Title :
Knowledge extraction model for power load characteristics of special days and extreme weather
Author :
Quansheng, Dou ; Guanyu, Pan ; Zhongzhi, Shi ; Bin, Yang
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Inst. of Bus. & Technol., Yantai, China
Abstract :
Load forecasting is a traditional research field of power system, under normal circumstance, there are great similarities between the similar days, but under the condition of special days and extreme weather, load prediction has some uncertainty. Extraction model for load characteristics of special days and extreme weather was proposed in this paper, coding strategy and genetic operation of traditional genetic algorithm were redefined in the model, the relational rules about relation between power load special days and extreme weather were extracted. At the same time, the credibility of these rules was proven by practice.
Keywords :
encoding; genetic algorithms; knowledge acquisition; load forecasting; power systems; coding strategy; extreme weather; genetic algorithm; genetic operation; knowledge extraction; load forecasting; load prediction; power load; power system; special days; Data mining; Genetics; Humidity; Load forecasting; Load modeling; Power system modeling; Technology forecasting; Temperature; Weather forecasting; Wind speed; load forecasting; rules extraction;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357793
