Natural gas is a fossil fuel with a high potential to become the bridging fuel in the transition towards a sustainable future because of its lower share of carbon compared to oil and coal. A growing popularity of LNG, biogas, CNG or SNG is expected to lead to an increase in the demand and consumption. However, the distribution of the gas from the gas sources to consumers at remote or stranded areas poses challenges for the gas supply chain.The main objective of this thesis is to study, formulate and apply optimization models for minimizing the costs incurring during the expansion and operation of a gas supply network. Such a network has to satisfy demands from multiple customers and technical requirements. At the same time, it has to be able to respond to the changes in the conditions such as fluctuations in the fuel prices and in the supply and demand.Mathematical modelling and optimization are efficient tools to deal with complex gas distribution problems. The optimal network structure may be determined by formulating and solving an optimization problem, using, e.g., non-linear programming (NLP), mixed-integer linear programming (MILP) or mixed-integer non-linear programming (MILNP) models. The specific features of gas pipeline distribution problems require consideration of nonlinear expressions, while options whether to connect a node to the network require binary variables. In the supply chain, pipeline distribution can be augmented by truck supply from LNG ports or CNG stations to the customers. This results in problem formulations where the optimal pipeline connections, gas flows, compression, storage size, the number of truck transports, etc., must be determined. The thesis develops a set of models for optimization of gas supply chains, and illustrates them by case studies considering the optimal structure, extensions and operation of the existing Finnish transmission network and of two small regional gas distribution networks in Finland. The sensitivity of the optimal solutions to changes in the conditions, e.g., fuel prices and investment costs, is also considered. The advantages and limitations of each of the formulations developed, such as the possibility to identify optimal extensions and network operation, the model complexity, calculation time, etc., have to be considered in the selection of an appropriate tool for optimizing the gas distribution network. The models developed can be used in the design of new supply chains, for analyzing existing ones with respect to operation efficiency or to assess the feasibility of extensions or modifications of the chains.
|Tila||Julkaistu - 2019|
|OKM-julkaisutyyppi||G5 Tohtorinväitöskirja (artikkeli)|