Satisfying the energy requirements of a process at minimum cost is a key issue of the energy integration studies. Starting from the definition of the Minimum Energy Requirement : of a process, we propose a method to compute the optimal utility system to satisfy the MER at minimum cost. The method uses three steps, the first step uses a generic utility system superstructure to identify what are the technology requirements of the process, i.e. the technologies that have to be used to satisfy the energy requirements. The model of the superstructure is based on the Effect Modelling and Optimisation (EMO) concepts that use a MILP (Mixed Integer Linear Programming) method to identify the best solutions. The second step is using an expert system to identify the available technologies able to satisfy the technology requirements identified in step 1, for example to identify the gas turbine (technology) that delivers a given heat load (requirement). The third step aims at targeting the optimal process configuration, i.e. to compute the integration of the different technologies to identify their best combinations. This step uses the EMO model to extract the best solutions. Multiple solutions are generated in order to compare the process configurations and identify the break even points of the technologies.