文章摘要
李刚,张博,赵文清,等.电力设备状态评估中的数据科学问题:挑战与展望[J].电力系统自动化,2018,42(21):10-20. DOI: 10.7500/AEPS20180331006.
LI Gang,ZHANG Bo,ZHAO Wenqing, et al.Data Science Issues in State Evaluation of Power Equipment: Challenges and Prospects[J].Automation of Electric Power Systems,2018,42(21):10-20. DOI: 10.7500/AEPS20180331006.
电力设备状态评估中的数据科学问题:挑战与展望
Data Science Issues in State Evaluation of Power Equipment: Challenges and Prospects
DOI:10.7500/AEPS20180331006
关键词: 电力设备  电力大数据  故障诊断  状态评估  数据科学
KeyWords: power equipment  electric power big data  fault diagnosis  state evaluation  data science
上网日期:2018-09-29
基金项目:国家电网公司科技项目(5204DY170010);国家自然科学基金资助项目(51407076);中央高校基本科研业务费专项资金资助项目(2018MS075)
作者单位E-mail
李刚 华北电力大学控制与计算机工程学院, 河北省保定市 071003 ququ_er2003@126.com 
张博 华北电力大学控制与计算机工程学院, 河北省保定市 071003  
赵文清 华北电力大学控制与计算机工程学院, 河北省保定市 071003  
刘云鹏 河北省输变电设备安全防御重点实验室(华北电力大学), 河北省保定市 071003  
高树国 国网河北省电力有限公司电力科学研究院, 河北省石家庄市 050021  
摘要:
      电力设备作为能源电力系统的纽带,对其进行有效的状态评估是电力系统稳定运行的有力保障。在目前已有研究成果基础上,从数据科学角度对电力设备状态评估领域中的分析方法做了深入剖析。首先,介绍了数据科学背景下电力设备状态评估的新特点;然后,以目前较为熟知的数据分析方法为切入点,论述了基于数据分析技术的电力设备状态评估方法在数据预处理、计算分析、存储及可视化等各环节的关键问题;其次,系统阐述了数据科学在电力设备状态评估领域中的具体应用场景、瓶颈问题和发展方向;最后,探讨了电力设备状态评估中的数据科学所面临的挑战,并展望了该领域未来研究工作的若干方向。
Abstract:
      As the link of the energy and electric power system, the effective state evaluation of the power equipment is a powerful guarantee for the stable operation of power system. Based on the existing research results and the perspective of data science, this paper makes an in-depth analysis of the methods in the field of state evaluation of power equipment. Firstly, the paper introduces the new characteristics of state evaluation of power equipment in the context of data science. Then, with the current well-known data science analysis method based on data analysis technology as the starting point, the paper presents the key issues of the state evaluation of power equipment in data preprocessing, calculation and analysis, storage, and visualization. In addition, the paper systematically expounds the specific application, bottleneck and future development of data science in the field of state evaluation of power equipment. Finally, the paper discusses the challenge of data science in the state evaluation of power equipment and anticipates some directions of future research work in this field.
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