| 摘要 |
PURPOSE: A wind power density predicting method using a principal component analysis technique is provided to supply a geographical statistic model related to ground density analysis by using various geographical data and reinterpretation weather data. CONSTITUTION: Independent variables selected from wind power density, directions, surface roughness, altitude, a relative altitude difference, a gradient, a relative gradient, average altitude, minimum altitude, maximum altitude, relief energy, a distance from a shore, and reinterpretation weather data are inputted(S100). The independent variables are analyzes as principal components through principal component analysis using an intrinsic value and an accumulated value(S200). Regression analysis by a phased selection method is performed by using the independent variables analyzed as the principal components, a variable number, and a dependent variable(S300). A multiple regression equation having the highest R^2 value among multiple regression equations using regression coefficients is estimated(S400). [Reference numerals] (AA) Start; (BB) End; (S100) Inputting variables; (S200) Analyzing principal components; (S300) Regression analyzing; (S400) Measuring a multiple regression equation |
