Coal has been used as a fuel for electricity generation for centuries. Inexpensive electricity from coal has been a key component in building large industrial economies such as USA and China. But in recent decades the negative aspects of coal, mainly carbon dioxide emissions, has changed the view on the fuel. Carbon capture and storage (CCS) is a solution to be able to continue using coal as an energy source, while limiting carbon emissions. One of the drawbacks of CCS is the energy need associated with the capture process, the energy penalty. This study aims to gather and analyze the energy penalties for the most developed types of carbon capture technologies. It also aims to model how the implementation of CCS would affect the future coal consumption. The results show that the range of energy penalties for a given type of technology is wide. Despite obtaining the energy penalty with the same simulation software, the energy penalty for post- combustion with MEA can range between 10.7% and 39.1%. Comparing mean energy penalties show that pre-combustion capture is the most efficient capture method (18.4% ± 4.4%) followed by oxy- fuel (21.6% ± 5.5%) and post-combustion (24.7% ± 7.9%). Further on, CCS implementation scenarios were compared and used as a starting point for coal consumption calculations. Three pathways were constructed in order to investigate how different distributions of technologies would affect the amount of needed coal. The pathways describe a implementation with only the most efficient technology, the least efficient and a middle option. The results suggest that a large scale implementation of CCS on coal power plant will have a significant impact on the global coal consumption. Under certain assumptions it takes up to 35 % more coal to deliver the same amount electricity with CCS in comparison without CCS. It is also found that certain implementation scenarios will struggle to produce the amount of coal that is needed to power the plants. A sensitivity analysis was performed to examine the impact of assumptions made on for instance plant efficiencies. The analysis shows that optimistic assumptions on development in plant efficiency and deploying only the best technology, uses less coal than a development without CCS and with current plant efficiencies.