Wide-Area Control of Power Systems

Chakrabortty, Aranya

doi:10.1007/978-1-4471-5102-9_100125-1

Cited by 1 publication

(1 citation statement)

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“…With the increasing penetration of renewable energy resources, dynamic loads, energy storage devices, and plug-in electric vehicles, the power system operation is currently experiencing a paradigm shift. In this context, it is important to note that designing real-time systemwide control, commonly referred to as wide-area control [3], [4] is of utmost importance for the resiliency and security of large-scale power systems. While centralized controllers are suitable for system-wide optimization; there are specific challenges in implementing centralized control frameworks for real-time system operation.…”

Section: Introductionmentioning

confidence: 99%

Distributed-MPC with Data-Driven Estimation of Bus Admittance Matrix in Voltage Control

Hossain¹,

Kumar²

2022

Preprint

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This paper presents a distributed model-predictive control (MPC) design for real-time voltage stabilization in power systems, allowing the bus admittance matrix Y = G + jB to be not known a priori (it may be time-varying), and so is estimated online. The prevalent control designs are either centralized and optimal but lack scalability and are subject to network attacks, or decentralized that are scalable and less vulnerable to attacks but are suboptimal. The proposed distributed solution offers the attractive features of both types of schemes, namely, optimality, scalability, as well as enhanced security to network attacks. In addition, since acquiring the exact knowledge of the line conductance and susceptance, which are required to form Y, is in general challenging, the presented framework integrates data-driven estimation of Y to circumvent this challenge. We first introduce the centralized version of the formulation, and next transfer it to a distributed version for efficiency, scalability, and attack-resilience, leveraging the graph structure of the power system. Only local computation and communication are used for (i) computing local control via distributed optimization (which is solved by the alternating direction method of multipliers ADMM), as well as (ii) data-driven estimation of Y. The performance of the proposed methodology is validated using numerical examples of the IEEE-30 Bus and IEEE-57 Bus systems.

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Section: Introductionmentioning

confidence: 99%