Abstract
The optimal power flow (OPF) problem plays an important role in power system operation and control. The problem is nonconvex and NP-hard, hence global optimality is not guaranteed and the complexity grows exponentially with the size of the system. Therefore, centralized optimization techniques are not suitable for large-scale systems and an efficient decomposed implementation of OPF is highly demanded. In this paper, we propose a novel and efficient method to decompose the entire system into multiple sub-systems based on automatic regionalization and acquire the OPF solution across sub-systems via a modified MATPOWER solver. The proposed method is implemented in a modified solver and tested on several IEEE Power System Test Cases. The performance is shown to be more appealing compared with the original solver.
Original language | English (US) |
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Article number | 4987 |
Journal | Energies |
Volume | 13 |
Issue number | 18 |
DOIs | |
State | Published - Sep 2020 |
Bibliographical note
Funding Information:Funding: This research was supported in part by the National Science Foundation under Grants DMS-1923142, CNS-1932413, ECCS-1828066, OAC-1923983, and CNS-1932139.
Publisher Copyright:
© 2020 by the authors.
Keywords
- Automatic regionalization
- Decomposed iterative algorithm
- Optimal power flow