Abstract
This article deals with optimal transmission switching (OTS) problems involving binary decisions about network topology and nonconvex power flow constraints. We adopt a semidefinite programming formulation for the optimal power flow (OPF) problem that, however, remains nonconvex due to the presence of discrete variables and bilinear products between the decision variables. To tackle the latter, we introduce a physically inspired, virtual-voltage approximation that leads to provable lower and upper bounds on the solution of the original problem. To deal with the exponential complexity caused by the discrete variables, we introduce a graph partition-based algorithm that breaks the problem into several parallel mixed-integer subproblems of smaller size. Simulations on the IEEE bus test cases demonstrate the high degree of accuracy and affordable computational requirements of our approach.
Original language | American English |
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Pages (from-to) | 1246-1256 |
Number of pages | 11 |
Journal | IEEE Transactions on Control Systems Technology |
Volume | 29 |
Issue number | 3 |
DOIs | |
State | Published - 2021 |
NREL Publication Number
- NREL/JA-5D00-77924
Keywords
- graph partitions
- mixed-integer programming
- optimal power flow (OPF)
- optimal transmission switching (OTS)
- power networks
- semidefinite programming (SDP)