PowerModelsADA: A Framework for Solving Optimal Power Flow Using Distributed Algorithms

被引：0
|
作者：
Alkhraijah, Mohannad [1 ]
Harris, Rachel [1 ]
Coffrin, Carleton [2 ]
Molzahn, Daniel K. [1 ]
机构：
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
[2] Los Alamos Natl Lab, Adv Network Sci Initiat, Los Alamos, NM 87545 USA
来源：
IEEE TRANSACTIONS ON POWER SYSTEMS | 2024年 / 39卷 / 01期
关键词：
Load flow; Generators; Optimization; Data structures; Benchmark testing; Loading; Distributed algorithms; Distributed optimization; optimal power flow; CONSTRAINED UNIT COMMITMENT;
D O I：
10.1109/TPWRS.2023.3318858
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This letter presents PowerModelsADA, an open-source framework for solving Optimal Power Flow (OPF) problems using Alternating Distributed Algorithms (ADA). PowerModelsADA provides a framework to test, verify, and benchmark both existing and new ADAs. This letter demonstrates use cases for PowerModelsADA and validates its implementation with multiple OPF formulations.
引用
收藏
页码：2357 / 2360
页数：4
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