A comprehensive survey on aquila optimizer

B Sasmal, AG Hussien, A Das, KG Dhal - Archives of Computational …, 2023 - Springer
Aquila Optimizer (AO) is a well-known nature-inspired optimization algorithm (NIOA) that
was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population …

Brazilian wind energy generation potential using mixtures of Weibull distributions

FS dos Santos, KKF do Nascimento… - … and Sustainable Energy …, 2024 - Elsevier
As concerns about the greenhouse effect and the resulting increase in carbon dioxide levels
in the atmosphere continue to mount, there is an increasing need to curtail the use of fossil …

Mixed Skewness Probability Modeling and Extreme Value Predicting for Physical System Input/Output Based on Full Bayesian Generalized Maximum-Likelihood …

X Zhang, Y Ding, H Zhao, L Yi, T Guo… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Dynamic parameterization of the statistical characteristics of structural systems' measured
input and output data is an important task for the digital twin modeling and intelligent risk …

Mixture bivariate distribution of wind speed and air density for wind energy assessment

Z Yang, W Huang, S Dong, H Li - Energy Conversion and Management, 2023 - Elsevier
The probabilistic structures of wind speed and air density are indispensable for the wind
energy assessment. Note that the statistical patterns of these parameters might involve …

The mixture of probability distribution functions for wind and photovoltaic power systems using a metaheuristic method

AK Khamees, AY Abdelaziz, MR Eskaros, MA Attia… - Processes, 2022 - mdpi.com
The rising use of renewable energy sources, particularly those that are weather-dependent
like wind and solar energy, has increased the uncertainty of supply in these power systems …

[HTML][HTML] Wind power forecasting using optimized LSTM by attraction–repulsion optimization algorithm

MAA Al-qaness, AA Ewees, AO Aseeri… - Ain Shams Engineering …, 2024 - Elsevier
Wind power forecasting is crucial for energy conversion and management. This study
employs the long short-term memory (LSTM) network, a specialized form of recurrent neural …

Optimal power flow with stochastic renewable energy using three mixture component distribution functions

AK Khamees, AY Abdelaziz, MR Eskaros, MA Attia… - Sustainability, 2022 - mdpi.com
The growing usage of renewable energy sources, such as solar and wind energy, has
increased the electrical system's unpredictability. The stochastic behavior of these sources …

[HTML][HTML] A new probabilistic model with applications to the wind speed energy data sets

AS Alharthi - Alexandria Engineering Journal, 2024 - Elsevier
So far in the literature, the two-parameter Weibull distribution and its other extensions are
frequently implemented to analyze the wind speed energy data sets. However, based on our …

Nonparametric versus parametric (both unimodal and mixed) probability distribution in hourly wind speed modelling for some regions of Tamil Nadu state in India

N Natarajan, S Latif - Stochastic Environmental Research and Risk …, 2024 - Springer
It is crucial to accurately predict the probability distribution of long-term wind speed patterns
to evaluate the potential for wind energy. This could involve testing various probability …

[HTML][HTML] Generalized bivariate mixture model of directional wind speed in mixed wind climates

X Ji, J Zou, Z Cheng, G Huang, YG Zhao - Alexandria Engineering Journal, 2024 - Elsevier
Probabilistic modeling of the directional wind speed has been an important topic in the fields
of wind energy assessment as well as structural wind-resistant design. The mixture model is …