The main goal of this paper is to prove that bi-objective optimization of high-pressure gas networks ensures grater system efficiency than scalar optimization. The proposed algorithm searches for a trade-off between minimization of the running costs of compressors and maximization of gas networks capacity (security of gas supply to customers). The bi-criteria algorithm was developed using a gradient projection method to solve the nonlinear constrained optimization problem, and a hierarchical vector optimization method. To prove the correctness of the algorithm, three existing networks have been solved. A comparison between the scalar optimization and bi-criteria optimization results confirmed the advantages of the bi-criteria optimization approach.

Abstract. The aim of this study was to identify an optimal CCS transport infrastructure for Polish energy sector in regards of selected European Commission Energy Roadmap 2050 scenario. The work covers identification of the offshore storage site location, CO2 pipeline network design and sizing for deployment at a national scale along with CAPEX analysis. It was conducted for the worst-case scenario, wherein the power plants operate under full-load conditions. The input data for the evaluation of CO2 flow rates (flue gas composition) were taken from the selected cogeneration plant with the maximum electric capacity of 620 MW and the results were extrapolated from these data given the power outputs of the remaining units. A graph search algorithm was employed to estimate pipeline infrastructure costs to transport 95 MT of CO2 annually, which amount to about 612.6 M€. Additional pipeline infrastructure costs will have to be incurred after 9 years of operation of the system due to limited storage site capacity. The results show that CAPEX estimates for CO2 pipeline infrastructure cannot be relied on natural gas infrastructure data, since both systems exhibit differences in pipe wall thickness that affects material cost.

No abstract