[HTML][HTML] An overview of performance evaluation metrics for short-term statistical wind power forecasting
Wind power forecasting has become an essential tool for energy trading and the operation
of the grid due to the increasing importance of wind energy. Therefore, estimating the …
of the grid due to the increasing importance of wind energy. Therefore, estimating the …
Bayesian network modelling for the wind energy industry: An overview
T Adedipe, M Shafiee, E Zio - Reliability Engineering & System Safety, 2020 - Elsevier
Wind energy farms are moving into deeper and more remote waters to benefit from
availability of more space for the installation of wind turbines as well as higher wind speed …
availability of more space for the installation of wind turbines as well as higher wind speed …
A hybrid deep learning-based neural network for 24-h ahead wind power forecasting
YY Hong, CLPP Rioflorido - Applied Energy, 2019 - Elsevier
Wind power generation is always associated with uncertainties as a result of fluctuations of
wind speed. Accurate predictions of wind power generation are important for the efficient …
wind speed. Accurate predictions of wind power generation are important for the efficient …
Ensemble wind speed forecasting with multi-objective Archimedes optimization algorithm and sub-model selection
Wind energy is becoming increasingly competitive and promising for renewable energy
profiles. Accurate and reliable wind speed prediction is crucial for the effective exploitation of …
profiles. Accurate and reliable wind speed prediction is crucial for the effective exploitation of …
A data-driven deep sequence-to-sequence long-short memory method along with a gated recurrent neural network for wind power forecasting
Large amounts of wind power generation have an impact not only on energy markets but
also on wholesale and retail market designs. Simultaneously, technological issues arise as …
also on wholesale and retail market designs. Simultaneously, technological issues arise as …
A novel ensemble model based on artificial intelligence and mixed-frequency techniques for wind speed forecasting
Wind speed forecasting is of prime importance for wind power generation, which can bring
tremendous economic, social and environmental benefits. However, previous wind speed …
tremendous economic, social and environmental benefits. However, previous wind speed …
Deep-based conditional probability density function forecasting of residential loads
This paper proposes a direct model for conditional probability density forecasting of
residential loads, based on a deep mixture network. Probabilistic residential load forecasting …
residential loads, based on a deep mixture network. Probabilistic residential load forecasting …
Transfer learning based multi-layer extreme learning machine for probabilistic wind power forecasting
Y Liu, J Wang - Applied Energy, 2022 - Elsevier
With the increasing penetration of wind power, probabilistic forecasting becomes critical to
quantifying wind power uncertainties and guiding power system operations. This paper …
quantifying wind power uncertainties and guiding power system operations. This paper …
Wind power prediction based on LSTM networks and nonparametric kernel density estimation
B Zhou, X Ma, Y Luo, D Yang - Ieee Access, 2019 - ieeexplore.ieee.org
Wind energy is a kind of sustainable energy with strong uncertainty. With a large amount of
wind power injected into the power grid, it will inevitably affect the security, stability and …
wind power injected into the power grid, it will inevitably affect the security, stability and …
Multi-source and temporal attention network for probabilistic wind power prediction
H Zhang, J Yan, Y Liu, Y Gao, S Han… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The temporal dependencies of wind power are significant to be involved in the modeling of
short-term wind power forecasts. However, different time series inputs will contribute …
short-term wind power forecasts. However, different time series inputs will contribute …