S. Pineda, M. Aguilar-Moreno, J. M. Morales
The transmission switching problem aims to determine the optimal network topology that minimizes the operating costs of a power system. This problem is typically formulated as a mixed-integer optimization model, which involves big-M constants that lead to weak relaxations and significant computational challenges, particularly when all lines are switchable. In this paper, we propose a two-fold approach: first, using graph theory to derive tighter big-M values by solving a relaxed longest path problem; second, introducing an iterative algorithm that incorporates a heuristic version of the switching problem to efficiently generate low-cost feasible solutions, thereby accelerating the search for optimal solutions in the integer optimization solver. Numerical results on the 118-bus network show that the proposed methodology significantly reduces the computational burden compared to conventional approaches.
Keywords: Transmission Swithcing, Big-M Constants, Graph Theory, Heuristic Algorithms, Computational Optimization.
Scheduled
Optimization and Learning in Energy
June 11, 2025 3:30 PM
Auditorio 2. Leandre Cristòfol