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Jakarta Lightning Detection System
Wibowo A.M.a, Zoro R.a
a Power System and Electrical Distribution Laboratory, Electrical Power Engineering, School of Electrical Engineering and Informatics, 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]© 2019 IEEE.Lightning is a serious problem for modern community. Direct lightning stroke can damage or destroy an obect and hurt or even kill a living thing. Indirect lightning stroke can damage elecronic and microcontroller stuff because it has very small or thin insulation. For all of that reason, Lightning Detection System (LDS) is needed to minimize the loss that caused by lightning strike. LDS can split into real time application and historical application. Real time application of LDS used as early warning of lightning strike. Historical application of LDS used as consideration in long planning such as structure planning, work shift planning, and lightning protection planning, etc. Observation area is DKI Jakarta from 4th April 2017 until 18th July 2018. In this study, the data collection is done through documentation studies. Data collection done by collecting data from existing database that belong to PT PLN Puslitbang using software Vaisala FALLS. The data that collected is the location, time, and peak current of flash. Lightning data then get processed using Microsoft Excel and Google Earth then shown as flash density map, variance of monthly lightning events, and peak current probability.[/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]Data collection,Direct lightning stroke,Indirect lightning,Lightning detection,Lightning strikes,Microsoft excel,Observation area,Real-time application[/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]Lightning data,Lightning Detection System,Modern community[/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]This research was supported by the use of two software applications (software), namely Vaisala FALLS and Microsoft Excel. A web interface nemely Thunderstorm Manager is also used. Hardware that used in this study is LS7002 sensor.[/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/10.1109/ICEEI47359.2019.8988802[/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]