The energy transition requires significant investments in new power generation, storage, and transmission technology to achieve emission reduction targets while ensuring a stable supply of electricity. However, the increasingly complex, uncertain nature of the power system creates challenges for investors and requires advanced research and modeling. An exploratory analysis is preformed to determine if and how energy system optimization modeling can be used to explore the long-term economic feasibility of investments in the power sector in light of the energy transition. A modeling framework is developed utilizing energy system optimization modeling paired with the uncertainty analysis, modeling to generate alternatives, to explore and provide insights into the profitability of investments in the range of possible near-optimal power system configurations that meet government emission reduction targets. We apply the modeling framework in a case study of the Dutch power system, focusing on investments in the 2030 time frame. The case study is used as a proof of concept of the developed methodological. The case study finds that the developed modeling framework can provide insight into the range of near-optimal power system configurations that meet emission reduction targets and, through an economic analysis, can shed light on the economic feasibility of different technologies. In the particular case of the Netherlands, the case study finds a wide range of possible future near-optimal energy systems exist to meet emission reduction targets, but a lack of profitability of investments indicate policy mechanisms or alternative market arrangements are needed to ensure economic incentives exist for the necessary investments. Further research should include a parametric uncertainty analysis to provide a complete and comprehensive overview, including all types of uncertainty in the system and to identify the affects different types of uncertainty have on the profitability of investments.