Renewable energy has been increasingly penetrating into the power grid system due to the stimulus plan from the government and its environment-friendly nature. But meanwhile the output of renewable energy (such as wind and solar) is intermittent. As a result, the increasing renewable energy penetration increases volatility for the power grid system, which is reflected as more significant electricity price fluctuations in the current deregulated electricity markets. Fortunately, the batteries of plug-in hybrid electric vehicles can serve as buffers to accommodate this by storing electricity when the renewable energy generation is high and discharging otherwise, so as to achieve power balance and flatten the electricity prices. This provides a promising win-win process of tackling renewable energy generation uncertainty and reducing fossil fuel usage, which can further achieve a sustainable integrated power-transportation system. This award supports fundamental research to efficiently integrate the plug-in hybrid electric vehicles into the power grid system at transmission and distribution levels, and show how this improves current deregulated electricity market practice. If successful, this project will help increase utilization of renewable energy and reduce greenhouse emissions for both power and transportation industry at minimum cost. By closely collaborating with Midcontinent Independent System Operator, the findings of this project can be implemented to industry faster. Finally, the underrepresented Ph.D. students will be recruited and motivated to participate in this project.
Integrating plug-in hybrid electric vehicles into the power grid system is technically challenging. This research is to explore advanced stochastic optimization and game theory models to formulate problems and develop innovative solution approaches to solve the models so as to help derive optimal decisions for system operators and market participants with different objectives, such as maximizing the social welfare for the system operators and maximizing the total profit for the market participants. This study will lead to innovative trading policies for the market participants and refined market design rules to ensure fairness and cost efficiency for the electricity markets, while ensuring high utilization of renewable energy. Furthermore, the innovative solution techniques explored, including convex and monotonicity analyses for Markov decision process utilizing the problem structure, linearization and decomposition algorithms for stochastic optimization problems with equilibrium constraints, and cutting planes and branch-and-cut algorithms for multistage stochastic integer programs, will lead to methodology innovations in each corresponding field.
