The MIND method: A decision support for optimization of industrial energy systems – Principles and case studies

Changes in complex industrial energy systems require adequate tools to be evaluated satisfactorily. The MIND method (Method for analysis of INDustrial energy systems) is a flexible method constructed as decision support for different types of analyses of industrial energy systems. It is based on Mixed Integer Linear Programming (MILP) and developed at Linköping University in Sweden. Several industries, ranging from the food industry to the pulp and paper industry, have hitherto been modelled and analyzed using the MIND method. In this paper the principles regarding the use of the method and the creation of constraints of the modelled system are presented. Two case studies are also included, a dairy and a pulp and paper mill, that focus some measures that can be evaluated using the MIND method, e.g. load shaping, fuel conversion and introduction of energy efficiency measures. The case studies illustrate the use of the method and its strengths and weaknesses. The results from the case studies are related to the main issues stated by the European Commission, such as reduction of greenhouse gas emissions, improvements regarding security of supply and increased use of renewable energy, and show great potential as regards both cost reductions and possible load shifting.