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In northern countries, such as Finland, the heat and electricity consumption are strongly affected by seasonal conditions. Thus in the cold and dark winter season the consumption is higher than during the other periods of the year. This leads to a strong seasonal component in the demand of natural gas, which is mainly used by heat and power plants. The current study focuses on the natural gas pipeline in Finland and considers options of extending the pipeline to new cities and/or connecting it with future LNG terminals. The simulation of the gas pipeline is based on information about the present layout, outdoor temperatures and a rough estimate of the distribution of the consumption in the nodes. For a given pipe network and given demands, it provides information about the pressures, flow rates and compressor duties. Furthermore, using the model within an optimisation framework, the feasibility of extending the pipeline to new regions and/or connecting LNG sites with regasification facilities to the network can be studied. The task is formulated as an MINLP optimisation problem, where, e.g., the choice of suitable sites for new LNG terminals in Finland can be evaluated, considering the future development of the whole natural gas distribution network and the gas demand around it. This is a key issue to decrease the dependence on the present energy supply paths and to increase the capacity without pipeline investments in remote regions.

Investigations regarding means to achieve savings in primary energy use and to decrease anthropogenic CO2 emissions have shown that improved energy efficiency has potential to offer a significant contribution to this cause. Considering energy networks and systems, improvements can be achieved by optimizing the structure of the energy chains and distribution networks. For instance, in the case of district heating, it is possible to find an optimal choice of energy supply and design of piping networks to provide the energy required by the customers. Additionally, heat storages and local small-scale energy contributions from e.g. heat pumps could provide benefits and should be taken into consideration. The complexity of the optimization problem increases when the choices of technologies and capacities as well as the network topologies need to be considered. Furthermore, a level of intricacy is added by the large differences in energy demand and temperature conditions between day and night and different seasons. A mixed-integer linear programming model for optimizing distributed energy systems, which takes into account the above mentioned aspects, is being developed and is presented herein. The model is tested with a case study concerning district heating in a locality in southern Finland.

In this study, a process integration approach was used to investigate process economics and carbon dioxide emissions from a steelmaking plant. The suggested superstructure includes the main process units in steelmaking and a polygeneration system producing methanol, heat and electricity. In the steel plant, advanced blast furnace technologies such as top gas recycling and cold oxygen injection have been implemented. The effect of partially replacing of coke with alternative fuels with lower carbon barrier, such as oil, natural gas and biomass on liquid steel production cost and carbon dioxide emission from the integrated plant has been investigated. The results of the analysis demonstrate that an integration of steelmaking with a polygeneration system could increase the total energy efficiency and decrease the emissions of the system. The combinations of technologies and alternative fuels were found to reveal potential paths towards more sustainable steelmaking concepts.