To improve the energy and environmental sustainability, the power grid is increasing the penetration of distributed energy resources, such as photovoltaic (PV) arrays, wind turbines, electric vehicles, batteries, and responsive demands. However, high levels of distributed energy resources can change the behavior of the grid, with potential undesirable effects on the grid stability and power quality. This necessitates transformative approaches to coordinate the large number of distributed energy resources. These approaches need to handle the high uncertainty involved in the renewable generation and to call upon customers to actively participate. Additional challenges are placed by the still-undeveloped sensing, communication, and computation resources for the grid. To address these challenges, this CAREER proposal is to develop distributed coordination rules to optimize, control, and incentivize the distributed energy resources in order to ensure efficient, adaptive, and reliable performance of the grid. The proposal will integrate multidisciplinary approaches, in particular, mathematics, engineering, and economics. Results can also be transferred to other large-scale socio-technical systems, such as transportation systems and water/gas distribution systems. Broad impacts will follow from an integrated educational dissemination plan, involvement of undergraduates especially under-represented groups in research, transition of new ideas to industry, and outreach to the general public and K-12 students.
As a socio-technical system, two factors distinguish the power grid from other networks, its intrinsic physics and its close human interactions. Accordingly, this proposal will design automated distributed algorithms to optimize the performance of the energy resources at slow-time scales and to control them to ensure energy balance at fast-time scales, and design incentive schemes such as pricing, rewards, payoff, and trading rules to promote human participants to take desired actions. The automated algorithms will tackle the challenges brought by the power system physics (e.g. physical laws such as Kirchhoff's law and system dynamics such as swing dynamics), limited communication, and uncertain generation/consumption. The algorithms will also maximize the use of physics in order to lower sensing, communication, and computation overhead. The incentive schemes will tackle the challenges brought by the self-interested nature of humans. Owners of distributed energy resources are mostly profit-maximizing entities, seeking their own best interest and lacking incentives to reveal truthful private information. Lastly the proposal will jointly design the distributed architecture, algorithms and incentive schemes by strongly integrating the engineering and economics in order to ensure high-performance and high-confidence operation of distributed energy resources to facilitate a smoother transition for the grid into the next age of a smarter grid.
