An artificial neural network hourly temperature forecaster with applications in load forecasting

被引:74
|
作者
Khotanzad, A [1 ]
Davis, MH [1 ]
Abaye, A [1 ]
Maratukulam, DJ [1 ]
机构
[1] ELECT POWER RES INST,POWER DELIVERY GRP,PALO ALTO,CA 94303
关键词
D O I
10.1109/59.496168
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Many short term load forecasting techniques use forecast hourly temperatures in generating a load forecast. Some utility companies, however, do not have access to a weather service that provides these forecasts. To fill this need, a temperature forecaster, based on artificial neural networks, has been developed that predicts hourly temperatures up to seven days in the future. The prediction is based on forecast daily high and law temperatures and other information that would be readily available to any utility. The forecaster has been evaluated using data from eight utilities in the U.S. The mean absolute error of one day ahead forecasts for these utilities is 1.48 degrees F. The forecaster is implemented at several electric utilities and is being used in production environments.
引用
收藏
页码:870 / 876
页数:7
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