Design and optimization of distributed energy management system based on edge computing and machine learning
Abstract With the continuous growth of global energy demand and the rapid development of renewable energy, traditional energy management systems are facing enormous challenges, especially in the scheduling and optimization of distributed energy. In order to meet these challenges, edge computing and...
Saved in:
Main Authors: | Nan Feng, Conglin Ran |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2025-02-01
|
Series: | Energy Informatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s42162-025-00471-2 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Energy-Efficient Distributed Edge Computing to Assist Dense Internet of Things
by: Sumaiah Algarni, et al.
Published: (2025-01-01) -
Elastic Optimization for Stragglers in Edge Federated Learning
by: Khadija Sultana, et al.
Published: (2023-12-01) -
Design a Robust DDoS Attack Detection and Mitigation Scheme in SDN-Edge-IoT by Leveraging Machine Learning
by: Habtamu Molla Belachew, et al.
Published: (2025-01-01) -
Optimal dispatch of distributed renewable energy and energy storage systems via optimal configuration of mobile edge computing
by: He Jiang, et al.
Published: (2024-12-01) -
Minimizing Delay and Power Consumption at the Edge
by: Erol Gelenbe
Published: (2025-01-01)