Application of support vector machine models for forecasting solar and wind energy resources: A review
Conventional fossil fuels are depleting daily due to the growing human population. Previous
research has proved that renewable energy sources, especially solar and wind, can be …
research has proved that renewable energy sources, especially solar and wind, can be …
Short-term wind power forecasting approach based on Seq2Seq model using NWP data
Y Zhang, Y Li, G Zhang - Energy, 2020 - Elsevier
Wind power is one of the main sources of renewable energy. Precise forecast of the power
output of wind farms could greatly decrease the negative impact of wind power on power …
output of wind farms could greatly decrease the negative impact of wind power on power …
Spatio-temporal graph deep neural network for short-term wind speed forecasting
M Khodayar, J Wang - IEEE Transactions on Sustainable …, 2018 - ieeexplore.ieee.org
Wind speed forecasting is still a challenge due to the stochastic and highly varying
characteristics of wind. In this paper, a graph deep learning model is proposed to learn the …
characteristics of wind. In this paper, a graph deep learning model is proposed to learn the …
Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian …
M Sharifzadeh, A Sikinioti-Lock, N Shah - Renewable and Sustainable …, 2019 - Elsevier
Renewable energy from wind and solar resources can contribute significantly to the
decarbonisation of the conventionally fossil-driven electricity grid. However, their seamless …
decarbonisation of the conventionally fossil-driven electricity grid. However, their seamless …
Short-term self-scheduling of virtual energy hub plant within thermal energy market
M Jadidbonab, B Mohammadi-Ivatloo… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Multicarrier energy systems create new challenges as well as opportunities in future energy
systems. One of these challenges is the interaction among multiple energy systems and …
systems. One of these challenges is the interaction among multiple energy systems and …
Comparing support vector regression for PV power forecasting to a physical modeling approach using measurement, numerical weather prediction, and cloud motion …
The growth of installed photovoltaic (PV) power capacity in recent years has emerged an
increasing interest in high quality forecasts. The most common ways to predict PV power …
increasing interest in high quality forecasts. The most common ways to predict PV power …
[图书][B] Dimensionality reduction with unsupervised nearest neighbors
O Kramer - 2013 - Springer
The growing information infrastructure in a variety of disciplines involves an increasing
requirement for efficient data mining techniques. Fast dimensionality reduction methods are …
requirement for efficient data mining techniques. Fast dimensionality reduction methods are …
[HTML][HTML] Short-term wind power prediction method based on deep clustering-improved Temporal Convolutional Network
Y Sheng, H Wang, J Yan, Y Liu, S Han - Energy Reports, 2023 - Elsevier
Carbon neutrality has become the global consensus, and wind power is one of the key
technologies to achieve carbon neutrality in the power system. However, the randomness …
technologies to achieve carbon neutrality in the power system. However, the randomness …
Mixformer: Mixture transformer with hierarchical context for spatio-temporal wind speed forecasting
Wind energy has attracted more and more attention due to its sustainability and pollution-
free nature. As wind energy is highly dependent on wind speed, wind speed forecasting is of …
free nature. As wind energy is highly dependent on wind speed, wind speed forecasting is of …
An ensemble approach for multi-step ahead energy forecasting of household communities
AM Pirbazari, E Sharma, A Chakravorty… - IEEE …, 2021 - ieeexplore.ieee.org
This paper addresses the estimation of household communities' overall energy usage and
solar energy production, considering different prediction horizons. Forecasting the electricity …
solar energy production, considering different prediction horizons. Forecasting the electricity …