Academic Journal
Hierarchical Task Planning for Power Line Flow Regulation
| العنوان: | Hierarchical Task Planning for Power Line Flow Regulation |
|---|---|
| المؤلفون: | Chenxi Wang, Youtian Du, Yanhao Huang, Yuanlin Chang, Zihao Guo |
| المصدر: | CSEE Journal of Power and Energy Systems, Vol 10, Iss 1, Pp 29-40 (2024) |
| بيانات النشر: | China electric power research institute, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Technology LCC:Physics |
| مصطلحات موضوعية: | Knowledge graph, power line flow regulation reinforcement learning, task planning, Technology, Physics, QC1-999 |
| الوصف: | The complexity and uncertainty in power systems cause great challenges to controlling power grids. As a popular data-driven technique, deep reinforcement learning (DRL) attracts attention in the control of power grids. However, DRL has some inherent drawbacks in terms of data efficiency and explainability. This paper presents a novel hierarchical task planning (HTP) approach, bridging planning and DRL, to the task of power line flow regulation. First, we introduce a three-level task hierarchy to model the task and model the sequence of task units on each level as a task planning-Markov decision processes (TP-MDPs). Second, we model the task as a sequential decision-making problem and introduce a higher planner and a lower planner in HTP to handle different levels of task units. In addition, we introduce a two-layer knowledge graph that can update dynamically during the planning procedure to assist HTP. Experimental results conducted on the IEEE 118-bus and IEEE 300-bus systems demonstrate our HTP approach outperforms proximal policy optimization, a state-of-the-art deep reinforcement learning (DRL) approach, improving efficiency by 26.16% and 6.86% on both systems. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2096-0042 |
| Relation: | https://ieeexplore.ieee.org/document/10375975/; https://doaj.org/toc/2096-0042 |
| DOI: | 10.17775/CSEEJPES.2023.00620 |
| URL الوصول: | https://doaj.org/article/2ace01d5cea8452f9e72e1581b05e3e6 |
| رقم الانضمام: | edsdoj.2ace01d5cea8452f9e72e1581b05e3e6 |
| قاعدة البيانات: | Directory of Open Access Journals |
| تدمد: | 20960042 |
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| DOI: | 10.17775/CSEEJPES.2023.00620 |