PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint

Wenbo Wang; Daniel Thom; Kwami Senam Sedzro; Sherin Ann Abraham; Yiyun Yao; Jianli Gu; Shibani Ghosh

PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint

Wenbo Wang, Daniel Thom, Kwami Senam Sedzro, Sherin Ann Abraham, Yiyun Yao, Jianli Gu, Shibani Ghosh

Research output: Contribution to conference › Paper

Abstract

Hosting capacity is an indication of the amount of photovoltaics (PV) can be hosted in a distribution system. This paper presents a framework for estimating distributed PV hosting capacity at scale. We first analyze the key challenges of performing relevant large scale simulation including computational and modeling challenges. Then, we develop two python-based software tools in order to conduct repeatable distribution analyses: Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations, and JADE for parallelizing jobs on HPC clusters. A case study of hosting capacity estimation for SMART-DS SFO 2000+ synthetic feeders is used to demonstrate the capability of the developed framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, through which the overall upgrade cost can be better planned in order to integrate more PV in the future.

Original language	American English
Number of pages	8
State	Published - 2022
Event	49th IEEE Photovoltaic Specialists Conference (PVSC 49) - Philadelphia, Pennsylvania Duration: 5 Jun 2022 → 10 Jun 2022

Conference

Conference	49th IEEE Photovoltaic Specialists Conference (PVSC 49)
City	Philadelphia, Pennsylvania
Period	5/06/22 → 10/06/22

Bibliographical note

See NREL/CP-6A40-85072 for paper as published in proceedings

NREL Publication Number

NREL/CP-6A40-81851

Keywords

distributed energy resources
hosting capacity
large-scale simulation

Access to Document

https://www.nrel.gov/docs/fy22osti/81851.pdf

Cite this

@conference{efa66ecfa90344f4bc57e54cde6d6e1f,

title = "PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint",

abstract = "Hosting capacity is an indication of the amount of photovoltaics (PV) can be hosted in a distribution system. This paper presents a framework for estimating distributed PV hosting capacity at scale. We first analyze the key challenges of performing relevant large scale simulation including computational and modeling challenges. Then, we develop two python-based software tools in order to conduct repeatable distribution analyses: Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations, and JADE for parallelizing jobs on HPC clusters. A case study of hosting capacity estimation for SMART-DS SFO 2000+ synthetic feeders is used to demonstrate the capability of the developed framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, through which the overall upgrade cost can be better planned in order to integrate more PV in the future.",

keywords = "distributed energy resources, hosting capacity, large-scale simulation",

author = "Wenbo Wang and Daniel Thom and Sedzro, {Kwami Senam} and Abraham, {Sherin Ann} and Yiyun Yao and Jianli Gu and Shibani Ghosh",

note = "See NREL/CP-6A40-85072 for paper as published in proceedings; 49th IEEE Photovoltaic Specialists Conference (PVSC 49) ; Conference date: 05-06-2022 Through 10-06-2022",

year = "2022",

language = "American English",

}

TY - CONF

T1 - PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint

AU - Wang, Wenbo

AU - Thom, Daniel

AU - Sedzro, Kwami Senam

AU - Abraham, Sherin Ann

AU - Yao, Yiyun

AU - Gu, Jianli

AU - Ghosh, Shibani

N1 - See NREL/CP-6A40-85072 for paper as published in proceedings

PY - 2022

Y1 - 2022

N2 - Hosting capacity is an indication of the amount of photovoltaics (PV) can be hosted in a distribution system. This paper presents a framework for estimating distributed PV hosting capacity at scale. We first analyze the key challenges of performing relevant large scale simulation including computational and modeling challenges. Then, we develop two python-based software tools in order to conduct repeatable distribution analyses: Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations, and JADE for parallelizing jobs on HPC clusters. A case study of hosting capacity estimation for SMART-DS SFO 2000+ synthetic feeders is used to demonstrate the capability of the developed framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, through which the overall upgrade cost can be better planned in order to integrate more PV in the future.

AB - Hosting capacity is an indication of the amount of photovoltaics (PV) can be hosted in a distribution system. This paper presents a framework for estimating distributed PV hosting capacity at scale. We first analyze the key challenges of performing relevant large scale simulation including computational and modeling challenges. Then, we develop two python-based software tools in order to conduct repeatable distribution analyses: Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations, and JADE for parallelizing jobs on HPC clusters. A case study of hosting capacity estimation for SMART-DS SFO 2000+ synthetic feeders is used to demonstrate the capability of the developed framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, through which the overall upgrade cost can be better planned in order to integrate more PV in the future.

KW - distributed energy resources

KW - hosting capacity

KW - large-scale simulation

M3 - Paper

T2 - 49th IEEE Photovoltaic Specialists Conference (PVSC 49)

Y2 - 5 June 2022 through 10 June 2022

ER -

PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint

Abstract

Conference

Bibliographical note

NREL Publication Number

Keywords

Access to Document

Fingerprint

Cite this