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Consensus-Based Distributed Economic Dispatch Control Method in Power Systems.

Authors :
Li, Qiao
Gao, David Wenzhong
Zhang, Huaguang
Wu, Ziping
Wang, Fei-yue
Source :
IEEE Transactions on Smart Grid; Jan2019, Vol. 10 Issue 1, p941-954, 14p
Publication Year :
2019

Abstract

This paper introduces a new consensus-based control scheme for distributed power systems to solve the distributed economic dispatch (DED) problem. With the development of renewable energy, smart grid, and microgrid, more and more distributed generators will be connected to power systems. Thus the distributed control schemes become more and more important for power systems to control and manage the distributed equipment. Therefore, some consensus-based methods are published previously to solve the DED problem. But the challenge to apply the consensus-based method is to meet the power balance constraint without the centralized facility, since the value of power mismatch is hard to be obtained for a distributed control system. To solve the problem, this paper proposes the method to combine the frequency control methods with the consensus protocol from graph theory to develop the DED control method, so that the real power between the load and the generation can be balanced during the economic dispatch. With this method, a totally distributed optimal control scheme is obtained. The PI frequency controller and neural network frequency controller are employed to develop the DED control method. Then the communication failure problem is considered in this paper. The robust DED control method is proposed to improve the robustness of this distributed control method, allowing the system to stay at the optimal dispatching even if the communication is failed. In addition, the model of transmission line losses is incorporated in the DED problem to reduce the line losses. Finally, several case studies are given in this paper to verify the proposed method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19493053
Volume :
10
Issue :
1
Database :
Complementary Index
Journal :
IEEE Transactions on Smart Grid
Publication Type :
Academic Journal
Accession number :
133875867
Full Text :
https://doi.org/10.1109/TSG.2017.2756041