Title :
A spatial modeling technique for small area load forecast
Author :
Wu, H.C. ; Lu, C.N.
Author_Institution :
Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
Abstract :
In a deregulated environment, competition will lead to an increase of electrical energy usage. The increase in the demand could lead to substantial expansion planning implications for many transmission and distribution (T&D) systems. Locations of future load growth have to be described with sufficient geographic precision to permit valid siting of future T&D equipment. Spatial load forecast provides information of future electric demand that includes location, magnitude and temporal characteristics. In this paper, a "knowledge discovery in database (KDD)" technique is used to determine automatically the preferential "scores" of small areas with respect to the possibility of land use changes, and consequently the load growth. It is an exploratory data analysis, trying to discover useful patterns in spatial data that are not obvious to the data user and to support the load forecast.
Keywords :
data mining; load forecasting; power system analysis computing; competition; data analysis; data mining; deregulated environment; power systems; small area load forecast; spatial modeling technique; Computational modeling; Data analysis; Data mining; Land use planning; Load forecasting; Load modeling; Pattern matching; Predictive models; Road transportation; Spatial databases;
Conference_Titel :
Power Engineering Society Summer Meeting, 2001
Conference_Location :
Vancouver, BC, Canada
Print_ISBN :
0-7803-7173-9
DOI :
10.1109/PESS.2001.970236
