A Monte Carlo tree search-based method for decision making of generator serial restoration sequence

Xu, Wenwen and Chen, Shuting and Han, Guangxin and Yu, Nan and Xu, Han (2023) A Monte Carlo tree search-based method for decision making of generator serial restoration sequence. Frontiers in Energy Research, 10. ISSN 2296-598X

[thumbnail of pubmed-zip/versions/2/package-entries/fenrg-10-1007914-r1/fenrg-10-1007914.pdf] Text
pubmed-zip/versions/2/package-entries/fenrg-10-1007914-r1/fenrg-10-1007914.pdf - Published Version

Download (1MB)

Abstract

Reasonable generator serial restoration sequence is a key issue to the system restoration following blackouts. This paper proposed an optimization method for the decision making of generator serial restoration sequence based on Monte Carlo tree search algorithm. First, the generator serial restoration sequence mechanism during the restoration process is analyzed. Considering the maximization of the total power generation capacity as the objective function, this paper also consider generator’s hot start. Second, the Monte Carlo tree search algorithm (MCTS) is applied to decide the generator serial restoration sequence. In the simulation stage of MCTS, the Dijkstra’s algorithm is utilized to determine the shortest path between the selected generator and the recovered power system. Finally, the IEEE 39 bus system and Hebei power grid system are used to validate the proposed algorithm. Simulation results show that the proposed method is efficiency and it can provide an reasonable generator serial restoration sequence to maximizing power generation during the restoration process.

Item Type: Article
Subjects: STM Digital > Energy
Depositing User: Unnamed user with email support@stmdigital.org
Date Deposited: 01 May 2023 07:29
Last Modified: 14 Sep 2024 04:42
URI: http://research.asianarticleeprint.com/id/eprint/711

Actions (login required)

View Item
View Item