Wind Power Forecasting Model Based on Extreme Learning Machine and Time series

Mansoury, Ibtissame; Bourakadi, Dounia El; Yahyaouy, Ali; Boumhidi, Jaouad

doi:10.1109/icds53782.2021.9626737

2021 Fifth International Conference on Intelligent Computing in Data Sciences (ICDS) 2021

DOI: 10.1109/icds53782.2021.9626737

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Wind Power Forecasting Model Based on Extreme Learning Machine and Time series

Ibtissame Mansoury

Dounia El Bourakadi

Ali Yahyaouy

et al.

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2024

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Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods

Teixeira,

Cerveira,

Pires

et al. 2024

Energies

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Socioeconomic growth and population increase are driving a constant global demand for energy. Renewable energy is emerging as a leading solution to minimise the use of fossil fuels. However, renewable resources are characterised by significant intermittency and unpredictability, which impact their energy production and integration into the power grid. Forecasting models are increasingly being developed to address these challenges and have become crucial as renewable energy sources are integrated in energy systems. In this paper, a comparative analysis of forecasting methods for renewable energy production is developed, focusing on photovoltaic and wind power. A review of state-of-the-art techniques is conducted to synthesise and categorise different forecasting models, taking into account climatic variables, optimisation algorithms, pre-processing techniques, and various forecasting horizons. By integrating diverse techniques such as optimisation algorithms and pre-processing methods and carefully selecting the forecast horizon, it is possible to highlight the accuracy and stability of forecasts. Overall, the ongoing development and refinement of forecasting methods are crucial to achieve a sustainable and reliable energy future.

show abstract

Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods

Teixeira,

Cerveira,

Pires

et al. 2024

Energies

View full text Add to dashboard Cite

show abstract

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Wind Power Forecasting Model Based on Extreme Learning Machine and Time series

Cited by 1 publication

References 18 publications

Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods

Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods

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