Assessing system costs for power generation is essential for evaluating the economical aspect of energy resources. This paper examines traditional and renewable energy resources under uncertainty and variability of input variables. The levelized cost of electricity (LCOE) of each technology is computed using a global sensitivity analysis. A Monte Carlo approach is utilized to study the thermoeconomics of a variety of power generation methods in the United States: fossil fuel-based, nuclear, developed renewable, and emerging renewable energy resources. The results of this study demonstrate how uncertainties in input data can significantly influence the LCOE values. Power generation from well-developed energy technologies exhibit less variability in LCOE due to established capital costs, operating and maintenance costs, and power generation. On the contrary, emerging renewable energy technologies are subject to high uncertainties in both technical and economic performance, as expected for technologies in early stages of development. A scenario with carbon pricing in power generation is also carried out in the paper. The presence of carbon pricing significantly increases the LCOEs of fossil fuel technologies, and LCOEs of other technologies also experience significant changes when life-cycle carbon assessments are considered. Several cost reduction opportunities are discussed to guide the development of future energy conversion, especially from emerging renewable energy resources.