Optimal Control and Optimization of Grid-Connected PV and Wind Turbine Hybrid Systems Using Electric Eel Foraging Optimization Algorithms

Optimal Control and Optimization of Grid-Connected PV and Wind Turbine Hybrid Systems Using Electric Eel Foraging Optimization Algorithms

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...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 24; no. 7; p. 2354
Main Authors: Abdelwahab, Saad A Mohamed, El-Rifaie, Ali M, Hegazy, Hossam Youssef, Tolba, Mohamed A, Mohamed, Wael I, Mohamed, Moayed
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 01-04-2024
Subjects:
Air-turbines
Algorithms
Alternative energy sources
Analysis
Cost control
Eels
Electric Eel Foraging Optimization
Energy resources
Energy storage
Fossil fuels
Green technology
Greenhouse gases
hybrid PV and wind turbine
Mathematical optimization
Optimization algorithms
Optimization techniques
Pareto optimum
Particle Swarm Optimization
Power supply
Renewable resources
Solar energy
Turbines
Wind power
Egypt
Electric Eel Foraging Optimization
Particle Swarm Optimization
hybrid PV and wind turbine
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Summary: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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ISSN:1424-8220
1424-8220
DOI:10.3390/s24072354