AI-Based Scheduling Agent Study

DOI

10.2991/978-94-6463-676-5_67How to use a DOI?

Keywords

Dispatch agents; Artificial intelligence; Power grid; Learn to train

Abstract

With the continuous increase in the scale and volume of the power grid, the proportion of existing new energy sources continues to increase, and the level of digitalisation of the power grid is also increasing, which brings huge challenges to power grid companies, and the importance and difficulty of intelligent grid dispatching decisions are also increasing. As the “brain” of power grid operation, dispatching is crucial to the balance and safety and stability of the power grid, and requires comprehensive judgement and accurate decision-making based on a variety of influencing factors. With the widespread access of new energy, the scale of power grid dispatching decisions and the difficulty of solving them are increasing day by day. Therefore, it is necessary to carry out the in-depth application of artificial intelligence technology in the dispatching profession to empower the construction of a digital and strong power grid.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Fengxi Gao
PY  - 2025
DA  - 2025/04/15
TI  - AI-Based Scheduling Agent Study
BT  - Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024)
PB  - Atlantis Press
SP  - 692
EP  - 700
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-676-5_67
DO  - 10.2991/978-94-6463-676-5_67
ID  - Gao2025
ER  -