.png){kind=icon}
.png){kind=icon}
Return
A Novel Graph-Based Routing Algorithm in Residential Multimicrogrid Systems
.png){kind=icon}
PRE
AI
DOI：10.1109/TII.2020.2997516.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The complementary energy exchange between residential microgrids aims at decreasing the dependence on the main grid, reducing the size and cost of the energy storage units, and increasing energy efficiency. In this regard, the use of a power router interface to connect the microgrids to the power system is necessary for controlling bidirectional power and data flow, which will build the core of the future Energy Internet. In fact, the power router is served as an energy exchange center that enables energy flow between microgrids. One of the most important factors in determining multimicrogrid system performance is the energy routing algorithm strategy. In this article, a new routing algorithm is proposed based on the graph theory. The objective of the proposed algorithm is to minimize the overall power losses with respect to congestion and reliability. Therefore, the best set of loads, optimal sources, and no-congestion minimum loss paths are determined. Various analysis cases have been investigated to confirm the performance and flexibility of the proposed algorithm. A novel case study with multisources and multiloads is addressed, which has not been previously analyzed with the application of power routers. In addition, the developed algorithm is compared with other existing algorithms in terms of power loss minimization, different scenarios, congestion management, computation time, and complexity.
Keywords:
Routing
Microgrids
Informatics
Peer-to-peer computing
Graph theory
Electronic mail
Energy storage
Energy Internet (EI)
graph theory
power losses
power router (PR)
routing algorithm
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.9
Papers:
8.3K
Citations:
6.0W
View more organizations