...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Electric power systems research >The application of artificial neural networks to substation load forecasting
【24h】

The application of artificial neural networks to substation load forecasting

机译：人工神经网络在变电站负荷预测中的应用

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The substation loading is highly correlated with the customers served. The substations in a distribution system can be categorized as residential, commercial and industrial. Each type has a different power consumption pattern. The substation loading will be varied according to the combination of the above three types of customers. In this paper, a supervisory functional artificial neural network (ANN) technique is applied to solve the load forecasting of three Taipower substations which serve the different customer types. The load forecasting accuracy is enhanced by considering the temperature effect on the substation load demand. With the converged ANN models derived by a training procedure, the temperature sensitivity of the substation load demand is easily obtained by the recall process. It is suggested that the substation load forecasting can be performed efficiently by the proposed method to support distribution operation effectively.
机译：变电站的负荷与所服务的客户高度相关。配电系统中的变电站可以分为住宅，商业和工业。每种类型都有不同的功耗模式。变电站的负荷将根据以上三种客户的组合而变化。在本文中，应用监督功能人工神经网络（ANN）技术来解决服务于不同客户类型的三个台电变电站的负荷预测。通过考虑温度对变电站负荷需求的影响，可以提高负荷预测的准确性。通过训练程序得出的融合ANN模型，通过召回过程可以轻松获得变电站负荷需求的温度敏感性。建议通过所提出的方法可以有效地进行变电站负荷预测，以有效地支持配电运行。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号