This body of work is dedicated to the modeling and assessment of initiatives within electricity markets using the underlying hourly market dynamics. The dissertation presents two separate frameworks that take a bottom-up approach for assessing benefits associated with various demand-side initiatives and other emerging interventions in power markets. Models in support of each framework are presented, and numerical results are used to highlight some impacts based on hourly dynamics. The first framework uses stochastic optimization models to explore the economic feasibility of grid-scale energy storage from the perspective of a price taking, profit maximizing firm facing uncertain market dynamics. This model is then extended to incorporate intermittent wind generation, demonstrating how storage can be used as a potential substitute for transmission capacity. The second framework uses a new dynamic market equilibrium simulation model to address broader economic and environmental impacts of various demand-side initiatives including: energy efficiency, distributed generation, and plug-in hybrid electric vehicles. The general model is calibrated for the California electricity market. The model is used to estimate impacts of the various interventions, taking into account varying market adoption levels and natural gas prices.
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