This paper examines flexible operation of solvent-based post-combustion carbon capture (PCC) for the reduction of power plant carbon emissions while minimizing revenue loss due to the reduced power plant electricity output. The study is conducted using a model superstructure enveloping three plants; a power plant, a PCC plant and a solar thermal field where the power plant and PCC plant are operated flexibly under the influence of hourly electricity market and weather conditions. Reduced (surrogate) models for the reboiler duty and auxiliary power requirement for the carbon capture plant are generated and applied to simulate and compare four cases, (A) power plant with PCC, (B) power plant with solar assisted PCC, (C) power plant with PCC and solar repowering - variable net electricity output and (D) power plant with PCC and solar repowering - fixed net electricity output. Such analyses are conducted under dynamic conditions including power plant part-load operation while varying the capture rate to optimize the revenue of the power plant. Each case was simulated with a lower carbon price of $25/tonne-CO2 and a higher price of $50/tonne-CO2. The comparison of cases B-D found that optimal revenue generation for case C can be up to 42% higher than that of solar-assisted PCC (case B). Case C is found to be the most profitable with the lowest carbon emissions intensity and is found to exhibit a constant capture rate for both carbon prices. The optimal revenue for case D is slightly lower than case C for the lower carbon price ($25/tonne-CO2) while it is considerably lower in the higher carbon price ($50/tonne-CO2) scenario. The highest revenue to electricity ratio is found to be for the case where solar repowering is used for power boosting. This study highlights the significant potential of dynamic flexible operation toward deeper reductions in carbon capture costs. This analysis is based on the presence of a carbon pricing scheme currently not present in the Australian market, but which could be realised in the future. (C) 2015 Elsevier Ltd. All rights reserved.