A computer-implemented method for evaluating the energy consumption in an industrial plant , comprising: at a plurality of time instants, capturing with a plurality of sensors, sensor data from at least one level of the industrial plant , wherein said plurality of sensors comprises energy measuring sensors, the method characterized in that it further comprises: from said sensor data, digitally obtaining a plurality of energy consumption curves x j , wherein j = 0, 1, 2, ..., J-1, J being a natural number, an energy consumption curve representing, along a certain time period T, discrete values of energy consumption corresponding to time intervals Δt into which said time period T is divided, from said energy consumption curves x j , applying a clustering algorithm for digitally computing a plurality of K energy consumption patterns C k , wherein k = 0, 1, 2, ..., K-1, K being a natural number, K < J, wherein each energy consumption pattern C k represents a set of energy consumption curves x j grouped together according to a similarity metric, wherein each energy consumption pattern C k comprises discrete values of energy consumption corresponding to said time intervals Δt into which said time period T is divided, capturing data of the production achieved during said time period T at said at least one level of the industrial plant , calculating, for each energy consumption curve belonging to each pattern, the aggregated sum of the discrete values of energy consumption during said time period T, thus obtaining the aggregated energy consumption for each energy consumption curve during said time period T, digitally establishing a relationship between aggregated energy consumption for each energy consumption curve during said time period T and said captured data of production. from said sensor data, digitally obtaining a plurality of energy consumption curves x j , wherein j = 0, 1, 2, ..., J-1, J being a natural number, an energy consumption curve representing, along a certain time period T, discrete values of energy consumption corresponding to time intervals Δt into which said time period T is divided, from said energy consumption curves x j , applying a clustering algorithm for digitally computing a plurality of K energy consumption patterns C k , wherein k = 0, 1, 2, ..., K-1, K being a natural number, K < J, wherein each energy consumption pattern C k represents a set of energy consumption curves x j grouped together according to a similarity metric, wherein each energy consumption pattern C k comprises discrete values of energy consumption corresponding to said time intervals Δt into which said time period T is divided, capturing data of the production achieved during said time period T at said at least one level of the industrial plant , calculating, for each energy consumption curve belonging to each pattern, the aggregated sum of the discrete values of energy consumption during said time period T, thus obtaining the aggregated energy consumption for each energy consumption curve during said time period T, digitally establishing a relationship between aggregated energy consumption for each energy consumption curve during said time period T and said captured data of production. <EOS>