A Novel Consensus-Based Distributed Algorithm for Economic Dispatch Based on Local Estimation of Power Mismatch

This paper proposes a novel consensus-based distributed control algorithm for solving the economic dispatch (ED) problem of distributed generators (DGs). A legacy central controller can be eliminated in order to avoid a single point of failure, relieve computational burden, maintain data privacy, an...

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Vydané v:IEEE transactions on smart grid Ročník 9; číslo 6; s. 5930 - 5942
Hlavní autori: Pourbabak, Hajir, Luo, Jingwei, Chen, Tao, Su, Wencong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1949-3053, 1949-3061
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Shrnutí:This paper proposes a novel consensus-based distributed control algorithm for solving the economic dispatch (ED) problem of distributed generators (DGs). A legacy central controller can be eliminated in order to avoid a single point of failure, relieve computational burden, maintain data privacy, and support plug-and-play functionalities. The optimal ED is achieved by allowing the iterative coordination of local agents (consumers and DGs). As coordination information, the local estimation of power mismatch is shared among DGs through communication networks and does not contain any private information, ultimately contributing to a fair electricity market. Additionally, the proposed distributed algorithm is particularly designed for easy implementation and configuration of a large number of agents in which the distributed decision making can be implemented in a simple proportional-integral or integral controller. In MATLAB/Simulink simulation, the accuracy of the proposed distributed algorithm is demonstrated in a 29-node system in comparison with the centralized algorithm. Scalability and a fast convergence rate are also demonstrated in a 1400-node case study. Further, the experimental test demonstrates the practical performance of the proposed distributed algorithm using the VOLTTRON platform and a cluster of low-cost credit-card-size single-board PCs.
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ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2017.2699084