  Rigorous model-based analysis can help inform state-level energy and climate
policy. In this study, we utilize an open-source energy system optimization
model and publicly available datasets to examine future electricity generation,
CO2 emissions, and CO2 abatement costs for the North Carolina electric power
sector through 2050. Model scenarios include uncertainty in future fuel prices,
a hypothetical CO2 cap, and an extended renewable portfolio standard. Across
the modeled scenarios, solar photovoltaics represent the most cost-effective
low-carbon technology, while trade-offs among carbon constrained scenarios
largely involve natural gas and renewables. We also develop a new method to
calculate break-even costs, which indicate the capital costs at which different
technologies become cost-effective within the model. Significant variation in
break-even costs are observed across different technologies and scenarios. We
illustrate how break-even costs can be used to inform the development of an
extended renewable portfolio standard in North Carolina. Utilizing the
break-even costs to calibrate a tax credit for onshore wind, we find that the
resultant wind deployment displaces other renewables, and thus has a negligible
effect on CO2 emissions. Such insights can provide crucial guidance to
policymakers weighing different policy options. This study provides an
analytical framework to conduct similar analyses in other states using an open
source model and freely available datasets.
