At present, the researchs on electric vehicle load prediction are mostly divided by functional areas in space, and the influences of complex spatial forms are rarely considered. So a fast charging load forecast method is proposed for electric vehicles considering urban spatial structure. Firstly, according to the urban road and points of interest (POI) data, the kernel density analysis method is used to determine the urban spatial structure, and the actual electric vehicle travel chain law is simulated by combining the central land theory and the improved gravity model. Then, the flow-speed-power consumption model of real-time traffic flow is constructed in the urban road network. Subsequently, considering the influence of subjective factors of decision-makers, the adsorption model is used to give the user′s limited rational decision-making method. Finally, taking the actual spatial data of a city as an example, the Monte Carlo method is used to obtain the temporal and spatial distribution map of fast charging load in the region, which verifies the effectiveness of the proposed method.