Motivated by the role of decarbonizing the electric power sector to mitigate climate change, I assess the economic and environmental merits of three key technologies for decarbonizing the electric power sector across four chapters in this thesis. These chapters explore how adding flexibility to power plants equipped with carbon capture and sequestration (CCS) affects system costs and carbon dioxide (CO2) emissions, how grid-scale electricity storage affects system CO2 emissions as a power system decarbonizes, and how distributed solar photovoltaic (distributed PV) electricity generation suppresses wholesale electricity prices. In each chapter, I address these questions through a combination of power system optimization, statistics, and techno-economic analysis, and tie my findings to policy implications. In Chapter 2, I compare the cost-effectiveness of “flexible” CCS retrofits to other compliance strategies with the U.S. Clean Power Plan (CPP) and a hypothetical stronger CPP. Relative to “normal” CCS, “flexible” CCS retrofits include solvent storage that allows the generator to temporarily eliminate the CCS parasitic load and increase the generator’s net efficiency, capacity, and ramp rate. Using a unit commitment and economic dispatch (UCED) model, I find that flexible CCS achieves more cost-effective emissions reductions than normal CCS under the CPP and stronger CPP, but that flexible CCS is less cost-effective than other compliance strategies under both reduction targets. In Chapter 3, I conduct a detailed comparison of how flexible versus normal CCS retrofits affect total system costs and CO2 emissions under a moderate and strong CO2 emission limit. Given that a key benefit of flexible CCS relative to normal CCS is increased reserve provision, I break total system costs into generation, reserve, and CCS capital costs. Using a UCED model, I find that flexible CCS retrofits reduce total system costs relative to normal CCS retrofits under both emission limits. Furthermore, 40-80% of these cost reductions come from reserve cost reductions. Accounting for costs and CO2 emissions, though, flexible CCS poses a trade-off to policymakers under the moderate emission limit, as flexible CCS increases system CO2 emissions relative to normal CCS. No such trade-off exists under the stronger emission limit, as flexible CCS reduces system CO2 emissions and costs relative to normal CCS. In Chapter 4, I quantify how storage affects operational CO2 emissions as a power system decarbonizes under a moderate and strong CO2 emission limit through 2045. In so doing, I aim to better understand how storage transitions from increasing CO2 emissions in historic U.S. systems to enabling deeply decarbonized systems. Additionally, under each target I compare how storage affects CO2 emissions when participating in only energy, only reserve, and energy and reserve markets. Using a capacity expansion (CE) model to forecast fleet changes through 2045 and a UCED model to quantify how storage affects system CO2 emissions, I find that storage quickly transitions from increasing to decreasing CO2 emissions under the moderate and strong emission limits. Whether storage provides only energy, only reserves, or energy and reserves drives large differences in the magnitude, but not the direction, of the effect of storage on CO2 emissions. In Chapter 5, I quantify a benefit of distributed photovoltaic (PV) generation often overlooked by value of solar studies, namely the market price response. By displacing high-cost marginal generators, distributed PV generation reduces wholesale electricity prices, which in turn reduces utilities’ energy procurement costs. Using 2013 through 2015 data from California including a database of all distributed PV systems in the three California investor owned utilities, we estimate historic hourly distributed PV generation in California, then link that generation to reduced wholesale electricity prices via linear regression. From 2013 through 2015, we find that distributed PV suppressed historic median hourly LMPs by up to $2.7-3.1/MWh, yielding avoided costs of up to $650-730 million. These avoided costs are smaller than but on the order of other avoided costs commonly included in value of solar studies, so merit inclusion in future studies to properly value distributed PV.