Application of four machine-learning methods to predict short-horizon wind energy-Reference-Cited by-同舟云学术

Application of four machine-learning methods to predict short-horizon wind energy

Published:2023-12 Issue:6 Volume:6 Page:726-737
ISSN:2096-5117
Container-title:Global Energy Interconnection
language:en
Short-container-title:Global Energy Interconnection

Author:

Bouabdallaoui Doha,Haidi Touria,Elmariami Faissal,Derri Mounir,Mellouli El Mehdi

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Automotive Engineering,Renewable Energy, Sustainability and the Environment,Control and Systems Engineering

Reference50 articles.

1. Advanced green technologies toward future sustainable energy systems;Aziz;Indones. J. Sci. Technol.,2019

2. State of wind energy in the world: evolution, impacts and perspectives;Haidi;Int. J. Technical Phys. Probl. Eng.,2022

3. Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges;Lu;Appl. Energy,2021

4. Forecasting method of monthly wind power generation based on climate model and long short-term memory neural network;Yin;Global Energy Interconnection,2020

5. Estimating the output power and wind speed with ML methods: a case study in Texas;Malakouti;Case Stud. Chem. Environ. Eng.,2023

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Combination of Metaheuristic Algorithm and Artificial Neural Networks Model to Forecast Wind Energy;2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET);2024-05-16

2. An Enhanced Adaptive Integral Derivative Sliding Mode Control for Photovoltaic Systems in Rapidly Changing Irradiation Environments;2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET);2024-05-16

3. Key players in renewable energy and artificial intelligence research;EAI Endorsed Transactions on Energy Web;2024-02-22