs) that consist of the metro and electric vehicles (EVs), microgrid and smart energy hub (EH) is presented. In the proposed model, an improved directed acyclic graph (DAG) approach is represented in order to enhance the security of data transaction within the smart city. In this approach, a security layer is added to the blockchain which will prevent the cyber hackers access to the system information. An effective energy management schedule is also developed in this paper. To do so, an intelligent priority selection (IPS) based on advanced math operators is provided to allocate the metro-owned charging stations (MCSs), optimally. Furthermore, the unscented transform (UT) is utilized to handle the uncertainty of the system parameters. The results showed that the proposed IPS could improve the method CPU time over 75% compared to other well-known meta-heuristic methods in the area. Moreover, the results showed that the proposed framework has remarkably reduced the run time and increased the accuracy of the solution compared to the other metaheuristic algorithms. en_US
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers en_US
dc.relation.ispartofseries IEEE Access;8, 161847–161861
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject Smart city en_US
dc.subject transportation system en_US
dc.subject microgrid en_US
dc.subject energy management en_US
dc.subject smart grid en_US
dc.subject unscented transform en_US
dc.subject Research Subject Categories::TECHNOLOGY en_US
dc.title OPTIMAL SCHEDULING AND MANAGEMENT OF A SMART CITY WITHIN THE SAFE FRAMEWORK en_US
dc.type Article en_US
workflow.import.source science


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