dc.contributor.author | Amankhan, Assilkhan | |
dc.contributor.author | Kural, Askat | |
dc.date.accessioned | 2021-01-25T09:24:02Z | |
dc.date.available | 2021-01-25T09:24:02Z | |
dc.date.issued | 2020-04-27 | |
dc.identifier.uri | http://nur.nu.edu.kz/handle/123456789/5236 | |
dc.description.abstract | This study has specifically focused to develop a multi-functional Smart Meter (SM) which would be able to address some of the challenges currently available in the conventional digital automated metering system in Eurasia. SMs with its unique performance with the Internet of Things (IoT) tend to be an efficient system for electricity management, secure against the intervention by third parties, and reliable for real-time remote monitoring and tracking via mobile application as well as web application. IoT-based architecture of SM is proposed along with employing anti-theft algorithms and Long Short-Term Memory (LSTM) load forecasting that can assist in maintaining energy management systems [1]. For industrial purpose, SM enables the customers to monitor the ageing and vibration of the transformer in order to adjust loading for the life extension of the transformer. The consumption patterns obtained by SM are studied and discussed. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Nazarbayev University School of Engineering and Digital Sciences | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | * |
dc.subject | Long Short-Term Memory | en_US |
dc.subject | LSTM | en_US |
dc.subject | Smart Meter | en_US |
dc.subject | Load Forecasting technique | en_US |
dc.subject | Internet of Things | en_US |
dc.subject | IoT | en_US |
dc.subject | SM | en_US |
dc.subject | Research Subject Categories::TECHNOLOGY | en_US |
dc.title | SMART METER DESIGN AND IMPLEMENTATION USING LOAD FORECASTING TECHNIQUE | en_US |
dc.type | Capstone Project | en_US |
workflow.import.source | science |
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