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Abstract Objective: The objectives of this paper are to 1) construct a new network model compatible with distributed computation, 2) construct the full optimal power flow (OPF) in a distributed fashion so that an effective, non-inferior…

最优化与控制 · 数学 2021-07-14 HyungSeon Oh

The classical optimal power flow problem optimizes the power flow in a power network considering the associated flow and operating constraints. In this paper, we investigate optimal power flow in the context of utility-maximizing demand…

数据结构与算法 · 计算机科学 2018-03-22 Majid Khonji , Chi-Kin Chau , Khaled Elbassioni

This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow…

最优化与控制 · 数学 2016-06-22 Emiliano Dall'Anese , Andrea Simonetto

Using deep neural networks to predict the solutions of AC optimal power flow (ACOPF) problems has been an active direction of research. However, because the ACOPF is nonconvex, it is difficult to construct a good data set that contains…

系统与控制 · 电气工程与系统科学 2021-10-06 Ling Zhang , Baosen Zhang

The primary goal of Optimal Power Flow (OPF) is to optimize the operation of a power system while meeting the demand and adhering to operational constraints. This paper presents a new approach for AC OPF. First, the approach constructs a…

最优化与控制 · 数学 2025-12-16 Mohammed N. Khamees , Kai Sun

Optimal Power Flow (OPF) is an important tool used to coordinate assets in electric power systems to ensure customer voltages are within pre-defined tolerances and to improve distribution system operations. While convex relaxations of…

最优化与控制 · 数学 2016-11-18 Michael D. Sankur , Roel Dobbe , Emma Stewart , Duncan S. Callaway , Daniel B. Arnold

In transmission networks power flows and network topology are deeply intertwined due to power flow physics. Recent literature shows that specific network substructures named bridge-blocks prevent line failures from propagating globally. A…

最优化与控制 · 数学 2021-10-15 Leon Lan , Alessandro Zocca

Higher levels of renewable electricity generation increase uncertainty in power system operation. To ensure secure system operation, new tools that account for this uncertainty are required. In this paper, we formulate a chance-constrained…

最优化与控制 · 数学 2019-05-07 Line Roald , Göran Andersson

Effective power flow (PF) modeling critically affects the solution accuracy and computational complexity of large-scale grid optimization problems. Especially for grid optimization involving flexible topology to enhance resilience,…

系统与控制 · 电气工程与系统科学 2025-03-27 Young-ho Cho , Hao Zhu

The optimal selection, sizing, and location of small-scale technologies within a grid-connected distributed energy system (DES) can contribute to reducing carbon emissions, consumer costs, and network imbalances. This is the first study to…

最优化与控制 · 数学 2022-09-30 Ishanki De Mel , Oleksiy V. Klymenko , Michael Short

Optimal power flow (OPF) problem is a class of large-scale and non-convex optimization problem. Various algorithms are proposed to solve the challenging OPF problem. Recent studies show that semidefinite programming (SDP) can either provide…

最优化与控制 · 数学 2018-02-09 Chin-Yao Chang , Wei Zhang

In recent years, there has been a huge trend to penetrate renewable energy sources into energy networks. However, these sources introduce uncertain power generation depending on environmental conditions. Therefore, finding 'optimal' and…

最优化与控制 · 数学 2019-02-26 Erfan Mohagheghi , Abebe Geletu , Nils Bremser , Mansour Alramlawi , Aouss Gabash , Pu Li

Despite significant economic and ecological effects, a higher level of renewable energy generation leads to increased uncertainty and variability in power injections, thus compromising grid reliability. In order to improve power grid…

最优化与控制 · 数学 2021-11-24 Aleksander Lukashevich , Vyacheslav Gorchakov , Petr Vorobev , Deepjyoti Deka , Yury Maximov

The optimal power flow (OPF) problem can be rapidly and reliably solved by employing responsive online solvers based on neural networks. The dynamic nature of renewable energy generation and the variability of power grid conditions…

系统与控制 · 电气工程与系统科学 2025-02-25 Kejun Chen , Shourya Bose , Yu Zhang

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to…

最优化与控制 · 数学 2019-03-07 Xinyang Zhou , Zhiyuan Liu , Wenbo Wang , Changhong Zhao , Fei Ding , Lijun Chen

In this paper, we propose a graph neural network architecture to solve the AC power flow problem under realistic constraints. To ensure a safe and resilient operation of distribution grids, AC power flow calculations are the means of choice…

Non-convex AC optimal power flow (AC-OPF) is a fundamental optimization problem in power system analysis. The computational complexity of conventional solvers is typically high and not suitable for large-scale networks in real-time…

系统与控制 · 电气工程与系统科学 2022-12-09 Kejun Chen , Shourya Bose , Yu Zhang

This paper introduces a distributed operational solution for coordinating integrated transmission-distribution (ITD) systems regarding data privacy. To tackle the nonconvex challenges of AC optimal power flow (OPF) problems, our research…

系统与控制 · 电气工程与系统科学 2024-02-01 Xinliang Dai , Junyi Zhai , Yuning Jiang , Yi Guo , Colin N. Jones , Veit Hagenmeyer

Many problems in power systems involve optimizing a certain objective function subject to power flow equations and engineering constraints. A long-standing challenge in solving them is the nonconvexity of their feasible sets. In this paper,…

最优化与控制 · 数学 2023-10-03 Ling Zhang , Daniel Tabas , Baosen Zhang

This paper proposes a quasi-optimal power flow (OPF) algorithm for flexible DC traction power systems (TPSs). Near-optimal solutions can be solved with high computational efficiency by the proposed quasi-OPF. Unlike conventional OPF…

系统与控制 · 电气工程与系统科学 2022-11-08 Zhanhe Li , Xiaoqian Li , Yingdong Wei , Chao Lu , Xuelian Bai