A review on hybrid empirical mode decomposition models for wind speed and wind power prediction
Reliable and accurate planning and scheduling of wind farms and power grids to ensure
sustainable use of wind energy can be better achieved with the use of precise and accurate …
sustainable use of wind energy can be better achieved with the use of precise and accurate …
A review of applications of artificial intelligent algorithms in wind farms
Wind farms are enormous and complex control systems. It is challenging and valuable to
control and optimize wind farms. Their applications are widely used in various industries …
control and optimize wind farms. Their applications are widely used in various industries …
Short-term offshore wind speed forecast by seasonal ARIMA-A comparison against GRU and LSTM
Offshore wind power is one of the fastest-growing energy sources worldwide, which is
environmentally friendly and economically competitive. Short-term time series wind speed …
environmentally friendly and economically competitive. Short-term time series wind speed …
Prediction of wind speed and wind direction using artificial neural network, support vector regression and adaptive neuro-fuzzy inference system
A Khosravi, RNN Koury, L Machado… - … Energy Technologies and …, 2018 - Elsevier
In this study, three models of machine learning algorithms are implemented to predict wind
speed, wind direction and output power of a wind turbine. The first model is multilayer feed …
speed, wind direction and output power of a wind turbine. The first model is multilayer feed …
Optimal day-ahead self-scheduling and operation of prosumer microgrids using hybrid machine learning-based weather and load forecasting
Prosumer microgrids (PMGs) are considered as active users in smart grids. These units are
able to generate and sell electricity to aggregators or neighbor consumers in the prosumer …
able to generate and sell electricity to aggregators or neighbor consumers in the prosumer …
Wind power forecasting based on echo state networks and long short-term memory
Wind power generation has presented an important development around the world.
However, its integration into electrical systems presents numerous challenges due to the …
However, its integration into electrical systems presents numerous challenges due to the …
Wind generation forecasting methods and proliferation of artificial neural network: A review of five years research trend
To sustain a clean environment by reducing fossil fuels-based energies and increasing the
integration of renewable-based energy sources, ie, wind and solar power, have become the …
integration of renewable-based energy sources, ie, wind and solar power, have become the …
[HTML][HTML] A survey of artificial intelligence methods for renewable energy forecasting: Methodologies and insights
The efforts to revolutionize electric power generation and produce clean and sustainable
electricity have led to the exploration of renewable energy systems (RES). This form of …
electricity have led to the exploration of renewable energy systems (RES). This form of …
Artificial intelligence in wind speed forecasting: A review
SM Valdivia-Bautista, JA Domínguez-Navarro… - Energies, 2023 - mdpi.com
Wind energy production has had accelerated growth in recent years, reaching an annual
increase of 17% in 2021. Wind speed plays a crucial role in the stability required for power …
increase of 17% in 2021. Wind speed plays a crucial role in the stability required for power …
Artificial Neural Network based computing model for wind speed prediction: A case study of Coimbatore, Tamil Nadu, India
The two main challenges of predicting the wind speed depend on various atmospheric
factors and random variables. This paper explores the possibility of developing a wind …
factors and random variables. This paper explores the possibility of developing a wind …