LAPSE:2023.7117
Published Article
LAPSE:2023.7117
Online ADMM for Distributed Optimal Power Flow via Lagrangian Duality
Song Wang, Liangyi Pu, Xiaodong Huang, Yifan Yu, Yawei Shi, Huiwei Wang
February 24, 2023
At present, the power system has the characteristics of mutual independence but interconnection, and the interconnection between the various subsystems brings certain challenges to the distributed computing of the power grid. In addition, a substantial amount of naturally uncertain renewable resources are incorporated into the power system, which will impose volatile dynamics on the grid. In this paper, an alternating direction multiplier method (ADMM) is proposed for the power system with real-time renewables to tackle the online optimal power flow (OPF) problem. Due to the adoption of the Lagrangian duality, the proposed distributed ADMM scheme utilizes consensus ADMM to solve the dual OPF problem, which only discloses boundary coupling via the Lagrangian multiplier and further reduces the amount of information communication. Given the natural uncertainty of distributed energy resources (DER), the algorithm avoids the double-loop implementation or the uncertainty of traditional distributed methods of using the boundary information as equality constraints caused by dynamic DER. It is thus capable of providing a provable performance guarantee and is inherently developed to cope with the dynamic OPF problem with renewables in an online fashion. Taking the IEEE 30-bus system as a test feeder, the simulation results verify the efficiency and robustness of the proposed algorithms in solving both the static and dynamic OPF problems; in addition, the online method can effectively avoid the violent fluctuations of the conventional generator output copying with renewables rapid variation in comparison with the offline algorithms.
Keywords
alternating direction multiplier method, Lagrangian duality, online approach, optimal power flow
Suggested Citation
Wang S, Pu L, Huang X, Yu Y, Shi Y, Wang H. Online ADMM for Distributed Optimal Power Flow via Lagrangian Duality. (2023). LAPSE:2023.7117
Author Affiliations
Wang S: Chongqing Huizhi Energy Corporation Ltd., State Power Investment Corporation (SPIC), Chongqing 401127, China
Pu L: Chongqing Huizhi Energy Corporation Ltd., State Power Investment Corporation (SPIC), Chongqing 401127, China
Huang X: Chongqing Huizhi Energy Corporation Ltd., State Power Investment Corporation (SPIC), Chongqing 401127, China
Yu Y: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China
Shi Y: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China
Wang H: Key Laboratory of Intelligent Information Processing, Chongqing Three Gorges University, Chongqing 404100, China; Chongqing Innovation Center, Beijing Institute of Technology, Chongqing 401120, China [ORCID]
Journal Name
Energies
Volume
15
Issue
24
First Page
9525
Year
2022
Publication Date
2022-12-15
Published Version
ISSN
1996-1073
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PII: en15249525, Publication Type: Journal Article
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LAPSE:2023.7117
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doi:10.3390/en15249525
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