| Abstract [eng] |
The decarbonization of the economies needs radical changes in all economic sectors that require massive investments. Therefore, decarbonization actions should be based on detailed analyses of the future development of various sectors and the cost-effectiveness of different emission abatement measures. Energy planning models that work based on minimizing total discounted costs are commonly used to determine how the energy sector should develop to reach various strategic targets, including emission reduction in a least-cost way. However, the cross-sectoral interrelations between the power and transport sectors are often neglected, even though they might have a substantial impact. This doctoral thesis presents a developed model within the MESSAGE modelling framework for assessing least-cost decarbonization pathways of power, district heating and transport sectors, considering the potential of sectoral interrelations in increasing power system flexibility. The developed model optimizes operation and investments in all modelled sectors using perfect foresight optimization. Also, the created model has two unique features: probabilistic wind speed representation for wind power plants and vehicle age distributions. Furthermore, to account for some of the transport sector’s behavioural aspects, travel time budget and inconvenience costs for electric vehicles were modelled. This doctoral thesis presents the results of an integrated least-cost decarbonization analysis of the electricity, district heating and transport sectors for the case of Lithuania that has been carried out using the developed model. |
