The objective of this research is to develop a tool for the security-constrained optimal coordination of generation and transmission maintenance outage scheduling. The proposed problem is a very large-scale, non-linear, non-convex, and mixed-integer optimization problem. The approach is to innovatively apply Lagrangian relaxation, Benders decomposition, and Dantzig-Wolfe decomposition techniques to decompose such a complex problem into tractable small-scale subproblems. The extreme complexity of this research makes it a high-risk project that no individual power market authority would normally fund, while the prospective security, economic, and social benefits of this research make it a perfect project that NSF should support.
Intellectual Merit:
This research will introduce methodologies for enhancing the security of aging power system infrastructure. The proposed methodologies consider comprehensive coordination schemes and realistic system operational condition simulations for modeling the outage management of integrated mid-term generation and transmission systems. The solution strategies will extend the boundaries of existing computational models and may benefit other industries facing similar outage management problems.
Broader Impacts:
Graduate students including female and minority students with diverse backgrounds will participate in this research. Such students will gain experience via exposure to the real world problems and mentorship they receive from industry participants in this project. A new course on power system outage management will be offered by the PI for educating students on applications of modern optimization techniques and risks associated with investments on and operations of generation and transmission assets. The proposed activity will promote awareness of complex power systems among electricity market participants.
