Cellular Wireless Network Communication for Smart Grid

dc.contributor.authorSillah, Abu Bakarr
dc.contributor.authorAwa, Coulibaly
dc.contributor.authorAichetou, Pamboundom Njoya
dc.contributor.authorHamid, Mohamed
dc.date.accessioned2022-12-26T05:45:48Z
dc.date.available2022-12-26T05:45:48Z
dc.date.issued2022-05-30
dc.descriptionSupervised by Prof. Dr. Rakibul Hasan Sagor, Department of Electrical and Electronics Engineering (EEE), Islamic University of Technology (IUT) , Board Bazar, Gazipur-1704, Bangladesh. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2022.en_US
dc.description.abstractSince the introduction of Long Term Evolution (LTE) networks and now 5th Generation, cellular mobile networks are turning into a great platform for universal massive data capture, communication, storage, and processing. Cellular Wireless Network will offer more acceptable services for operation and realworld applications, especially the anticipation of the upcoming Smart Grids. Throughout this article, we describe how the cellular wireless network, with its rise of Machine-Type Connectivity and the notion of Mobile Edge Computing, provides a suitable setting for dispersed monitoring and control operations in Smart Grids. In particular, we demonstrate in detail how Smart Grids could benefit from enhanced distributed State Prediction models implemented within a cellular network setting. We present an overview of highly scalable State Estimation techniques, focusing on those highly distributed optimizations and likely statistical models, and explore their inclusion as part of the Cellular Smart Grid activities. We also show the prototype utilizing both the software and the hardware implementation. As a consequence, it was evident that the integration of the newest cellular wireless technologies into the conventional power grid would boost its smartness, efficiency, security, power quality, and intelligent communications amongst the distribution substations.en_US
dc.identifier.citationAtay, M. "Three Phase AC Voltage Measurement using Arduino." Retrieved 13, March 2022, from https://bestengineeringprojects.com/three-phase-ac-voltage-measurement-usingarduino. Cosovic, M., et al. (2017). "5G mobile cellular networks: Enabling distributed state estimation for smart grids." IEEE Communications Magazine 55(10): 62-69. Ganguly, P., et al. (2016). Analysis of the security anomalies in the smart metering infrastructure and its impact on energy profiling and measurement. 2016 5th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS), IEEE. Kalalas, C., et al. (2016). "Cellular Communications for Smart Grid Neighborhood Area Networks: A Survey." IEEE Access 4: 1469-1493. Kalathil, D., et al. (2021). Microcontroller based Substation Disaster Monitoring System. 2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I-SMAC), IEEE. Loganathan, N., et al. (2021). Smart Substation Monitoring and Control. 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), IEEE. Narejo, G. B., et al. (2015). Remote Microcontroller Based Monitoring of Substation and Control System Through GSM Modem. Rajnikanth, M. "Substation Equipment Monitoring And Controllig Using IoT." Sangolkar, R. (2020). "Fault Identification and Remote Operation of Receiving Substation and Auxiliary Substation using IoT." International Journal for Research in Applied Science and Engineering Technology 8(9): 250-254. Thakare, S., et al. (2016). Implementation of an energy monitoring and control device based on IoT. 2016 IEEE Annual India Conference (INDICON), IEEE.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1622
dc.language.isoenen_US
dc.publisherDepartment of Electrical and Electronic Engineering(EEE), Islamic University of Technology(IUT),en_US
dc.subject5th Generation 5G American National Standards Institute ANSI automated meter reading device AMR Communications HTC Concentrator or Data Aggregator Unit DAU Demand Response DR Device-to-Device D2D Distribution System Operators DSO energy meter EM energy services interface ESI Fault Location, Isolation, and Service Restoration FLISR Federal Communications Commission FCC Graphical User Interface GUI Home Energy Management System HEMS Intelligent Electronic Devices IEDs Liquid Crystal Display LCD Long Term Evolution (LTE) LTE Machine-Type Communications MT Mobile Network Operators MNOs Neighborhood Area Networks NANs Plug-in Electric Vehicle PEV Power Line Communication PLC Quality-of-Service QoS Remote Terminal Units RTUs Service Level Agreement SLA Supervisory Control and Data Acquisition SCADA User Equipment UE Wireless Automatic Meter Reading System WAMRSen_US
dc.titleCellular Wireless Network Communication for Smart Griden_US
dc.typeThesisen_US

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