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	Impact analysis of hourly weather factors in short-term load forecasting and its processing strategy
	Kang Chong-qing ; Zhou An-shi ; Wang Peng ; Zheng Guang-jun ; Liu Yi
	2010-05-06 ; 2010-05-06
关键词	Practical/ load forecasting meteorology neural nets power engineering computing power grids power system security/ short-term load forecasting hourly weather factors power grids economic operation power grids security load sensitive meteorological factors weather service daily maximum temperature daily minimum temperature artificial neural network ANN load curve/ B8110D Power system planning and layout B8140 Power system protection C7410B Power engineering computing C5290 Neural computing techniques
中文摘要	Short-term load forecasting is of great significance to secure and economic operation of power grids, so that novel load forecasting models are always studied to improve forecasting accuracy. Because the portion of the load sensitive to meteorology in the total load becomes more and more great, the key problem in the endeavor of improving the load forecasting accuracy is how to consider the influence of meteorological factors on power loads more reasonably. For a long time past due to that the weather service cannot provide real-time weather forecasting results such as temperature, etc., the overwhelming majority in load forecasting models are established on the basis of daily characteristic meteorological factors, e.g., daily maximum temperature, daily minimum temperature and so on. For short-term load forecasting, after examining the action of meteorological factors and analyzing the strategies to process meteorological factors in different stage, the authors propose a new artificial neural network (ANN) based short-term load forecasting model considering hourly weather factors and strive to find out the correlativity and varying pattern of load curve with real-time meteorological factors such as temperature, relative humidity and other weather variables. Actual applications show that by use of the given forecasting model and processing strategy the obtained forecasting results are more accurate, in addition, the proposed forecasting model is also applicable to ultra-short term load forecasting.
语种	中文 ; 中文
出版者	Electr. Power Res. Inst ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/10540]
专题	清华大学
推荐引用方式 GB/T 7714	Kang Chong-qing,Zhou An-shi,Wang Peng,et al. Impact analysis of hourly weather factors in short-term load forecasting and its processing strategy[J],2010, 2010.
APA	Kang Chong-qing,Zhou An-shi,Wang Peng,Zheng Guang-jun,&Liu Yi.(2010).Impact analysis of hourly weather factors in short-term load forecasting and its processing strategy..
MLA	Kang Chong-qing,et al."Impact analysis of hourly weather factors in short-term load forecasting and its processing strategy".(2010).

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