Strategic decisions regarding industrial energy systems should ideally involve the entire plant. Complexity in most industrial systems makes it difficult to gain good insight into how well such systems work. This depends on the number of existing and possible choices. Lack of necessary control can lead to undesirable results in the form of less economical results and/or increased environmental impacts. Industrial energy efficiency is of vital importance as regards the environment and industrial profitability.

 In the deregulated Swedish (and European) energy market, there are large variations in spot prices for electricity. Systems analysis using optimization methods identifies the minimum cost solution among numerous alternatives.

New possibilities for modeling certain parts of a dynamic industrial energy

system are described. Also, processes involving generating and using heat, such as certain processes in steelmaking companies, are one of the subjects in this thesis. A decision-making tool, called MIND, has been developed and used.

The papers describe developments regarding energy or material storage, batch

processes, and the capacity to describe the generation and usage of heat in a process unit in an industrial system, as well as the benefits of optimization modeling. The results show that the developed tool functions well; it has been applied to two industries.