Considering that the result from single characteristics may differ from other characteristics and the weights of aging characteristics may be not reasonable enough to judge the actual transformer oil-paper insulation state

we put forward methods of Gray Clustering and Set Weighting to evaluate the oil-paper insulation state. First

we extracted the aging characteristics of return voltage method（RVM） and polarization and depolarzation current（PDC） from the theoretical achievements in existence. Second

we sorted out the standard values of the index of large number of known insulated power transformer time-domain response data which were used to establish the insulation state classification. Last

from the collected data

we used an entropy method and the improved AHP to allocate the grey clustering weights of different aging characteristics. The feasibility and accuracy of Gray Clustering and Set Weighting Methods in evaluation of transformer oil-paper insulation state are verified by the examples of field transformer test

which provides a new direction for the comprehensive evaluation of oil-paper insulation state.