Mechanical and Civil Engineering Seminar

Abstract: To decarbonize the electric power grid, there have been increased efforts to utilize clean renewable energy sources, as well as demand-side resources such as electric loads. This utilization is challenging because of uncertain renewable generation and inelastic demand. Furthermore, the interdependencies between system states of power networks or interconnected loads complicate several decision-making problems. In this talk, I will present two control and optimization tools to help to overcome these challenges and improve the sustainability of electric power systems. The first tool is a new dynamic contract approach for direct or indirect load control that can manage the financial risks of utilities and customers, where the risks are generated by uncertain renewable generation. The key feature of the proposed contract method is its risk-limiting capability, which is achieved by formulating the contract design problem as mean-variance constrained risk-sensitive control. The performance of the proposed contract framework is demonstrated using data from the Electricity Reliability Council of Texas. The second tool is developed for combinatorial decision-making under system interdependencies, which are inherent in interconnected loads and power networks. For such decision-making problems, which can be formulated as optimization of combinatorial dynamical systems, I will present a linear approximation method that is scalable and has a provable suboptimality bound. The performance of the approximation algorithm is illustrated in ON/OFF control of interconnected supermarket refrigeration systems and power network topology optimization. Finally, I will discuss several future research directions in the operation of sustainable systems, including a unified risk management framework for electricity markets, contract theory for networked systems, and the design of optimization and control tools for resilient cyber-physical infrastructure systems.