Modeling / Optimization and Effect of Environmental Variables on Energy Production Based on PV / Wind Turbine Hybrid System

Alayi, Reza; Velayti, Javad Javad

doi:10.26555/jiteki.v7i1.20515

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…In ref. [17], the authors focus on performing a sensitivity analysis of renewable energy sources, with a specific focus on wind and solar power. The goal is to determine their impact on the costs associated with hybrid power plants in the Kermanshah region.…”

Section: Review Of Related Workmentioning

confidence: 99%

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

Abdelwahab,

El-Rifaie,

Hegazy

et al. 2024

Sensors

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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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Section: Review Of Related Workmentioning

confidence: 99%

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

Abdelwahab,

El-Rifaie,

Hegazy

et al. 2024

Sensors

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“…), multiple hybrid energy system (HES) methods may be chosen for that kind of location [17][18][19][20]. Various renewable technologies including wind turbines, fuel cells, and photovoltaics [21][22][23] could be combined to create a hybrid power system. Consequently, the wind, photovoltaic, and fuel-cell hybrid combination is a brand-new renewable resource.…”

Section: Introductionmentioning

confidence: 99%

Comparative Investigation of On-Grid and Off-Grid Hybrid Energy System for a Remote Area in District Jamshoro of Sindh, Pakistan

et al. 2023

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To meet electricity requirements and provide a long-term, sustainable existence, remote areas need to promote renewable projects. Most of the time, wind and solar power sources are selected as renewable energy technologies to help satisfy some of the power requirements. Alternative approaches should be employed, considering the inconsistent characteristics among those resources, to offer efficient and long-lasting responses. Electricity production needs to be conducted with the help of a wide range of energy sources to be productive and efficient. As a result, the current research concentrates on feasible analyses of interconnected hybrid energy systems for such remote residential electricity supply. To help a remote area’s establishment decide whether to adopt renewable electricity technology, this paper evaluates the techno-economic effectiveness of grid-connected and standalone integrated hybrid energy systems. The electricity requirements for the entire selected remote area were determined first. Furthermore, the National Aeronautics and Space Administration, a national renewable energy laboratory, was used to evaluate the possibilities of green energy supplies. A thorough survey was performed to determine which parts were needed to simulate the interconnected hybrid energy systems. Employing the HOMER program, we conducted a simulation, optimizations, and economic research. Considering the net present cost, cost of energy, and compensation time, an economic comparison was made between the evaluated integrated hybrid systems. The assessment reveals that perhaps the grid-connected hybrid energy system is the best option for reliably satisfying remote areas’ energy needs.

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“…Wind energy is considered a renewable energy source that responds to the increasing demand for energy [6]. Producing electricity with environmental concerns at an affordable price has become a key challenge [7,8]. Because of their many advantages, the technology of variable speed wind power generation has become a research hotspot in this field [9,10].…”

Section: Introductionmentioning

confidence: 99%

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2023

Journal of Robotics and Control

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In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm 𝑃𝑂 and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control. This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.

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Modeling / Optimization and Effect of Environmental Variables on Energy Production Based on PV / Wind Turbine Hybrid System

Cited by 10 publications

References 16 publications

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

Comparative Investigation of On-Grid and Off-Grid Hybrid Energy System for a Remote Area in District Jamshoro of Sindh, Pakistan

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

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