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基于数据驱动的电力系统灾变演化及防控研究与展望
作者:
作者单位:

1.华北电力大学经济与管理学院;2.新能源电力与低碳发展研究北京市重点实验室(华北电力大学),北京市102206;3.华北水利水电大学管理与经济学院,河南省郑州市 450045

作者简介:

通讯作者:

基金项目:

国家自然科学基金资助项目(71840004);国家电网公司总部科技项目(5204BB1600CN)。


Research and Prospect of Data-Driven Disaster Evolution and Prevention of Power System
Author:
Affiliation:

1.School of Economics and Management, North China Electric Power University, Beijing 102206, China;2.Beijing Key Laboratory of New Energy and Low-Carbon Development;3.(North China Electric Power University), Beijing 102206, China;4.School of Management and Economics, North China University of Water Resources and;5.Electric Power, Zhengzhou 450045, China

Fund Project:

This work is supported by National Natural Science Foundation of China (No. 71840004) and State Grid Corporation of China (No. 5204BB1600CN).

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    摘要:

    随着电力信息物理融合的深入,电力系统呈现结构复杂化、外部致灾因子易发等发展趋势。在对电力系统灾变研究现状分析的基础上,针对电力系统灾变演化及防控问题,提出电力系统“孕灾–传灾–报灾–防灾”灾变过程理论。首先,基于大数据驱动分析致灾因子与电力系统孕灾机理及其耦合关系;其次,研究致灾因子的孕育、演化、临界态、涌现与传递机理;再次,基于对外部致灾因子的物联网实时监测技术研究致灾因子及灾变的评估和预警机制;然后,基于态势感知技术分析灾变的主动防控策略,从灾变防控手段库构建、灾变发展趋势感知预测、防控手段智能决策以及灵敏度评估等方面进行分析。最后,提出应用于电力系统灾变防控的大数据分析流程框架。

    Abstract:

    With the deep integration of cyber-physical system, power system presents the development trend that structure is complicated and external hazard factors are easy to occur. Based on the analysis of the current research of power system disaster, this paper proposes the theory of power system catastrophic process —“disaster pregnancy -disaster transmission-disaster reporting-disaster prevention” for the catastrophe evolution and prevention of power system. Firstly, the hazard factors and disaster-generation mechanism of power system and their coupling relationship are analyzed based on the big data-driven. Secondly, the pregnancy, evolution, critical state, emergence and transmission mechanism of hazard factors are studied. Thirdly, based on the Internet of Things(IoT) real-time monitoring technology for external hazard factors, the assessment and early warning mechanism of hazard factors and disasters are studied. Then, based on situational awareness technology, active disaster prevention and control strategies are analyzed from the aspects of disaster prevention and control strategy database construction, perception prediction of the catastrophic development trend, intelligent decision-making of prevention and control strategies, and sensitivity evaluation. Finally, a big data analysis framework for power system disaster prevention and control is proposed.

    表 1 Table 1
    图1 电力系统致灾因子及其分类示意图Fig.1 Schematic diagram of the hazard factor of power system and its classification
    图2 电力系统灾变过程:“孕灾-传灾-报灾-防灾”示意图Fig.2 Schematic diagram of power system disaster process:“disaster pregnancy - disaster transmission - disaster reporting - disaster prevention”
    图3 孕灾过程主要逻辑关系示意图Fig.3 Schematic diagram of main logical relationship of the disaster pregnancy process
    图4 传灾过程主要逻辑关系示意图Fig.4 Schematic diagram of the main logical relationship of the disaster transmission process
    图5 报灾环节主要逻辑关系示意图Fig.5 Schematic diagram of the main logical relationship of disaster reporting link
    图6 防灾环节主要逻辑关系示意图Fig.6 Schematic diagram of the main logical relationship of disaster prevention link
    图7 应用于电力系统灾变研究的大数据分析方法流程图Fig.7 Flow chart of big data analysis method applied to power system disaster research
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引用本文

李存斌,计丽妍,赵德福,等.基于数据驱动的电力系统灾变演化及防控研究与展望[J/OL].电力系统自动化,http://doi.org/10.7500/AEPS20190226004.
LI Cunbin,JI Liyan,ZHAO Defu,et al.Research and Prospect of Data-Driven Disaster Evolution and Prevention of Power System[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20190226004.

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  • 收稿日期:2019-02-26
  • 最后修改日期:2020-02-16
  • 录用日期:2019-10-13
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