Hierarchical distributed scheme for demand estimation and power reallocation in a future power grid

Hu, X, Zhou, H, Liu, Z, Yu, X and Li, C 2017, 'Hierarchical distributed scheme for demand estimation and power reallocation in a future power grid', IEEE Transactions on Industrial Informatics, vol. 13, no. 5, pp. 2279-2290.


Document type: Journal Article
Collection: Journal Articles

Title Hierarchical distributed scheme for demand estimation and power reallocation in a future power grid
Author(s) Hu, X
Zhou, H
Liu, Z
Yu, X
Li, C
Year 2017
Journal name IEEE Transactions on Industrial Informatics
Volume number 13
Issue number 5
Start page 2279
End page 2290
Total pages 12
Publisher Institute of Electrical and Electronics Engineers
Abstract The classical power allocation/reallocation faces difficult challenges in a future power grid with a great many distributed generators and fast power fluctuations caused by high percentage of renewable energy. To perform power reallocation fast in a future power grid with a large number of participants and disturbances, a hierarchical distributed scheme based on a partition framework is proposed. In the proposed scheme, the power grid is naturally partitioned into a certain number of regions, and the total energy demand in the power grid with disturbances is automatically estimated rather than given in advance. Besides, the centralized local optimizations in regions and the distributed global optimization among regions are coupled to solve the power reallocation problem, in which each region performs as a single agent. Thus, the agents in the proposed scheme are much fewer than the purely distributed ones, hence the communication load is greatly relieved and the reallocation process is significantly simplified. Effectiveness of the proposed scheme is verified by the cases.
Subject Power and Energy Systems Engineering (excl. Renewable Power)
Keyword(s) Controllable loads
energy management system (EMS)
hierarchical distributed scheme
power reallocation
DOI - identifier 10.1109/TII.2017.2670065
Copyright notice © 2017 IEEE. ersonal use is permitted, but republication/redistribution requires IEEE permission
ISSN 1551-3203
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