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Aiming at the integrated energy optimization problem of residential buildings including production energy, energy storage and energy use objects, such as photovoltaic power generation, solar heat, electric heating, heat storage, battery, household power load and so on, this paper formulate the energy scheduling policy under the current running state referring to the scheduling policy of similar running state in history from the point of view of data mining. Firstly, a random matrix of basic status of residential buildings energy is constructed. Based on this, a similarity search method based on standardized Euclidean distance measure is proposed. This method forms four standardized Euclidean distances that are the solar irradiance vector, outdoor temperature vector, residential buildings’ electric load vector and heat load vector by the similarity measure calculation based on the standardized Euclidean distance model. The weight analysis method is used to uniformly process a standardized European distance comprehensive index as a measure of similarity. Then, the paper analyses the threshold setting principle of similarity measure. Finally, the optimization process of scheduling strategy of residential buildings energy based on similarity search method is given. A simulation example of an actual residential buildings under a typical scenario of sunny day in winter shows that the proposed similarity search method based on the standardized Euclidean distance measure can make full use of a large amount of historical operating data and speed up the optimization efficiency of optimal scheduling strategy for integrated buildings energy. The scheduling strategy can guide energy storage to play the role of energy transfer, and guide the electric heating equipment and the time-shifting electric load to work in the valley period through the peak and valley electricity prices, thereby the user’s bill is effectively reduced.