Multiregion Short-Term Load Forecasting in Consideration of HI and Load/Weather Diversity

被引:27
|
作者
Chu, Wen-Chen [1 ]
Chen, Yi-Ping [1 ]
Xu, Zheng-Wei [1 ]
Lee, Wei-Jen [2 ]
机构
[1] Tatung Univ, Taipei 104, Taiwan
[2] Univ Texas Arlington, Dept Elect Engn, Arlington, TX 76011 USA
关键词
Heat Index (HI); load forecasting; multiregion; neural network;
D O I
10.1109/TIA.2010.2090440
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The ultimate goal of an electric utility is to create maximum profit while maintaining reliability and security of the power supply. The operation and control of power system is sensitive to system demand. Therefore, improvements in load-forecasting accuracy will lead to cost savings and enhance system security. Due to Taiwan's distinct climate characteristics, it is difficult to obtain satisfactory load-forecasting results by treating the whole island as a single region. In addition, weather factors, such as temperature, relative humidity, and the Heat Index (HI) (a human-perceived equivalent temperature) may also affect load-consumption patterns. This paper proposes a multiregion short-term load-forecasting methodology, taking into account the HI to improve load-forecasting accuracy in Taiwan Power Company's (Taipower's) system. The results show that adopting the HI as a parameter can effectively improve the accuracy if the temperature of the region under investigation is above 27 degrees C (80 degrees F). By considering both the load/weather diversity and the HI, further improvements to the load forecasting for the Taipower system during summer can be achieved.
引用
收藏
页码:232 / 237
页数:6
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