# A set of models for optimization of gas distribution networks: a study in Process and Systems Engineering

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Abstract

atural 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.