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Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications
In this article, a multi-port non-isolated converter is implemented for renewable energy applications. High voltage gain is accomplished with a switched capacitor and coupled inductor, and power transfer between the inputs, battery, and load can be realized using three power switches. The power collected in the leakage inductance is reused to decrease the voltage stress on the power switch. Various functioning periods are also examined, and design requirements are offered. The proposed converter uses fewer parts to realize power flows and obtain high voltage gain compared to comparable converters. Additionally, under partial shading conditions, the traditional maximum power point tracking (MPPT) approaches are not able to collect the global maximum power point (MPP) from the numerous local MPPs. This work proposes an artificial neural-network-based MPPT technique with variable step size for tracing speed, MPP oscillations, and operating efficiency. The proposed converter experiment is also constructed and successfully tested in a laboratory environment.
Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications
In this article, a multi-port non-isolated converter is implemented for renewable energy applications. High voltage gain is accomplished with a switched capacitor and coupled inductor, and power transfer between the inputs, battery, and load can be realized using three power switches. The power collected in the leakage inductance is reused to decrease the voltage stress on the power switch. Various functioning periods are also examined, and design requirements are offered. The proposed converter uses fewer parts to realize power flows and obtain high voltage gain compared to comparable converters. Additionally, under partial shading conditions, the traditional maximum power point tracking (MPPT) approaches are not able to collect the global maximum power point (MPP) from the numerous local MPPs. This work proposes an artificial neural-network-based MPPT technique with variable step size for tracing speed, MPP oscillations, and operating efficiency. The proposed converter experiment is also constructed and successfully tested in a laboratory environment.
Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications
Belqasem Aljafari (Autor:in) / Gunapriya Devarajan (Autor:in) / Sivaranjani Subramani (Autor:in) / Subramaniyaswamy Vairavasundaram (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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