The Joukowsky rotor for diffuser augmented wind turbines: design and analysis

Bontempo, R.; Manna, M.

doi:10.1016/j.enconman.2021.114952

Cited by 13 publications

(3 citation statements)

References 45 publications

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“…Moreover, the maximum-power-coefficient/tip-speed-ratio characteristic curve for a diffuser augmented wind turbine has been derived for the first time. Finally, taking into full account the mutual influence of the disk and duct, a new rotor design strategy, capable to evaluate the optimum distribution of the chord and pitch-angle along the blade span, has also been proposed [ 22].…”

Section: Wind Turbines and Propellersmentioning

confidence: 99%

Fluid Machinery, Energy Systems and Power Generation

Manna,

Senatore

2024

Springer Aerospace Technology

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Section: Wind Turbines and Propellersmentioning

confidence: 99%

Fluid Machinery, Energy Systems and Power Generation

Manna,

Senatore

2024

Springer Aerospace Technology

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“…The tip angle, the design of the blades, and the relationship between wind speed and rotor speed are the factors that come into play when calculating the Cp for a certain turbine. The maximum 10.3389/fenrg.2023.1220085 power coefficient, often known as the Betz limit, is 0.593 (Bontempo and Manna, 2022). However, it is not possible to obtain this value in actual practice.…”

Section: Problem Statementmentioning

confidence: 99%

“…It was not possible to obtain the power coefficient under a variety of different operating situations. The number 0.5 was utilized for the majority of the practical computations (Bontempo and Manna, 2022). One of the most influential aspects of the wind turbine's output is the air density.…”

Section: Problem Statementmentioning

confidence: 99%

Forecasting wind power based on an improved al-Biruni Earth radius metaheuristic optimization algorithm

Saeed¹,

Ibrahim²,

El-kenawy³

et al. 2023

Front. Energy Res.

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Wind power forecasting is pivotal in optimizing renewable energy generation and grid stability. This paper presents a groundbreaking optimization algorithm to enhance wind power forecasting through an improved al-Biruni Earth radius (BER) metaheuristic optimization algorithm. The BER algorithm, based on stochastic fractal search (SFS) principles, has been refined and optimized to achieve superior accuracy in wind power prediction. The proposed algorithm is denoted by BERSFS and is used in an ensemble model’s feature selection and optimization to boost prediction accuracy. In the experiments, the first scenario covers the proposed binary BERSFS algorithm’s feature selection capabilities for the dataset under test, while the second scenario demonstrates the algorithm’s regression capabilities. The BERSFS algorithm is investigated and compared to state-of-the-art algorithms of BER, SFS, particle swarm optimization, gray wolf optimizer, and whale optimization algorithm. The proposed optimizing ensemble BERSFS-based model is also compared to the basic models of long short-term memory, bidirectional long short-term memory, gated recurrent unit, and the k-nearest neighbor ensemble model. The statistical investigation utilized Wilcoxon’s rank-sum and analysis of variance tests to investigate the robustness of the created BERSFS-based model. The achieved results and analysis confirm the effectiveness and superiority of the proposed approach in wind power forecasting.

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