Loading…

Hierarchical Optimization and Grid Scheduling Model for Energy Internet: A Genetic Algorithm-Based Layered Approach

The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction. Energy Internet, as a core technology of the third industrial revo...

Full description

Saved in:
Bibliographic Details
Published in:Frontiers in energy research 2022-07, Vol.10
Main Authors: Lin, Lihua, Abdallah, Abdallah, Ishak, Mohamad Khairi, Ali, Ziad M., Khan, Imran, Rabie, Khaled, Safak Bayram, Islam, Li, Xingwang, Madsen, Dag Øivind, Kim, Ki-Il
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction. Energy Internet, as a core technology of the third industrial revolution, aims to combine renewable energy and Internet technology to promote the large-scale use and sharing of distributed renewable energy as well as the integration of multiple complex network systems, such as electricity, transportation, and natural gas. This novel technology enables power networks to save energy. However, multienergy synchronization optimization poses a significant problem. As a solution, this study proposed an optimized approach based on the concept of layered control–collaborate optimization. The proposed method allows the distributed device to plan the heat, cold, gas, and electricity in the regional system in the most efficient way possible. Moreover, the proposed optimization model is simulated using a real-number genetic algorithm. It improved the optimal scheduling between different regions and the independence of distributed equipment with minimal cost. Furthermore, the inverse system and energy and cost saving rate of the proposed method are better than those of existing methods, which prove its effectiveness.
ISSN:2296-598X
2296-598X
DOI:10.3389/fenrg.2022.921411