ADMS Test Bed: Defining a Use Case for Data Improvement for ADMS Deployment: Preprint

Santosh Veda; Murali Baggu; Annabelle Pratt

ADMS Test Bed: Defining a Use Case for Data Improvement for ADMS Deployment: Preprint

Santosh Veda, Murali Baggu, Annabelle Pratt

Research output: Contribution to conference › Paper

Abstract

Advanced distribution management systems (ADMS) provide a suite of tools for meeting the needs of a modern grid - higher reliability and power quality, improved resiliency and security, lower costs and enhanced customer participation. Data quality has two-fold impact on ADMS adoption: 1. Data quality improvement may constitute up to 25% of ADMS deployment costs. 2. The accuracy of data and models used by the ADMS greatly affect the utility's ability to meet the operational objectives. Thus, quantifying the data quality requirements and its impact on performance is critical to reducing the overall cost of deployment, enabling wider adoption and ensuring that the ADMS performs as specified. The paper offers the motivation, methodology and evaluation strategy for filling this critical gap.

Original language	American English
Number of pages	8
State	Published - 2019
Event	2019 IEEE Innovative Smart Grid Technologies Conference (IEEE ISGT) - Washington, D.C. Duration: 18 Feb 2019 → 21 Feb 2019

Conference

Conference	2019 IEEE Innovative Smart Grid Technologies Conference (IEEE ISGT)
City	Washington, D.C.
Period	18/02/19 → 21/02/19

Bibliographical note

See NREL/CP-5D00-74947 for paper as published in IEEE proceedings

NREL Publication Number

NREL/CP-5D00-72404

Keywords

ADMS
ADMS test bed
data quality
measurement density
performance

Access to Document

https://www.nrel.gov/docs/fy19osti/72404.pdf

Cite this

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title = "ADMS Test Bed: Defining a Use Case for Data Improvement for ADMS Deployment: Preprint",

abstract = "Advanced distribution management systems (ADMS) provide a suite of tools for meeting the needs of a modern grid - higher reliability and power quality, improved resiliency and security, lower costs and enhanced customer participation. Data quality has two-fold impact on ADMS adoption: 1. Data quality improvement may constitute up to 25% of ADMS deployment costs. 2. The accuracy of data and models used by the ADMS greatly affect the utility's ability to meet the operational objectives. Thus, quantifying the data quality requirements and its impact on performance is critical to reducing the overall cost of deployment, enabling wider adoption and ensuring that the ADMS performs as specified. The paper offers the motivation, methodology and evaluation strategy for filling this critical gap.",

keywords = "ADMS, ADMS test bed, data quality, measurement density, performance",

author = "Santosh Veda and Murali Baggu and Annabelle Pratt",

note = "See NREL/CP-5D00-74947 for paper as published in IEEE proceedings; 2019 IEEE Innovative Smart Grid Technologies Conference (IEEE ISGT) ; Conference date: 18-02-2019 Through 21-02-2019",

year = "2019",

language = "American English",

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TY - CONF

T1 - ADMS Test Bed: Defining a Use Case for Data Improvement for ADMS Deployment: Preprint

AU - Veda, Santosh

AU - Baggu, Murali

AU - Pratt, Annabelle

N1 - See NREL/CP-5D00-74947 for paper as published in IEEE proceedings

PY - 2019

Y1 - 2019

N2 - Advanced distribution management systems (ADMS) provide a suite of tools for meeting the needs of a modern grid - higher reliability and power quality, improved resiliency and security, lower costs and enhanced customer participation. Data quality has two-fold impact on ADMS adoption: 1. Data quality improvement may constitute up to 25% of ADMS deployment costs. 2. The accuracy of data and models used by the ADMS greatly affect the utility's ability to meet the operational objectives. Thus, quantifying the data quality requirements and its impact on performance is critical to reducing the overall cost of deployment, enabling wider adoption and ensuring that the ADMS performs as specified. The paper offers the motivation, methodology and evaluation strategy for filling this critical gap.

AB - Advanced distribution management systems (ADMS) provide a suite of tools for meeting the needs of a modern grid - higher reliability and power quality, improved resiliency and security, lower costs and enhanced customer participation. Data quality has two-fold impact on ADMS adoption: 1. Data quality improvement may constitute up to 25% of ADMS deployment costs. 2. The accuracy of data and models used by the ADMS greatly affect the utility's ability to meet the operational objectives. Thus, quantifying the data quality requirements and its impact on performance is critical to reducing the overall cost of deployment, enabling wider adoption and ensuring that the ADMS performs as specified. The paper offers the motivation, methodology and evaluation strategy for filling this critical gap.

KW - ADMS

KW - ADMS test bed

KW - data quality

KW - measurement density

KW - performance

M3 - Paper

T2 - 2019 IEEE Innovative Smart Grid Technologies Conference (IEEE ISGT)

Y2 - 18 February 2019 through 21 February 2019

ER -

ADMS Test Bed: Defining a Use Case for Data Improvement for ADMS Deployment: Preprint

Abstract

Conference

Bibliographical note

NREL Publication Number

Keywords

Access to Document

Fingerprint

Cite this