UAV-assited Wireless Powered Sensor Network over Rician Shadowed Fading Channels / S. Panich, T. D. Ponnimbaduge Perera, D. N. K. Dzhayakodi (Jayakody) Arachshiladzh [et al.]

Альтернативный автор-лицо: Panich, S., specialist in the field of informatics and computer technology, Researcher at Tomsk Polytechnic University, Ph.D, 1983-, Stefan;Ponnimbaduge Perera, T. D., programmer, Research Engineer of Tomsk Polytechnic University, 1990-, Tarindu Dilshan;Dzhayakodi (Jayakody) Arachshiladzh, D. N. K., specialist in the field of electronics, Professor of Tomsk Polytechnic University, 1983-, Dushanta Nalin Kumara;Stefanovic, C., Caslav;Prlincevic, B., BojanКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет, Инженерная школа информационных технологий и робототехники, Научно-образовательный центр "Автоматизация и информационные технологии"Язык: английский.Резюме или реферат: 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..Примечания о наличии в документе библиографии/указателя: [References: 18 tit.].Аудитория: .Тематика: 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 Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: 18 tit.]

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.

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