Abstract
With the growing integration of renewable energy and electronic devices, power dispatch tasks face increasing complexity due to internal and external factors, such as weather uncertainty, the long-term impact of energy storage operation, and the fluctuations in the electricity market. Recently, the large language model (LLM) Agent has been proposed, incorporating the LLM with human-like capabilities. This promotes building the LLM-based power dispatch agent to address the abovementioned problems. However, the framework of LLM-based power dispatch agents, key capabilities, and associated challenges remain unclear. Therefore, this paper proposes a comprehensive LLM-based Power Dispatch Agent framework, encompassing perception, planning, memory, reflection, and action modules, to tackle real-world tasks. Then, the capabilities and potential applications of LLM-based Power Dispatch Agent among different power dispatch-related tasks are explored. Finally, the challenges of the LLM-based power dispatch agent are discussed in relation to the requirements of power dispatch and current technologies.
© 2026 The Authors. Published by Elsevier Ltd.
© 2026 The Authors. Published by Elsevier Ltd.
| Original language | English |
|---|---|
| Article number | 111653 |
| Number of pages | 20 |
| Journal | International Journal of Electrical Power & Energy Systems |
| Volume | 175 |
| Online published | 9 Feb 2026 |
| DOIs | |
| Publication status | Published - Feb 2026 |
Funding
This work was supported by the Guangdong Power Grid Company (Grant Number: 036000KC23090006(GDKJXM20231028)) and the National Natural Science Foundation of China (Grant Number: 72331009, 72171206, and 92270105).
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Research Keywords
- Artificial intelligence
- Power dispatch
- Large Language Model-based agent
Publisher's Copyright Statement
- This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/
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