1. Multiregion Short-Term Load Forecasting in Consideration of HI and Load/Weather Diversity.
- Author
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Chu, Wen-Chen, Chen, Yi-Ping, Xu, Zheng-Wei, and Lee, Wei-Jen
- Subjects
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HEATING load , *HUMIDITY , *HEAT index , *ARTIFICIAL neural networks , *REGRESSION analysis , *WEATHER forecasting - Abstract
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 ^\circ\C (80 ^ \circ\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. [ABSTRACT FROM AUTHOR]
- Published
- 2011
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