The work presented in this paper is part of a project that focuses on sorting simulation models used at Intel to calculate power consumption of electronic devices. Hundreds of thousands of analytical power models have already been accumulated in a directory of files and folders, for the simulation of the consumption of thousands of products. As a first step, this work focuses on comparing and grouping together models of smaller granularity-the formulas-which consist of power equations, the definition of the parameters involved in these equations, and a description. To manage this large data problem, we follow the principles of Model Management and Analytics, to decompose the problem into the analysis of constituent fields. We believe that the equations describing power consumption are the most highly information-rich field of our models. The aim of this work is to group together the formulas models, using Mathematical Language Processing (MLP), to take advantage of the business information contained in electrical equations. We calculate the embeddings of our formulas, to enable comparisons between them, to cluster together similar equations (and therefore models).