Challenges and trade-offs of a cloud hosted phasor measurement unit-based linear state estimator

Vinaya Chakati, Madhurima Pore, A. Pal, Ayan Banerjee, S. Gupta
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引用次数: 5

Abstract

Being one of the key derivatives of phasor measurement units (PMUs), a synchrophasor-only linear state estimator (LSE) presents a reliable, high quality, and truly dynamic picture of the power grid. However, with the increase in number of buses monitored by PMUs, computational burden will become a critical constraint for the state estimation solver. Although installing additional hardware can be a possible solution, such a solution will considerably raise the cost of capital investment, operation, and maintenance. This paper proposes cloud-computing as a cost-effective alternative to the computational burden problem. This paper also presents feasibility of the cloud based solution with regards to scalability of the system and latency incurred. Our solution is designed to address the critical operational parameters such as latency and variable network sizes. Additionally, the LSE application establishes robust communication procedures to process inputs arriving at high data rates from multiple PMUs. The paper concludes by highlighting future research directions for enhancing such cloud based solutions.
基于云托管相量测量单元的线性状态估计器的挑战和权衡
纯同步相量线性状态估计器(LSE)是相量测量单元(pmu)的关键衍生物之一,它能提供可靠、高质量、真实的电网动态图像。然而,随着pmu监控的总线数量的增加,计算负担将成为状态估计求解器的一个关键约束。虽然安装额外的硬件是一种可能的解决方案,但这种解决方案将大大增加资本投资、操作和维护的成本。本文提出云计算作为一种具有成本效益的替代方案来解决计算负担问题。本文还从系统的可扩展性和延迟方面介绍了基于云的解决方案的可行性。我们的解决方案旨在解决关键的操作参数,如延迟和可变网络大小。此外,LSE应用程序建立了健壮的通信程序来处理来自多个pmu的高数据速率输入。文章最后强调了未来的研究方向,以增强这种基于云的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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