Enhancing Smart Grids for Sustainable Energy Transition and Emission Reduction with Advanced Forecasting Techniques
Smart grids are modernized, intelligent electricity distribution systems that integrate information and communication technologies to improve the efficiency, reliability, and sustainability of the electricity network. However, existing smart grids only integrate renewable energies when it comes to a...
Saved in:
Main Author: | Farah Rania, Farou Brahim, Kouahla Zineddine and Seridi Hamid |
---|---|
Format: | Article |
Language: | English |
Published: |
Technoscience Publications
2024-12-01
|
Series: | Nature Environment and Pollution Technology |
Subjects: | |
Online Access: | https://neptjournal.com/upload-images/(18)D-1625.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adversarial Attack Detection in Smart Grids Using Deep Learning Architectures
by: Stephanie Ness
Published: (2025-01-01) -
Forecasting consumption of electric energy by using wavelet transform
by: V. I. Skorokhodov, et al.
Published: (2021-06-01) -
UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data
by: Shiyang Zhou, et al.
Published: (2025-02-01) -
Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon
by: Abhishu Oza, et al.
Published: (2025-01-01) -
A deep reinforcement learning-based approach for cyber resilient demand response optimization
by: Ayush Sinha, et al.
Published: (2025-01-01)