基于数据驱动的电力系统灾变演化及防控研究与展望

李存斌; 计丽妍; 赵德福; 李小鹏

doi:10.7500/AEPS20190226004

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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

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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
- Research and Prospect of Data-driven Based Disaster Evolution and Prevention of Power System
- 电力系统自动化-方正平台 2020年44卷第9期页码：1-11
- 作者机构：
  
  1. 华北电力大学经济与管理学院，北京市 102206
  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：
  
  李存斌(1959—)，男，通信作者，硕士，教授，博士生导师，主要研究方向：电力系统风险管理、电力物理信息融合系统。E-mail：lcb999@263.net
  计丽妍（1991—），女，博士研究生，主要研究方向：中文作者简介:电力系统风险管理、电力物理信息融合系统。E-mail：jiliyan_work@163.com
  赵德福(1994—)，男，硕士研究生，主要研究方向：电力系统风险管理、大数据分析。E-mail：zdf737477@163.com
- 基金信息：
  
  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)
- DOI：10.7500/AEPS20190226004
  中图分类号：
- 收稿日期：2019-02-26，
  
  修回日期：2019-09-04，
  
  网络出版日期：2020-02-17，
  
  纸质出版日期：2020-05-10
- 稿件说明：
移动端阅览
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].电力系统自动化,2020,44(9):1-11.

LI Cunbin,JI Liyan,ZHAO Defu,et al.Research and Prospect of Data-driven Based Disaster Evolution and Prevention of Power System[J].Automation of Electric Power Systems,2020,44(9):1-11.
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].电力系统自动化,2020,44(9):1-11. DOI： 10.7500/AEPS20190226004.

LI Cunbin,JI Liyan,ZHAO Defu,et al.Research and Prospect of Data-driven Based Disaster Evolution and Prevention of Power System[J].Automation of Electric Power Systems,2020,44(9):1-11. DOI： 10.7500/AEPS20190226004.

摘要

随着电力信息物理融合的深入，电力系统呈现出结构复杂化、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 bring forth. Based on the analysis of the current research of power system disaster

this paper proposes the theory of power system disaster process—“disaster pregnancy-disaster transmission-disaster reporting-disaster prevention” for the disaster 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 disaster 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.

关键词

Keywords

references

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