A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …
renewable energy sources (RESs), energy storage devices, and load management …
Realization of sustainable development goals with disruptive technologies by integrating industry 5.0, society 5.0, smart cities and villages
Significant changes in society were emphasized as being required to achieve Sustainable
Development Goals, a need which was further intensified with the emergence of the …
Development Goals, a need which was further intensified with the emergence of the …
Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm
It is hard to predict wind power with high-precision due to its non-stationary and stochastic
nature. The wind power has developed rapidly around the world as a promising renewable …
nature. The wind power has developed rapidly around the world as a promising renewable …
Load forecasting techniques for power system: Research challenges and survey
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …
think tank of power sectors should forecast the future need of electricity with large accuracy …
Evolutionary quantile regression gated recurrent unit network based on variational mode decomposition, improved whale optimization algorithm for probabilistic short …
C Zhang, C Ji, L Hua, H Ma, MS Nazir, T Peng - Renewable Energy, 2022 - Elsevier
Wind energy, as clean energy, has attracted more and more attention. Wind power
generation is easily threatened by the irregular fluctuation of wind speed, which interferes …
generation is easily threatened by the irregular fluctuation of wind speed, which interferes …
Planning of distributed renewable energy systems under uncertainty based on statistical machine learning
X Fu, X Wu, C Zhang, S Fan… - Protection and Control of …, 2022 - ieeexplore.ieee.org
The development of distributed renewable energy, such as photovoltaic power and wind
power generation, makes the energy system cleaner, and is of great significance in reducing …
power generation, makes the energy system cleaner, and is of great significance in reducing …
[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 …
Short-term wind power prediction based on EEMD–LASSO–QRNN model
Y He, Y Wang - Applied Soft Computing, 2021 - Elsevier
With the increasing utilization of wind generation in power system, the improvement of wind
power forecasting precision is attached vital importance. Owing to the stochastic and …
power forecasting precision is attached vital importance. Owing to the stochastic and …
Forecasting carbon prices based on real-time decomposition and causal temporal convolutional networks
Recently, global attention has been paid to climate change. On this account, the market-
based carbon pricing scheme is developed to limit greenhouse gas emissions, where a …
based carbon pricing scheme is developed to limit greenhouse gas emissions, where a …
Neural network-based uncertainty quantification: A survey of methodologies and applications
Uncertainty quantification plays a critical role in the process of decision making and
optimization in many fields of science and engineering. The field has gained an …
optimization in many fields of science and engineering. The field has gained an …