2021_IJEPES__Tuning_Successive_Linear_Programming_to_Solve_AC_Optimal_Power_Flow_Problem_for_Large_Networks__preprint_adjustments_.pdf (358.27 kB)
Tuning Successive Linear Programming to Solve AC Optimal Power Flow Problem for Large Networks
preprint
posted on 2021-11-29, 07:13 authored by Sayed Abdullah SadatSayed Abdullah Sadat, mostafa Sahraei-ArdakaniSuccessive linear programming (SLP) is a practical approach for solving large-scale nonlinear optimization problems. Alternating current optimal power flow (ACOPF) is no exception, particularly the large size of real-world networks. However, in order to achieve tractability, it is essential to tune the SLP algorithm presented in the literature. This paper presents a modified SLP algorithm to solve the ACOPF problem, specified by the U.S. Department of Energy's (DOE) Grid Optimization (GO) Competition Challenge 1, within strict time limits. The algorithm first finds a near-optimal solution for the relaxed problem (i.e., Stage 1). Then, it finds a feasible solution in the proximity of the near-optimal solution (i.e., Stage 2 and Stage 3). The numerical experiments on test cases ranging from 500-bus to 30,000-bus systems show that the algorithm is tractable. The results show that our proposed algorithm is tractable and can solve more than 80\% of test cases faster than the well-known Interior Point Method while significantly reduce the number of iterations required to solve ACOPF. The number of iterations is considered an important factor in the examination of tractability which can drastically reduce the computational time required within each iteration.
History
Email Address of Submitting Author
email@SayedSadat.comORCID of Submitting Author
0000-0001-8290-6065Submitting Author's Institution
University of UtahSubmitting Author's Country
- United States of America