Author ORCID Identifier
Date of Graduation
Statler College of Engineering and Mineral Resources
Lane Department of Computer Science and Electrical Engineering
Hong Jian Lai
Security Constrained Unit Commitment (SC-UC) is a complex large scale mix integer constrained optimization problem solved by Independent System Operators (ISOs) in the daily planning of the electricity markets. After receiving offers and bids, ISOs have only few hours to clear the day-ahead electricity market. It requires a lot of computational effort and a reasonable time to solve a large-scale SC-UC problem. However, exploiting the fact that a UC problem is solved several times a day with only minor changes in the system data, the computational effort can be reduced by learning from the historical data and identifying the patterns in the historical data using data mining techniques.
In this research study, two data driven approaches based on predictive modeling techniques are proposed to solve a SC-UC problem in a day ahead electricity market which can be used as alternative backup methods for solving a SC-UC problem. In the first approach, the SC-UC is partially modeled using predictive modeling techniques to enhance the computational speed of the problem, while in the second approach, the optimization problem is completely replaced by data driven predictive models to further enhance the computational efficiency, however, at the cost of some optimality loss. The proposed approaches are validated through numerical simulations on different IEEE case studies to demonstrate and study the effectiveness of the developed approaches. The results obtained from the proposed approaches are compared with those obtained from commercial optimization solvers e.g., IBM CPLEX MIQP and GUROBI MIQP solvers.
Iqbal, Talha, "AI-Driven Security Constrained Unit Commitment Using Predictive Modeling And Eigen Decomposition" (2023). Graduate Theses, Dissertations, and Problem Reports. 12109.