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A method of predicting failures of 10KV distribution networks of countries every month by Markov chain with weights

机译:权重马尔可夫链预测国家10KV配电网故障的一种方法

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摘要

The failures in 10KV distribution networks of countries every month are affected by various factors such as weather, load. There are much uncertainty and imprecise characteristics in predicting the failures of 10KV distribution networks every month. A method called Markov chain applied in predicting the future failures of rural distribution networks is presented in this paper. The number of fault is calculated according to the history data of the failures sequence. The self-coefficients of the historical data sequence is calculated as weight number by applying the scheme of blur and cluster to constitute the standard of classification. The number of fault in the next month is predicted by applying the model of the Markov chain. Other disturbance is avoided by applying the scheme presented in this paper, the precision is improved and model of prediction is simplified at the same time. The scheme is validated at last the paper by applying the scheme to predict a real failures of 10KV distribution networks in nearly 40 months, and an ideal result is obtained.
机译:每个国家的10KV配电网络的故障每月都会受到各种因素的影响,例如天气,负荷。每月预测10KV配电网络的故障有很多不确定性和不精确的特征。提出了一种用于预测农村配电网未来故障的马尔可夫链方法。根据故障序列的历史数据计算故障数。通过应用模糊和聚类方案构成分类标准,将历史数据序列的自系数计算为权数。通过应用马尔可夫链模型可以预测下个月的断层数。应用本文提出的方案避免了其他干扰,提高了精度,同时简化了预测模型。最后,将该方案应用于近40个月内10KV配电网的实际故障预测,验证了该方案的有效性。

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