Abstract: In order to reflect the time value of electricity, aiming at the price elasticity for changes in supply and demand and the followed economic principle, the electricity spot market usually adopts the declaration form of multi-segment quotation,i.e., each segment includes the segment capacity and the price. In the spot market, the unit quotation behavior is complicated, except for some extremely high or low prices, it is difficult to distinguish potential conspiracy or abnormal quotes with highly deviated outliers. In order to effectively identify abnormal quotations in the spot market, monitor and analyze market behaviors, and timely discover and control market risks, the Mahalanobis distance is used to eliminate the impact of different prices and capacity dimensions to measure the similarity of different units quotation. The three-dimensional contrast vector of spot quotations is proposed to measure the similarity of quotations. The quotation mode of the density clustering analysis is used to avoid the excessive classification of discrete points, and the judgment indicators are designed for two conspiracy characteristics, the price similarity and the transaction results showing the expected performance of the collusion. Finally, In the context of five segment quotes, in this paper, a simulation example of declaration data in the spot market is used to compare the characteristics of Mahalanobis distance and Euclidean distance in the clustering analysis. The proposed method can eliminate the impact of the dimension, and effectively discover the similarities of the unit in the three dimensions of price declaration, capacity declaration and volume price declaration.