Dynamic Aggregation of Grid-Tied Three-Phase Inverters

Victor Purba; Brian B. Johnson; Saber Jafarpour; Francesco Bullo; Sairaj V. Dhople

doi:10.1109/TPWRS.2019.2942292

Dynamic Aggregation of Grid-Tied Three-Phase Inverters

Victor Purba, Brian B. Johnson, Saber Jafarpour, Francesco Bullo, Sairaj V. Dhople

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

The number of grid-tied inverters interfacing renewable resources, energy-storage devices, and flexible loads in distribution networks is steadily increasing. State-space models for inverters are nonlinear and high dimensional which renders the task of modeling large numbers at the edge of the grid to be a difficult undertaking. To address this issue, we develop a distribution-network-cognizant aggregation approach that describes the collective dynamics of grid-tied three-phase inverters. Inverters are clustered based on effective impedances to an infinite bus (modeling the transmission-distribution boundary) and for each cluster, an aggregate dynamical model is developed to preserve the structure and order of each individual inverter state-space model. The K-means algorithm is leveraged for clustering and a suitable linearization of the power-flow equations reduces computational burden involved in determining terminal voltages for the clusters. Numerical simulation results for the IEEE 37-bus feeder system demonstrate the accuracy and computational benefits of the proposed aggregation method.

Original language	English (US)
Article number	8843913
Pages (from-to)	1520-1530
Number of pages	11
Journal	IEEE Transactions on Power Systems
Volume	35
Issue number	2
DOIs	https://doi.org/10.1109/TPWRS.2019.2942292
State	Published - Mar 2020

Bibliographical note

Funding Information:
Manuscript received March 29, 2019; revised August 8, 2019; accepted September 14, 2019. Date of publication September 18, 2019; date of current version February 26, 2020. This work was supported in part by the U.S. Department of Energy Solar Energy Technologies Office under Contract DE-EE0000-1583, in part by the National Science Foundation through Grant 1453921, and in part by the Washington Research Foundation. Paper no. TPWRS-00459-2019. (Corresponding author: Sairaj V. Dhople.) V. Purba and S. V. Dhople are with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: [email protected]; [email protected]).

Publisher Copyright:
© 1969-2012 IEEE.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

Distribution network
model reduction
three-phase inverter
voltage-source inverter

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TPWRS.2019.2942292

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abstract = "The number of grid-tied inverters interfacing renewable resources, energy-storage devices, and flexible loads in distribution networks is steadily increasing. State-space models for inverters are nonlinear and high dimensional which renders the task of modeling large numbers at the edge of the grid to be a difficult undertaking. To address this issue, we develop a distribution-network-cognizant aggregation approach that describes the collective dynamics of grid-tied three-phase inverters. Inverters are clustered based on effective impedances to an infinite bus (modeling the transmission-distribution boundary) and for each cluster, an aggregate dynamical model is developed to preserve the structure and order of each individual inverter state-space model. The K-means algorithm is leveraged for clustering and a suitable linearization of the power-flow equations reduces computational burden involved in determining terminal voltages for the clusters. Numerical simulation results for the IEEE 37-bus feeder system demonstrate the accuracy and computational benefits of the proposed aggregation method.",

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note = "Funding Information: Manuscript received March 29, 2019; revised August 8, 2019; accepted September 14, 2019. Date of publication September 18, 2019; date of current version February 26, 2020. This work was supported in part by the U.S. Department of Energy Solar Energy Technologies Office under Contract DE-EE0000-1583, in part by the National Science Foundation through Grant 1453921, and in part by the Washington Research Foundation. Paper no. TPWRS-00459-2019. (Corresponding author: Sairaj V. Dhople.) V. Purba and S. V. Dhople are with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455 USA (e-mail: [email protected]; [email protected]). Publisher Copyright: {\textcopyright} 1969-2012 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",

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Dynamic Aggregation of Grid-Tied Three-Phase Inverters

Abstract

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Keywords

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