DocumentCode
1366694
Title
Multiregion Short-Term Load Forecasting in Consideration of HI and Load/Weather Diversity
Author
Chu, Wen-Chen ; Chen, Yi Ping ; Xu, Zheng Wei ; Lee, Wei Jen
Author_Institution
Tatung Univ., Taipei, Taiwan
Volume
47
Issue
1
fYear
2011
Firstpage
232
Lastpage
237
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°C (80°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.
Keywords
humidity; load forecasting; meteorology; power consumption; power system control; power system security; Taiwan Power Company; Taiwan´s distinct climate characteristics; electric utility; heat index; human-perceived equivalent temperature; load consumption; load/weather diversity; multiregion short-term load forecasting; power supply reliability; power supply security; power system control; power system operation; relative humidity; Artificial neural networks; Forecasting; Heating; Humidity; Indexes; Load forecasting; Heat Index (HI); load forecasting; multiregion; neural network;
fLanguage
English
Journal_Title
Industry Applications, IEEE Transactions on
Publisher
ieee
ISSN
0093-9994
Type
jour
DOI
10.1109/TIA.2010.2090440
Filename
5617262
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