Keywords
power system operation control, power grid operation section, Qlearning, dynamic detection method, agent
Abstract
Power grid operation section is an important measure in power system operation control. Faced with the numerous intelligent generation methods of grid operation sections at present, how to make a reasonable choice has become an important content of the research in the field of online generation algorithms for grid operation sections. To solve this problem, a dynamic detection method for power grid operation section based on Qlearning algorithm is proposed. The main feature of this method is that the Qlearning agent is trained, and the grid operation section generation method is dynamically selected according to the grid operation characteristics, so as to make full use of the algorithm advantages of different generation methods in different scenarios. Finally, a case study based on the actual data in a certain provincial power grid shows that the dynamic detection method can improve the accuracy of the generated results by optimizing the selection of the detection algorithms in different scenarios. For the applied sample set, the method could improve the accuracy by nearly 5.2%.
DOI
10.19781/j.issn.1673-9140.2021.04.015
First Page
116
Last Page
123
Recommended Citation
Li, Bao; Wu, Yunliang; Deng, Weisi; and Li, Peng
(2021)
"A novel dynamic detection approach for power system operation section based on Qlearning algorithm,"
Journal of Electric Power Science and Technology: Vol. 36:
Iss.
4, Article 15.
DOI: 10.19781/j.issn.1673-9140.2021.04.015
Available at:
https://jepst.researchcommons.org/journal/vol36/iss4/15