Load Forecasting Techniques and Their Applications in Smart Grids
Military Technical College · Qatar University · +4 more institutions
Abstract
The growing success of smart grids (SGs) is driving increased interest in load forecasting (LF) as accurate predictions of energy demand are crucial for ensuring the reliability, stability, and efficiency of SGs. LF techniques aid SGs in making decisions related to power operation and planning upgrades, and can help provide efficient and reliable power services at fair prices. Advances in artificial intelligence (AI), specifically in machine learning (ML) and deep learning (DL), have also played a significant role in improving the precision of demand forecasting. It is important to evaluate different LF techniques to identify the most accurate and appropriate one for use in SGs. This paper conducts a…
Citation impact
- FWCI
- 25.03
- Percentile
- 100%
- References
- 115
Authors
5Topics & keywords
- Computer science
- Mean absolute percentage error
- Reliability (semiconductor)
- Cluster analysis
- Artificial neural network
- Mean squared error
- Artificial intelligence
- Smart grid
- Affordable and clean energy