基于实时停电态势的风险预警识别模型研究

Research on Risk Early Warning Identification Model Based on Real-time Outage Situation

为了降低电力用户经济损失,设计基于实时停电态势的风险预警识别模型。将系统负载率、自然条件等内外部因素作为实时停电态势要素,构建实时停电态势评价要素体系,采用模糊层次分析法求出实时停电态势要素权重,经加权平均得出实时停电态势评估值,将其作为改进卷积神经网络预测模型输入,预测实时停电态势风险值,按照风险值区分预警级别,并通过不同颜色指示灯呈现预警结果,实现停电风险预警识别。实验结果表明:模型可获取电网停电态势风险值,判断风险等级,在风险较高时及时预警,模型应用后可降低由停电产生的电网经济损失。

The risk early warning identification model based on real-time outage situation is studied to reduce the economic losses of power users.The system load rate,natural conditions and other internal and external factors are taken as the real-time outage situation elements,and the real-time outage situation evaluation element system is constructed.The fuzzy analytic hierarchy process is used to calculate the real-time outage situation element weight,and the real-time outage situation evaluation value is obtained by weighted average.It is used as the input of the improved convolutional neural network prediction model to predict the real-time outage situation risk value,and the early warning level is divided according to the risk value.The early warning results are displayed by different color indicators to realize the early warning identification of power failure risk.The experimental results show that the model can obtain the risk value of power grid outage situation,judge the risk level,and give early warning when the risk is high.After the model is applied,the economic loss of power grid caused by power outage can be reduced.