A Random Forest-Assisted Fast Distributed Auction-Based Algorithm for Hierarchical Coordinated Power Control in a Large-Scale PV Power Plant

Zhang, Xiao Shun, Yu, Tao, Yang, Bo and Jiang, L ORCID: 0000-0001-6531-2791 (2021) A Random Forest-Assisted Fast Distributed Auction-Based Algorithm for Hierarchical Coordinated Power Control in a Large-Scale PV Power Plant. IEEE Transactions on Sustainable Energy, 12 (4). p. 1.

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Official URL: http://dx.doi.org/10.1109/tste.2021.3101520

Abstract

In response to the automatic generation control (AGC) signals, the direct power control of a large-scale PV power plant easily encounters the communication bottlenecks, the high optimization difficulty and computation burden due to the large number of controllable inverters with different response performances. To handle these problems, a hierarchical framework of coordinated power control (CPC) is constructed, which is decomposed into a upper-layer CPC between different sub-areas and a lower-layer CPC between different inverters in each sub-area. Instead of a centralized optimization, a novel random forest-assisted fast distributed auction-based algorithm (FDAA) is proposed for a distributed optimization of CPC. The random forest can rapidly generate a dynamic surrogate model of the optimization results from the low-layer CPC to the upper-layer CPC, thus these two-layer optimizations of CPC can be decoupled without too much interactions and computations. The effectiveness of the proposed method is thoroughly evaluated on a PV power plant with 10 sub-areas and 100 inverters under various irradiation conditions.

Item Type:	Article
Uncontrolled Keywords:	Random forests, Optimization, Automatic generation control, Real-time systems, Reactive power, Power control, PV power plant, hierarchical coordinated power control, fast distributed auction-based algorithm, random forest, surrogate model
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	03 Sep 2021 07:17
Last Modified:	18 Jan 2023 21:30
DOI:	10.1109/tste.2021.3101520
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3135671