摘要
调查数据作为停电损失评估的基础已得到普遍认同,然而,如何应对调查数据中的瞒报与虚报问题,迄今为止尚无切实可行的技术措施。针对这一问题,引入了能够对调查数据进行截断处理的Tobit模型,在对其进行改进后,得到了适用于停电损失评估的新的Tobit模型。该模型首先对超出限值的数据进行截断处理,然后通过极大似然估计的回归计算方法得到停电损失估算函数。利用该模型可以计算出区域内某次停电事故给各类用户造成的损失,同时对市场环境下的用户恶意虚报损失行为有良好的甄别效果。最后以某商业用户为例进行了测算,测算结果证明了所提出的方法的正确性。
It has been widely recognized that investigation data is the foundation of outage cost assessment. However,how to deal with the inevitable fault and concealed information from the original data under investigation remain a challenging problem yet to be solved effectively by applicable measures. Focused on this problem,the Tobit model to truncated process the investigation data is firstly introduced,and then an improved Tobit model suitable for outage loss assessment is proposed. In this model,the data beyond the limits are truncated and the outage cost assessment function is obtained by the regression method based on the maximum likelihood estimation （MLE）. By using this model,the outage cost of all kinds of customers caused by an outage in a specific area can be calculated,and good results can be obtained to identify customers＇ malicious fault behaviors in an electricity market. At last,a testing scenario of a business customer is done,and the testing results show the correctness of the proposed method.
出处
《电力系统自动化》
EI
CSCD
北大核心
2010年第9期29-33,共5页
Automation of Electric Power Systems
基金
国家科技支撑计划资助项目(2008BAA13B00)~~
