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 …
On the influence of wind speed model resolution on the global technical wind energy potential
C Jung, D Schindler - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Previous estimations of the global technical onshore wind energy potential (WEP) range
between 64 and 690 PWh/yr. The diversity of WEP estimates is caused by various applied …
between 64 and 690 PWh/yr. The diversity of WEP estimates is caused by various applied …
Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM
H Liu, X Mi, Y Li - Energy Conversion and Management, 2018 - Elsevier
Accurate and robust wind speed forecasting is essential for the planning, scheduling and
maintenance of wind power. In this study, a novel wind speed multistep prediction model is …
maintenance of wind power. In this study, a novel wind speed multistep prediction model is …
Developed comparative analysis of metaheuristic optimization algorithms for optimal active control of structures
A developed comparative analysis of metaheuristic optimization algorithms has been used
for optimal active control of structures. The linear quadratic regulator (LQR) has ignored the …
for optimal active control of structures. The linear quadratic regulator (LQR) has ignored the …
Assessment of wind energy potential using wind energy conversion system
M Shoaib, I Siddiqui, S Rehman, S Khan… - Journal of cleaner …, 2019 - Elsevier
Wind energy, as a renewable resource, is the most rapidly growing source that produces
electrical energy using wind turbines. Such a wind energy conversion system is both …
electrical energy using wind turbines. Such a wind energy conversion system is both …
Soft computing based closed form equations correlating L and N-type Schmidt hammer rebound numbers of rocks
This paper reports the results of soft computing-based models correlating L and N-type
Schmidt hammer rebound numbers of rock. A data-independent database was compiled …
Schmidt hammer rebound numbers of rock. A data-independent database was compiled …
Wind turbine power output prediction using a new hybrid neuro-evolutionary method
Short-term wind power prediction is challenging due to the chaotic characteristics of wind
speed. Since, for wind power industries, designing an accurate and reliable wind power …
speed. Since, for wind power industries, designing an accurate and reliable wind power …
Performance improvement of empirical models for estimation of global solar radiation in India: A k-fold cross-validation approach
In this work, global solar radiation is estimated based on sunshine duration. Solar radiation
measurements have been collected from the Indian Meteorological Department (Pune …
measurements have been collected from the Indian Meteorological Department (Pune …
Prediction of hourly solar radiation in Abu Musa Island using machine learning algorithms
A Khosravi, RNN Koury, L Machado… - Journal of Cleaner …, 2018 - Elsevier
Accurate forecasting of renewable energy sources plays a key role in their integration into
the grid. This study proposes machine learning algorithms to predict the hourly solar …
the grid. This study proposes machine learning algorithms to predict the hourly solar …
A novel deep learning ensemble model with data denoising for short-term wind speed forecasting
Wind speed forecasting plays a pivotal role in the security and economy of the power system
operation. However, accurate prediction on the wind speed value is still quite challenging …
operation. However, accurate prediction on the wind speed value is still quite challenging …