A Hierarchical OPF Algorithm With Improved Gradient Evaluation in Three-Phase Networks

IF 5 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Control of Network Systems Pub Date : 2024-07-09 DOI:10.1109/TCNS.2024.3425633
Heng Liang;Xinyang Zhou;Changhong Zhao
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Abstract

Linear approximation commonly used in solving ac optimal power flow (OPF) simplifies the system models but incurs accumulated voltage errors in large power networks. Such errors will make the primal–dual type gradient algorithms converge to solutions with voltage violations. In this article, we improve a recent hierarchical OPF algorithm that rested on primal–dual gradients evaluated with a linearized distribution power flow model. Specifically, we propose a more accurate gradient evaluation method based on an unbalanced three-phase nonlinear distribution power flow model to mitigate the errors arising from linearization. The resultant gradients feature a blocked structure that enables our development of an improved hierarchical primal–dual algorithm to solve the OPF problem. Numerical results on the IEEE 123-bus test feeder and a 4518-node test feeder show that the proposed method can enhance voltage safety at comparable computational efficiency with the linearized algorithm.
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三相网络中改进梯度评估的分层 OPF 算法
在求解交流最优潮流(OPF)时,常用的线性逼近法简化了系统模型,但在大型电网中存在电压累积误差。这些误差将使原对偶型梯度算法收敛于电压违和的解。在本文中,我们改进了最近的分层OPF算法,该算法依赖于用线性化配电潮流模型评估的原始对偶梯度。具体而言,我们提出了一种基于不平衡三相非线性配电潮流模型的更精确的梯度评估方法,以减轻线性化带来的误差。所得梯度具有阻塞结构,使我们能够开发改进的分层原始对偶算法来解决OPF问题。在IEEE 123总线测试馈线和4518节点测试馈线上的数值计算结果表明,该方法可以在与线性化算法相当的计算效率下提高电压安全性。
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来源期刊
IEEE Transactions on Control of Network Systems
IEEE Transactions on Control of Network Systems Mathematics-Control and Optimization
CiteScore
7.80
自引率
7.10%
发文量
169
期刊介绍: The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.
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