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IEEE Transactions on Power Systems
Article . 2024 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2022
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Online Decentralized Tracking for Nonlinear Time-Varying Optimal Power Flow of Coupled Transmission–Distribution Grids

Authors: Wentian Lu; Kaijun Xie; Mingbo Liu; Xiaogang Wang; Lefeng Cheng;

Online Decentralized Tracking for Nonlinear Time-Varying Optimal Power Flow of Coupled Transmission–Distribution Grids

Abstract

The coordinated alternating current optimal power flow (ACOPF) for coupled transmission-distribution grids has become crucial to handle problems related to high penetration of renewable energy sources (RESs). However, obtaining all system details and solving ACOPF centrally is not feasible because of privacy concerns. Intermittent RESs and uncontrollable loads can swiftly change the operating condition of the power grid. Existing decentralized optimization methods can seldom track the optimal solutions of time-varying ACOPFs. Here, we propose an online decentralized optimization method to track the time-varying ACOPF of coupled transmission-distribution grids. First, the time-varying ACOPF problem is converted to a dynamic system based on Karush-Kuhn-Tucker conditions from the control perspective. Second, a prediction term denoted by the partial derivative with respect to time is developed to improve the tracking accuracy of the dynamic system. Third, a decentralized implementation for solving the dynamic system is designed based on only a few information exchanges with respect to boundary variables. Moreover, the proposed algorithm can be used to directly address nonlinear power flow equations without relying on convex relaxations or linearization techniques. Numerical test results reveal the effectiveness and fast-tracking performance of the proposed algorithm.

18 pages with 15 figures

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Keywords

FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Optimization and Control (math.OC), FOS: Mathematics, Distributed, Parallel, and Cluster Computing (cs.DC), Mathematics - Optimization and Control

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green