This body of work is dedicated to the modeling and assessment of initiatives within electricity markets using the underlying hourly market dynamics. We present two separate frameworks that take a bottom-up approach for assessing benefits associated with various demand-side initiatives and other emerging initiatives in power markets. We develop and present models in support of each framework, 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. We find that forward-looking, dynamic strategies are needed in the proper assessment of arbitrage operating profits, because deterministic strategies were only capable of capturing a small fraction of available operating profits. The key insight is that storage does not appear to be a financially prudent investment for arbitrage alone; the substantial capital and fixed operating costs are greater than the operating gains.
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 fuel prices. Numerical results have helped highlight the systematic gains in cost savings and emissions reductions that are made possible through demand side initiatives.
Project Abstract: Energy Economics and Policy Stochastic Modeling of Electric Systems (0.9MB PDF)
James L. Sweeney, Pedram Mokrian