With oxygen enrichment in hot stoves (HS) the high calorific coke oven gas can be saved due to the possibility of using lower calorific gases which enables replacement of other imported fuels such as oil or LPG. The application of oxygen enrichment in hot stoves or increased O2 content in the blast to the blast furnace (BF), will also potentially lead to lower coke rate. The demand for coke oven gas depends on internal operation logistics and it also has outdoor temperature dependence through a heat and power plant producing district heat to the community. An analysis of the influence of increased oxygen enrichment in HS-BF on the entire energy system has been carried out by using an optimization model. A method of achieving a high time resolution in MILP optimisation is applied in the analysis. Different strategies have been suggested for minimum energy consumption at the studied steel plant and the nearby combined heat and power (CHP) plant. Central to the performance in system optimisation is the ability to analyse and properly describe the system variations.

In this paper a new method for increased time resolution in multi-period Mixed Integer Linear Programming (MILP) optimisation is presented and applied to a district heating system. The proposed method facilitates the analysis of many time periods in multi period MILP optimisation projects. In the paper, a 365 time period model spanning 1 year developed with the novel method is compared to a 12 time period model developed with a more conventional methodology. The new method offers a significant decrease in the amount of input data for multi period models and facilitates changes to the analysed time span or resolution in time. In the application of the new method oil savings of 7% compared to the current operational strategy of the district heating system are revealed.

A detailed mathematical process integration model of a pulp and paper mill in the Northern Sweden has been developed. The main objective of this work has been set to describe the practical development of the model with particular emphasis on the development of the digester and evaporation plant sub-models. Actual plant measurements have been used to validate the model. By implementing the sub-models into the complete plant model, the influence of different operation parameters on the overall plant performance has been investigated. Furthermore, introductory studies with the main objective to minimize the plant energy cost have been carried out.

A mathematical process integration model of a pulp and paper mill in the Northern Sweden has been developed. The main modelling focus has been put on the two main steam consumers (the evaporation plant and the digester), for which detailed material and energy balances have been established. Operational data have been used to validate the simulation results. By implementing these submodels into the complete plant model, the influence of different operation parameters on the overall plant performance has been investigated. Furthermore, introductory studies with the main objective to minimize the plant energy cost have been carried out. The correlation and differences between economic and energy have been discussed

A mathematical process integration model for the steam generation part (recovery boiler, bark boiler, and turbine) was developed based on a pulp and paper mill in the Northern Sweden. The material and energy balances were calculated theoretically and then the operation data from a pulp and paper mill in the Northern Sweden were used to validate the simulation results. By implementing it into the whole plant, the effect of the operation conditions on the whole plant performance were investigated. The introductory studies were carried out with an objective function to minimize the energy cost. The influence of different parameters was rigorously studied. The correlation between economic and energy optima was discussed.

LKAB Malmberget is a Swedish mining site located at Malmberget, Sweden. Seven boiler centers are located in the north part of Malmberget. There are no connections in between these boiler centers, meaning that it is a decentralized heating system. The heat generated is used to heat up buildings and for mine ventilation air mainly during the cold periods. The heat is mainly provided from electric and oil boilers. However, most boilers under use are over 20 years old, and it is time to retrofit the boiler system and infrastructure. The purpose of this work is to design and optimize the heating system by introducing an integrated concept to minimize the heat production cost.An optimization model based on the mixed integer linear programming (MILP) has been developed. Several technical options have been considered in a new centralized heating system. The optimization principle is based on two kinds of perspectives: current price and external costs. With consideration of environmental and health damage from society concerns point of view, instead of environmental taxes in the current price perspective, the monetary values of externalities due to pollutants such as CO2, NOx, SO2 and particulates emitted from the heating system are included. On the basis of data input and assumptions, modeling results indicate that a lower cost could be achieved when a waste heat recovery boiler is installed at the older pelletization plant to recover sensible heat from flue gas. This technical option is the best solution or at least contributes to the best solution in all optimization results. Including the externality cost is useful for making fair evaluation of the social-environmental impacts of the alternatives.

The development and application of a 1-dimensional static blast furnace model, "Masmod", written in a common spreadsheet environment, is described. The model includes blast furnace, hot stove, and burden models with recent additions of other operations including CO2 stripping and top gas recycle. Although blast furnace modelling has become increasingly sophisticated, a relatively simple and flexible model is shown to be useful for evaluating burden options, equipment and operational strategies, and process development. Furthermore the Masmod model has been integrated with global steel plant optimization models and Process Integration models for more complex system analysis and optimization.

LKAB Malmberget is a Swedish mining site located at Malmberget, Sweden. Seven boiler centers are located on north part of Malmberget. There are no connections in between these boiler centers, meaning that it is a decentralized heating system. The heat generated is to heat up buildings and for mine ventilation mainly during the cold periods. The heat is mainly provided from electric and oil boilers. However, most boilers under use are over 20 years old, and it is time to retrofit the boiler system and infrastructure. The purpose of this work is to design and optimize the heating system by the integrated concept. An optimization model based on the mixed integer linear programming (MlLP) has been developed to minimize the total heat production cost, including operation cost and investment cost. The model can be used to calculate how a given heat demand can be satisfied at the lowest possible cost. Four different technical options have been considered in a new centralized heating system. On the basis of data input and assumptions, modeling results indicate that a lower cost could be achieved when a waste heat recovery boiler is installed at the old pelletization plant to recover sensible heat from flue gas. This will lead to a remarkable electricity saving (around 70% saving) compared to the reference case. It has also been noticed that in the optimized cases, oil boilers should not be operated due to a higher price compared to electricity, and by estimation an annual reduction of 3000 ton CO2 and 4.5 ton NOx could be achieved.

Currently, the blast furnace (BF) to basic oxygen furnace (BOF) is the dominant steel production route in the steel industry. The direct CO2 emission in this process system exceeds 1 t of CO2/t of crude steel produced. Different ferrous burden materials, for instance iron ore and scrap, can be used in various proportions in this steelmaking route. This paper analyses how energy use, conversion costs, and CO2 emissions can be influenced by the use of different ferrous burden materials when producing crude steel. An optimisation mixed integer linear programming (MILP) model has been applied for analysis. By the use of the optimisation model, it is possible to highlight some issues of special importance, such as best practices to increase production at low conversion cost, or best practices to increase production at low CO2 emission. It is found out that more benefits will be gained when using the system-oriented analysis to the steelmaking process. Furthermore, a comprehensive view of the trade-offs between the objectives of Cost and CO2 can provide useful information for decision makers to generate strategies under the future emission trading.