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Development of Battery Monitoring System in Smart Microgrid Based on Internet of Things (IoT)
Friansa K.a, Haq I.N.a, Santi B.M.a, Kurniadi D.a, Leksono E.a, Yuliarto B.a
a Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2017 Published by Elsevier Ltd.In this paper, battery monitoring system based on internet of things (IoT) has been developed to monitor the operational and performance of batteries in a smart microgrid system. This smart microgrid includes a battery pack, PV system, Intelligent Electronic Device (IED) hybrid inverter, grid connection and electricity load. The IoT developed in this work consists of a communication channel from and to IED, data acquisition algorithm, cloud system and Human Machine Interface (HMI). Data acquisition was scheduled to execute every minute as mentioned in IEC61724. The battery monitoring system information as part of battery management system (BMS) is displayed on a Human Machine Interface (HMI) using ExtJS / HTML5 framework which can be accessed using desktop or mobile devices. From analytical results, the average execution time for overall BMS-IoT based data acquisition to the cloud server is 19.54 ± 18.00 seconds. The result of availability monitored data in the cloud database server is 92.92 ± 6.00 percent, which shows satisfactory result for the reliability of BMS-IoT system data acquisition.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Analytical results,Average Execution Time,Battery systems,Data-acquisition algorithm,Human Machine Interface,Intelligent electronic device,Internet of Things (IOT),Smart Micro Grids[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]battery monitoring system,battery system,communication protocol,internet of things,smart microgrid[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1016/j.proeng.2017.03.077[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]