台风气象环境电网设备风险量化预警及其N-m故障处置预案在线生成方法

doi:10.16183/j.cnki.jsjtu.2021.S2.004

摘要/Abstract

摘要：

为提升台风等灾害性气候下电网运行的风险预警预控能力,将气象环境数据、地理环境、输变电设备状态与电网实时状态结合,通过机器学习技术提取电网历史故障特征,将数字化输电通道的气象风险概率量化研判,实现台风气象环境下电网高风险故障的超前量化预警,并根据当时的电网状态实时生成当前和未来态N-m故障处置预案,显著增强故障预想的及时性与针对性.该方法克服了气象风险模型需要不断根据实际情况修正的困难,考虑了高风险概率设备故障后电网中的各类安全自动装置的响应情况和需要采取的控制措施.实际应用表明, 该方法可为电网调度运行风险预控提供重要决策支持.

关键词: 气象风险, 机器学习, 量化预警, 预案在线生成, 在线安全分析

Abstract:

In order to improve the power grid operation risk early warning and pre-control capabilities in typhoon and other disastrous climates, the historical fault features of power grid are extracted by utilizing the machine learning technology based on the meteorological environment data, geographic environment, and the status of power transmission and transformation equipment. The meteorological risk probability of digital transmission channel is quantified to realize the advanced quantitative warning of high-risk faults in the power grid under typhoon weather environment. The proposed method can genarate the current and future N-m fault handling plans based on the current power grid status and significantly enhance the timeliness and pertinence of fault prediction. This method overcomes the difficulty that the meteorological risk model needs to be continuously revised according to the actual situation, and takes into account the response of various safety automatic devices in the power grid after a high-risk equipment failure and the control measures that need to be taken. The practical application shows that this method can provide significant decision supports for risk pre-control in the power grid dispatching operation.

Key words: meteorological risk, machine learning, quantitative warning, fault contingency plan generation, online dynamic security analysis

中图分类号:

TM732

周毅, 秦康平, 孙近文, 范栋琦, 郑义明. 台风气象环境电网设备风险量化预警及其N-m故障处置预案在线生成方法[J]. 上海交通大学学报, 2021, 55(S2): 22-30.

ZHOU Yi, QIN Kangping, SUN Jinwen, FAN Dongqi, ZHENG Yiming. Real-Time Risk Evaluation Method of Power System Equipment and N-m Fault Contingency Plan Generation Under Typhoon Meteorological Environment[J]. Journal of Shanghai Jiao Tong University, 2021, 55(S2): 22-30.

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气象类型	数据类型	具体数据	时空分辨率
台风	中心预报	台风中心经纬度、移动速度、中心最低气压	台风生成时即开始发布,48 h警戒线外每3~6 h 1次; 24 h警戒线外每3 h 1次; 24 h警戒线内每1 h 1次
	中心实测	台风中心经纬度、台风中心风速、台风中心气压、7级风圈半径、10级风圈半径、台风中心移动速度、台风中心移动方向	台风中心实时数据1h发布1次,台风进入预报范围后,整点发布
	网格预报	台风网格风速、台风网格风向	9 km×9 km 台风期间每日8:00、20:00时各发布1次,共计12789个网格