An optimal control method considering degradation and economy based on mutual learn salp swarm algorithm of an islanded zero‐carbon DC microgrid
Abstract Due to the energy storage lifetime effects of the power allocation, there is a large space to improve the economy of the electric‐hydrogen hybrid DC microgrid. This paper provides an optimal control method based on the mutual learn salp swarm algorithm (MLSSA) in real‐time, which aims to en...
Saved in:
Main Authors: | Ying Han, Yujing Hou, Luoyi Li, Weifeng Meng, Qi Li, Weirong Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2024-12-01
|
Series: | IET Renewable Power Generation |
Subjects: | |
Online Access: | https://doi.org/10.1049/rpg2.13012 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Hybrid Renewable Sources Implementation for a DC Microgrid with Flatness-Nonlinear Control to Achieve Efficient Energy Management Strategy
by: Furqan A. Abbas, et al.
Published: (2023-12-01) -
A Near-Zero Energy Smart Greenhouse Integrated Into a Microgrid for Sustainable Energy and Microclimate Management
by: Tuan Minh Tran, et al.
Published: (2025-01-01) -
Adaptive identification of critical nodes for fault‐on voltage support in islanded microgrids
by: Shiran Cao, et al.
Published: (2024-12-01) -
Cybersecurity in microgrids: A review on advanced techniques and practical implementation of resilient energy systems
by: Ijaz Ahmed, et al.
Published: (2025-03-01) -
Microgrid energy management strategy considering source-load forecast error
by: Kaikai Zhang, et al.
Published: (2025-03-01)