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 …
A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
[HTML][HTML] Time-series forecasting of seasonal items sales using machine learning–A comparative analysis
There has been a growing interest in the field of neural networks for prediction in recent
years. In this research, a public dataset including the sales history of a retail store is …
years. In this research, a public dataset including the sales history of a retail store is …
[HTML][HTML] Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach
An accurate solar energy forecast is of utmost importance to allow a higher level of
integration of renewable energy into the controls of the existing electricity grid. With the …
integration of renewable energy into the controls of the existing electricity grid. With the …
Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time
S Ayvaz, K Alpay - Expert Systems with Applications, 2021 - Elsevier
In this study, a data driven predictive maintenance system was developed for production
lines in manufacturing. By utilizing the data generated from IoT sensors in real-time, the …
lines in manufacturing. By utilizing the data generated from IoT sensors in real-time, the …
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …
resources planning and management. It is highly vital for hydropower operation, agricultural …
[HTML][HTML] Distributed energy systems: A review of classification, technologies, applications, and policies
The sustainable energy transition taking place in the 21st century requires a major
revamping of the energy sector. Improvements are required not only in terms of the …
revamping of the energy sector. Improvements are required not only in terms of the …
A review of machine learning applications in wildfire science and management
Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …
with early applications including neural networks and expert systems. Since then, the field …
A review on deep learning techniques for IoT data
Continuous growth in software, hardware and internet technology has enabled the growth of
internet-based sensor tools that provide physical world observations and data …
internet-based sensor tools that provide physical world observations and data …
Deep learning neural networks for short-term photovoltaic power forecasting
Accurate short-term forecasting of photovoltaic (PV) power is indispensable for controlling
and designing smart energy management systems for microgrids. In this paper, different …
and designing smart energy management systems for microgrids. In this paper, different …