Recent Research Hotspot Introduction on the Application of Artificial Intelligence in Power System

Yongli ZHU; Xin SHI; Liuwang WANG

doi:10.12096/j.2096-4528.pgt.2018.031

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Recent Research Hotspot Introduction on the Application of Artificial Intelligence in Power System

Energy Internet | 更新时间：2025-06-06

- Recent Research Hotspot Introduction on the Application of Artificial Intelligence in Power System
- Power Generation Technology Vol. 39, Issue 3, Pages: 204-212(2018)
- 作者机构：
  
  1.新能源电力系统国家重点实验室(华北电力大学), 河北省保定市 071003
  2.上海交通大学大数据工程技术研究中心, 上海市闵行区 200240
  3.国网浙江省电力有限公司电力科学研究院, 浙江省杭州市 310014
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(51677072)
- DOI：10.12096/j.2096-4528.pgt.2018.031
  CLC：
- Received：12 March 2018，
  
  Published：28 June 2018
- 稿件说明：
移动端阅览
Yongli ZHU, Xin SHI, Liuwang WANG. Recent Research Hotspot Introduction on the Application of Artificial Intelligence in Power System[J]. Power Generation Technology, 2018, 39(3): 204-212.
DOI：

Yongli ZHU, Xin SHI, Liuwang WANG. Recent Research Hotspot Introduction on the Application of Artificial Intelligence in Power System[J]. Power Generation Technology, 2018, 39(3): 204-212. DOI： 10.12096/j.2096-4528.pgt.2018.031.

摘要

大数据驱动下的新一代人工智能由传统知识表示转向深度、自主知识学习，不再需要人的过多干预，展现出了更加智能的一面。近年来，深度学习成为人工智能研究热点。该文重点介绍了深度学习的特点、原理及其在电力系统中的应用研究现状，分析了新一代智能方法研究趋势及在应用过程中存在的问题，并提供了基于分布式机器学习和增量学习的解决方法，旨在为相关研究工作者提供参考。

Abstract

The new generation of artificial intelligence driven by big data has shifted from traditional knowledge representation to deep and autonomous learning. It no longer requires too much human intervention and shows a smarter side. In recent years

deep learning (DL) has become the hotspot of artificial intelligence. This paper focuses on the characteristics

principles and the current application status of DL in the power system. It also analyzes the research trends and problems in the application process of the new generation artificial intelligence

and provides solutions based on distributed machine learning and incremental learning methods. This paper is written for providing references for researchers involved in the field.

关键词

Keywords

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