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Optimal Control and Optimization of Grid-Connected PV and Wind Turbine Hybrid Systems Using Electric Eel Foraging Optimization Algorithms.
Abdelwahab, Saad A Mohamed; El-Rifaie, Ali M; Hegazy, Hossam Youssef; Tolba, Mohamed A; Mohamed, Wael I; Mohamed, Moayed.
Afiliación
  • Abdelwahab SAM; Electrical Department, Faculty of Technology and Education, Suez University, Suez 43221, Egypt.
  • El-Rifaie AM; College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.
  • Hegazy HY; Electrical Department, Faculty of Technology and Education, Helwan University, Helwan 11795, Egypt.
  • Tolba MA; Reactors Department, Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo 11787, Egypt.
  • Mohamed WI; Electrical Department, Faculty of Technology and Education, Helwan University, Helwan 11795, Egypt.
  • Mohamed M; Electrical Department, Faculty of Technology and Education, Sohag University, Sohag 82524, Egypt.
Sensors (Basel) ; 24(7)2024 Apr 07.
Article en En | MEDLINE | ID: mdl-38610565
ABSTRACT
This paper presents a comprehensive exploration of a hybrid energy system that integrates wind turbines with photovoltaics (PVs) to address the intermittent nature of electricity production from these sources. The necessity for such technology arises from the sporadic nature of electricity generated by PV cells and wind turbines. The envisioned outcome is an emissions-free, more efficient alternative to traditional energy sources. A variety of optimization techniques are utilized, specifically the Particle Swarm Optimization (PSO) algorithm and Electric Eel Foraging Optimization (EEFO), to achieve optimal power regulation and seamless integration with the public grid, as well as to mitigate anticipated loading issues. The employed mathematical modeling and simulation techniques are used to assess the effectiveness of EEFO in optimizing the operation of grid-connected PV and wind turbine hybrid systems. In this paper, the optimization methods applied to the system's architecture are described in detail, providing a clear understanding of the intricate nature of the approach. The efficacy of these optimization strategies is rigorously evaluated through simulations of diverse operating scenarios using MATLAB/SIMULINK. The results demonstrate that the proposed optimization strategies are not only capable of precisely and swiftly compensating for linked loads, but also effectively controlling the energy supply to maintain the load's power at the desired level. The findings underscore the potential of this hybrid energy system to offer a sustainable and reliable solution for meeting power demands, contributing to the advancement of clean and efficient energy technologies. The results demonstrate the capability of the proposed approach to improve system performance, maximize energy yield, and enhance grid integration, thereby contributing to the advancement of renewable energy technologies and sustainable energy systems.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Egipto Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Egipto Pais de publicación: Suiza