基于支持向量机的变电站蓄电池健康度评估

Health Evaluation of Storage Battery in Substation Based on Support Vector Machine

针对变电站蓄电池健康状态评估手段效率低,破坏性强的缺点,以评估变电站蓄电池健康度为目标,利用支持向量机算法提出了一种新的变电站蓄电池健康评估模型。为了验证该模型的有效性,利用北京某变电站蓄电池组的实测数据进行验证,实验结果表明该模型的分类精度高达97.45%。通过实例验证了该模型能够对变电站蓄电池的健康度能够进行较好评估。

In view of the disadvantages of low efficiency and strong destructiveness of substation battery health assessment method,a new substation battery health assessment model is proposed by using support vector machine algorithm to assess the health of substation battery.In order to verify the effectiveness of the model,the measured data of a substation in Beijing are used to verify the model.The experimental results show that the classification accuracy of the model is as high as 97.45%.The exemplified model can be used to evaluate the health of battery in substation.