While economic research usually concentrates on capital cost as the dominant driver of the economic competitiveness, operating costs have much lower impact on generation costs. Few estimates are available on SMR O&M costs and fuel costs. Nonetheless some trends and general considerations may be argued:

• The designers of advanced SMRs often indicate that O&M costs might be lower than those of LRs, owing to a stronger reliance of SMRs on passive safety features and to the resulting decrease in the number and complexity of safety features (Kuznetsov and Lokhov, 2011).

• Economy of scale, co-siting economies and learning influence operating costs of multiple SMRs as in the case of construction costs; comparing an LR of 1340 MWe with a fleet of four SMRs of 335 MWe each, the penalty of SMRs on O&M costs due to the loss of economy of scale is mitigated by co-siting and learning effects and the corresponding overall cost increase on LR is limited to +19%; a learning effect on O&M activities of multiple SMRs is also confirmed (Carelli et al., 2008a).

• In general SMRs offer poor neutron economy due to lower reactor core dimensions, which translates into higher fuel cost incidence on generation costs.

• It is expected that long refueling schemes of some SMRs may increase specific fuel costs, due to a less effective fuel utilization, as compared to SMRs with conventional refueling intervals (IAEA, 2006, 2007b).

• Moreover, it is expected that for barge-mounted SMRs the sum of O&M and fuel costs is 50% higher than land-based SMRs, mainly due to a large O&M required by the barge.

Data information on decontamination and decommissioning (D&D) costs of advanced, modular SMR are not available from experience. One possible unbiased way to calculate them is to perform a statistical analysis of the data available from past decommissioning projects. Historical records show that there are several cost drivers that determine the decommissioning cost. Specifically those critical in the comparison between SMR and LR are: plant size, number of units in the site and decommissioning strategy (‘immediate decommissioning’ or ‘deferred decommissioning’). Multiple regression analysis is a powerful tool applicable to these kinds of analysis which is able to quantify exactly the impact of each cost driver; it allows for an in-depth examination of the trend correlation between the dependent and the explanatory variables. The result of this statistical analysis is that the economy of scale also applies to the plant decommissioning activities and represents a disadvantage for SMRs (Locatelli and Mancini, 2010b); the D&D cost for a medium-sized SMR unit may be three times higher than for a large plant. On the other hand, co-siting economies should decrease D&D costs for parallel dismantling of twin units.

It is worth stressing that historical data are related only to GEN I and GEN II reactors (both large and small), not to modern GEN III+ reactors and SMRs. Regarding SMRs, the design layout simplifications and reduced number of components should drive a cost reduction. In the same way as high content of factory fabrication should decrease construction costs by decreasing on-site assembling activities, modular and factory-assembled reactors should be dismantled in a sub-system that could be transported back to a centralized factory, where operations should be cheaper than on-site dismantling (Kuznetsov and Lokhov, 2011; IAEA, 2007b).

As a general, final comment, it can be stated that technical savings from design simplification and standardization and co-siting economies are the competing forces that play against the loss of economy of scale. The balance between these factors should be evaluated on a project-specific basis and supported by data information from actual experience.