A survey of artificial neural network in wind energy systems
Wind energy has become one of the most important forms of renewable energy. Wind
energy conversion systems are more sophisticated and new approaches are required based …
energy conversion systems are more sophisticated and new approaches are required based …
Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …
processes in science and engineering. In the current review, we focus on the applications of …
A combined forecasting system based on statistical method, artificial neural networks, and deep learning methods for short-term wind speed forecasting
Wind speed forecasting is gaining importance as the share of wind energy in electricity
systems increases. Numerous forecasting approaches have been used to predict wind …
systems increases. Numerous forecasting approaches have been used to predict wind …
Near real-time wind speed forecast model with bidirectional LSTM networks
Wind is an important source of renewable energy, often used to provide clean electricity to
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
Boosted GRU model for short-term forecasting of wind power with feature-weighted principal component analysis
Wind power is a clean resource that is widely used as a renewable energy source. Accurate
wind power forecasting is important for the efficient and stable use of wind energy. The …
wind power forecasting is important for the efficient and stable use of wind energy. The …
A short-term wind speed prediction method utilizing novel hybrid deep learning algorithms to correct numerical weather forecasting
The accuracy of the wind speed prediction is of crucial significance for the operation and
dispatch of the power grid system reasonably. However, wind speed is so random and …
dispatch of the power grid system reasonably. However, wind speed is so random and …
Deep belief network based deterministic and probabilistic wind speed forecasting approach
With the rapid growth of wind power penetration into modern power grids, wind speed
forecasting (WSF) plays an increasingly significant role in the planning and operation of …
forecasting (WSF) plays an increasingly significant role in the planning and operation of …
A wind speed correction method based on modified hidden Markov model for enhancing wind power forecast
Short-term wind power forecast (WPF) depends highly on the wind speed forecast (WSF),
which is the prime contributor to the forecasting error. To achieve more accurate WPF …
which is the prime contributor to the forecasting error. To achieve more accurate WPF …
Renewable energy: Present research and future scope of Artificial Intelligence
SK Jha, J Bilalovic, A Jha, N Patel, H Zhang - Renewable and Sustainable …, 2017 - Elsevier
The existence of sunlight, air and other resources on earth must be used in an appropriate
way for human welfare while still protecting the environment and its living creatures. The …
way for human welfare while still protecting the environment and its living creatures. The …
A review of combined approaches for prediction of short-term wind speed and power
A Tascikaraoglu, M Uzunoglu - Renewable and Sustainable Energy …, 2014 - Elsevier
With the continuous increase of wind power penetration in power systems, the problems
caused by the volatile nature of wind speed and its occurrence in the system operations …
caused by the volatile nature of wind speed and its occurrence in the system operations …