A review of wind speed and wind power forecasting with deep neural networks
The use of wind power, a pollution-free and renewable form of energy, to generate electricity
has attracted increasing attention. However, intermittent electricity generation resulting from …
has attracted increasing attention. However, intermittent electricity generation resulting from …
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 …
Application of hybrid model based on empirical mode decomposition, novel recurrent neural networks and the ARIMA to wind speed prediction
MD Liu, L Ding, YL Bai - Energy Conversion and Management, 2021 - Elsevier
Wind speed is the key factor of wind power generation. With the increase of the proportion of
wind power generation in total power generation, the accurate prediction of wind speeds …
wind power generation in total power generation, the accurate prediction of wind speeds …
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy storage
D Rangel-Martinez, KDP Nigam… - … Research and Design, 2021 - Elsevier
This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …
manufacturing sectors that have a considerable impact on sustainability and the …
Network topology optimisation based on dynamic thermal rating and battery storage systems for improved wind penetration and reliability
The nonflexible operations of transmission networks with high load demand and wind power
increase the likelihood of power congestions and deteriorate grid reliability. This condition …
increase the likelihood of power congestions and deteriorate grid reliability. This condition …
Wind power forecasting using attention-based gated recurrent unit network
Wind power forecasting (WPF) plays an increasingly essential role in power system
operations. So far, most forecasting models have focused on a single-step-ahead WPF, and …
operations. So far, most forecasting models have focused on a single-step-ahead WPF, and …
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …
operations due to its strong randomness and volatility. These issues can be resolved via …
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 …
Data processing strategies in wind energy forecasting models and applications: A comprehensive review
H Liu, C Chen - Applied Energy, 2019 - Elsevier
Given the intermittent nature of the wind, accurate wind energy forecasting is significant to
the proper utilization of renewable energy sources. In recent years, data-driven models …
the proper utilization of renewable energy sources. In recent years, data-driven models …