张凯,彭辉.基于鸡群算法参数优化的改进GM(1,1)模型的变压器绝缘水平预测[J].水电能源科学,2019,37(1):164-167
基于鸡群算法参数优化的改进GM(1,1)模型的变压器绝缘水平预测
Prediction of Transformer Insulation Level Based on GM(1,1) Model Improved by Chicken Swarm Parameter Optimization
  
DOI:
中文关键词:  变压器  灰色模型  数据预测  鸡群算法  绝缘水平
英文关键词:power transformer  grey model  data prediction  chicken swarm optimization  insulation level
基金项目:中国南方电网有限责任公司重点科技项目(GZ2014-2-0049)
作者单位
张凯,彭辉 武汉大学 电气工程学院 湖北 武汉 430072 
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中文摘要:
      针对GM(1,1)模型背景值及初始值设置方面存在的缺陷,为减少绝缘事故的发生,提出一种基于鸡群算法参数优化的改进GM(1,1)模型,以南方电网某变电站SSP9-H-120000/220型220 kV主变压器为例,选取绝缘电阻和油介质损耗因数两种指标作为反映变压器整体绝缘水平的状态量,采用所提模型对其进行预测。实例应用结果表明,改进模型在提高变压器绝缘水平预测精度方面效果显著,更符合实际工程需要。
英文摘要:
      An improved GM(1,1) model based parameter optimization with chicken swarm algorithm is proposed to solve the defects of background value and initial value setting of GM(1,1) model. This model can reduce the occurrence of insulation accidents. Taking a SSP9-H-120000/220 main transformer in China Southern Power Grid as an example, choosing the insulation resistance and oil dielectric loss factor as two criterions, the proposed model is used to predict the overall insulation level of the transformer. The application results show that the improved model has a significant effect in improving the prediction accuracy of transformer insulation level, which is more in line with actual engineering needs.
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