This presentation explores the potential role of various system flexibility investments in regional electric power systems with high variable renewable energy deployment, and the impacts these investments can have on energy market prices. Using EPRI’s United States Regional Economy, Greenhouse Gas, and Energy (US-REGEN) model, this research (1) examines the potential for a range of flexibility enhancing resources, such as natural gas turbines, energy storage, and transmission capacity investments, to support increased variability across a range of high-renewable regional grids; (2) explores the relative role and comparative value of these different system flexibility resources for different regions; and (3) analyzes potential implications of increased renewable deployment and system flexibility resource investments on regional bulk-system energy market prices. Results show that(1) energy storage can be an important resource in high-renewable power systems, particularly in managing energy price volatility and preventing significant shifts in negative price hours; (2) new transmission capacity can support renewable deployment, but its marginal value decreases as regions further develop their own high-renewable grids; (3) natural gas combustion turbines continue to play an important role in supporting higher renewable grids, but their role might be more easily substituted for by other resources at very high penetration levels; and (4) overall, the level of variable renewable energy appears to be a larger determinant of changes in energy prices than the specific set of flexibility resources that may be available on the system. Sensitivity analyses exploring these impacts under an alternate natural gas price suggest that results are relatively robust against future higher natural gas prices. Overall, this research develops a foundation for future research to further examine the value of system flexibility enhancing resources, including considering the additional grid services they may provide and additional asset-specific engineering and system-level operational constraints.