Fast QSTS for Distributed PV Impact Studies Using Vector Quantization and Variable Time-Steps

Barry Mather; Qinmiao Li; Jeremiah Deboever; Matthew Reno

doi:10.1109/ISGT.2018.8403406

Fast QSTS for Distributed PV Impact Studies Using Vector Quantization and Variable Time-Steps

Barry Mather, Qinmiao Li, Jeremiah Deboever, Matthew Reno

Power Systems Engineering

Research output: Contribution to conference › Paper › peer-review

8 Scopus Citations

Abstract

As the penetration level of PV systems increases, utilities are in great need of methods to quickly and effectively analyze PV's impact on electric distribution systems. Compared to other conventional methods, quasi-static time-series (QSTS) based analysis has demonstrated its advantages of accurately capturing the impact of interest, e.g. control device operations, and min and max voltages. However, yearlong QSTS simulation with 1-second granularity is currently too computationally expensive for regular use. Therefore, vector quantization (VQ) and variable time-step (VTS) solution methods have been developed to accelerate QSTS simulation. This paper proposes the combination of VQ with VTS. We investigate the effectiveness of implementing VQ in combination with 2 VTS algorithms, predetermined time-step (PT) and VTS with backtrack downsampling (VTS-BD) to demonstrate a runtime reduction of 99.55% with error metrics below acceptable thresholds.

Original language	American English
Pages	1-5
Number of pages	5
DOIs	https://doi.org/10.1109/ISGT.2018.8403406 https://doi.org/10.1109/ISGT.2018.8403406
State	Published - 3 Jul 2018
Event	2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018 - Washington, United States Duration: 19 Feb 2018 → 22 Feb 2018

Conference

Conference	2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018
Country/Territory	United States
City	Washington
Period	19/02/18 → 22/02/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

NREL Publication Number

NREL/CP-5D00-68992

Keywords

Photovoltaic Systems
Power Distribution
Power System Analysis Computing
Power System Planning
QSTS
Vector Quantization

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Mather, B., Li, Q., Deboever, J., & Reno, M. (2018). Fast QSTS for Distributed PV Impact Studies Using Vector Quantization and Variable Time-Steps. 1-5. Paper presented at 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018, Washington, United States. https://doi.org/10.1109/ISGT.2018.8403406, https://doi.org/10.1109/ISGT.2018.8403406

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abstract = "As the penetration level of PV systems increases, utilities are in great need of methods to quickly and effectively analyze PV's impact on electric distribution systems. Compared to other conventional methods, quasi-static time-series (QSTS) based analysis has demonstrated its advantages of accurately capturing the impact of interest, e.g. control device operations, and min and max voltages. However, yearlong QSTS simulation with 1-second granularity is currently too computationally expensive for regular use. Therefore, vector quantization (VQ) and variable time-step (VTS) solution methods have been developed to accelerate QSTS simulation. This paper proposes the combination of VQ with VTS. We investigate the effectiveness of implementing VQ in combination with 2 VTS algorithms, predetermined time-step (PT) and VTS with backtrack downsampling (VTS-BD) to demonstrate a runtime reduction of 99.55% with error metrics below acceptable thresholds.",

keywords = "Photovoltaic Systems, Power Distribution, Power System Analysis Computing, Power System Planning, QSTS, Vector Quantization",

author = "Barry Mather and Qinmiao Li and Jeremiah Deboever and Matthew Reno",

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Mather, B, Li, Q, Deboever, J & Reno, M 2018, 'Fast QSTS for Distributed PV Impact Studies Using Vector Quantization and Variable Time-Steps', Paper presented at 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018, Washington, United States, 19/02/18 - 22/02/18 pp. 1-5. https://doi.org/10.1109/ISGT.2018.8403406, https://doi.org/10.1109/ISGT.2018.8403406

TY - CONF

T1 - Fast QSTS for Distributed PV Impact Studies Using Vector Quantization and Variable Time-Steps

AU - Mather, Barry

AU - Li, Qinmiao

AU - Deboever, Jeremiah

AU - Reno, Matthew

PY - 2018/7/3

Y1 - 2018/7/3

N2 - As the penetration level of PV systems increases, utilities are in great need of methods to quickly and effectively analyze PV's impact on electric distribution systems. Compared to other conventional methods, quasi-static time-series (QSTS) based analysis has demonstrated its advantages of accurately capturing the impact of interest, e.g. control device operations, and min and max voltages. However, yearlong QSTS simulation with 1-second granularity is currently too computationally expensive for regular use. Therefore, vector quantization (VQ) and variable time-step (VTS) solution methods have been developed to accelerate QSTS simulation. This paper proposes the combination of VQ with VTS. We investigate the effectiveness of implementing VQ in combination with 2 VTS algorithms, predetermined time-step (PT) and VTS with backtrack downsampling (VTS-BD) to demonstrate a runtime reduction of 99.55% with error metrics below acceptable thresholds.

AB - As the penetration level of PV systems increases, utilities are in great need of methods to quickly and effectively analyze PV's impact on electric distribution systems. Compared to other conventional methods, quasi-static time-series (QSTS) based analysis has demonstrated its advantages of accurately capturing the impact of interest, e.g. control device operations, and min and max voltages. However, yearlong QSTS simulation with 1-second granularity is currently too computationally expensive for regular use. Therefore, vector quantization (VQ) and variable time-step (VTS) solution methods have been developed to accelerate QSTS simulation. This paper proposes the combination of VQ with VTS. We investigate the effectiveness of implementing VQ in combination with 2 VTS algorithms, predetermined time-step (PT) and VTS with backtrack downsampling (VTS-BD) to demonstrate a runtime reduction of 99.55% with error metrics below acceptable thresholds.

KW - Photovoltaic Systems

KW - Power Distribution

KW - Power System Analysis Computing

KW - Power System Planning

KW - QSTS

KW - Vector Quantization

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DO - 10.1109/ISGT.2018.8403406

M3 - Paper

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T2 - 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2018

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ER -

Fast QSTS for Distributed PV Impact Studies Using Vector Quantization and Variable Time-Steps

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Keywords

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