The present invention relates to an intelligent electricity consumption data mining method based on a manifold learning clustering algorithm. The method comprises: acquiring a user n-point electricity consumption data set X={X1, X2...Xs...Xt}, wherein, Xs={x1, x2...xi...xn}, s is an element of [1, t], t is a total number of users, i is an element of [1, n], and n is a total number of electricity consumption data acquisition points; performing normalization processing on s-th user n-point electricity consumption data Xs, and acquiring data Xs' after normalization processing, wherein Xs'={x1', x2'...xi'...xn'}; performing curve fitting on Xs', acquiring a peak corresponding time Tp and a valley corresponding time Tv of electricity consumption of a user, and using Tp and Tv as labels of the user; based on a manifold learning algorithm, performing dimension reduction on the data subjected to normalization processing, and acquiring a data set Y after dimension reduction, wherein Y={Y1, Y2...Ys...Yt}; classifying the data set after dimension reduction by using a clustering algorithm; and evaluating price sensitivity of each class of users. According to the method provided by the present invention, targeted at intelligent electricity consumption data information, clustering analysis is performed on the information by using a manifold learning clustering method, so as to provide decision information for intelligent electricity consumption interaction.