Decomposed Iterative Optimal Power Flow with Automatic Regionalization

Energies

Xinhu Zheng¹  Liuqing Yang¹  Dongliang Duan²  Haonan Wang³ 

[1] Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA;Department of Electrical and Computer Engineering, University of Wyoming, Laramie, WY 82071, USA;Department of Statistics, Colorado State University, Fort Collins, CO 80523, USA;

关键词: optimal power flow, automatic regionalization, decomposed iterative algorithm;   

DOI  :  10.3390/en13184987

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown