UAV-assited Wireless Powered Sensor Network over Rician Shadowed Fading Channels; Microwaves, Antennas, Communications and Electronic Systems (COMCAS)

UAV-assited Wireless Powered Sensor Network over Rician Shadowed Fading Channels; Microwaves, Antennas, Communications and Electronic Systems (COMCAS)

Opis bibliograficzny
Parent link:Microwaves, Antennas, Communications and Electronic Systems (COMCAS).— 2019.— [6 p.]
Korporacja: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники
Kolejni autorzy: Panich S. Stefan, Ponnimbaduge Perera T. D. Tarindu Dilshan, Dzhayakodi (Jayakody) Arachshiladzh D. N. K. Dushanta Nalin Kumara, Stefanovic C. Caslav, Prlincevic B. Bojan
Streszczenie:Title screen
In this study, introduces a cuckoo search (CS) algorithm for determining the global maximum power point (GMPP) of photovoltaic (PV). The traditional methods are failed to track the global maximum power point under partially shaded conditions (PSC), which decrease the reliability of the power system and increase the system losses. The research results of the CS algorithm and perturb and observe (P&O) algorithm are investigated for different cases of operations of PV panels under PSC. The proposed CS model can track the GMPP very accurate with high efficiency in less time under severe weather conditions as well as in PSC.
Режим доступа: по договору с организацией-держателем ресурса
Język:angielski
Wydane: 2019
Hasła przedmiotowe:
электронный ресурс
труды учёных ТПУ
5G communication
Rician Shadowed fading channels
sensor network
unmanned aerial vehicle (UAV)
wireless energy transfer (WET)
5G
сенсорные сети
беспилотные летательные аппараты
беспроводная передача
Dostęp online:https://doi.org/10.1109/COMCAS44984.2019.8958112
Format: Elektroniczne Rozdział
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=662291
Opis
Streszczenie:Title screen
In this study, introduces a cuckoo search (CS) algorithm for determining the global maximum power point (GMPP) of photovoltaic (PV). The traditional methods are failed to track the global maximum power point under partially shaded conditions (PSC), which decrease the reliability of the power system and increase the system losses. The research results of the CS algorithm and perturb and observe (P&O) algorithm are investigated for different cases of operations of PV panels under PSC. The proposed CS model can track the GMPP very accurate with high efficiency in less time under severe weather conditions as well as in PSC.
Режим доступа: по договору с организацией-держателем ресурса
DOI:10.1109/COMCAS44984.2019.8958112

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