A Privacy Preserving Distributed Optimization Algorithm for Economic Dispatch Over Time-Varying Directed Networks

The economic dispatch problem (EDP) plays a fundamental and significant role in smart grids. Its purpose is to decide the output power of every generator in smart grids for achieving the minimal generation cost. With advantages in flexibility, robustness, and scalability, it is desirable to apply di...

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Vydané v:IEEE transactions on industrial informatics Ročník 17; číslo 3; s. 1689 - 1701
Hlavní autori: Mao, Shuai, Tang, Yang, Dong, Ziwei, Meng, Ke, Dong, Zhao Yang, Qian, Feng
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.03.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Communication networks
Convergence
Distributed optimization
economic dispatch
Economics
Exchanging
Generators
Optimization
Optimization algorithms
Power dispatch
Privacy
privacy preservation
Smart grid
Smart grids
ISSN:1551-3203, 1941-0050
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Shrnutí:The economic dispatch problem (EDP) plays a fundamental and significant role in smart grids. Its purpose is to decide the output power of every generator in smart grids for achieving the minimal generation cost. With advantages in flexibility, robustness, and scalability, it is desirable to apply distributed optimization methods to solve EDPs. In most existing distributed optimization approaches, all generators explicitly exchange their states with neighbors to obtain the optimal solution, which may result in disclosing the privacy information of generators. This problem becomes worse if there are some adversaries aimed at inferring privacy information from the communication network for nefarious purposes. For privacy preservation, a privacy preserving distributed optimization algorithm over time-varying directed communication networks is proposed in this article by adding conditional noises to the exchanged states. It is proved that this proposed algorithm is able to solve the EDP. Moreover, the convergence rate and privacy analysis of the proposed algorithm are also shown in this article. An example is provided to confirm the effectiveness of this proposed algorithm.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2020.2996198