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Title: Fast Determination of Distribution-Connected PV Impacts Using a Variable Time-Step Quasi-Static Time-Series Approach: Preprint

Abstract

The increasing deployment of distribution-connected photovoltaic (DPV) systems requires utilities to complete complex interconnection studies. Relatively simple interconnection study methods worked well for low penetrations of photovoltaic systems, but more complicated quasi-static time-series (QSTS) analysis is required to make better interconnection decisions as DPV penetration levels increase. Tools and methods must be developed to support this. This paper presents a variable-time-step solver for QSTS analysis that significantly shortens the computational time and effort to complete a detailed analysis of the operation of a distribution circuit with many DPV systems. Specifically, it demonstrates that the proposed variable-time-step solver can reduce the required computational time by as much as 84% without introducing any important errors to metrics, such as the highest and lowest voltage occurring on the feeder, number of voltage regulator tap operations, and total amount of losses realized in the distribution circuit during a 1-yr period. Further improvement in computational speed is possible with the introduction of only modest errors in these metrics, such as a 91 percent reduction with less than 5 percent error when predicting voltage regulator operations.

Authors:
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1377792
Report Number(s):
NREL/CP-5D00-67769
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2017 IEEE 44th Photovoltaic Specialists Conference (PVSC), 25-30 June 2017, Washington, DC
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; photovoltaic; PV; distribution; interconnectino; quasi-static time-series analysis; QSTS

Citation Formats

Mather, Barry. Fast Determination of Distribution-Connected PV Impacts Using a Variable Time-Step Quasi-Static Time-Series Approach: Preprint. United States: N. p., 2017. Web.
Mather, Barry. Fast Determination of Distribution-Connected PV Impacts Using a Variable Time-Step Quasi-Static Time-Series Approach: Preprint. United States.
Mather, Barry. Thu . "Fast Determination of Distribution-Connected PV Impacts Using a Variable Time-Step Quasi-Static Time-Series Approach: Preprint". United States. https://www.osti.gov/servlets/purl/1377792.
@article{osti_1377792,
title = {Fast Determination of Distribution-Connected PV Impacts Using a Variable Time-Step Quasi-Static Time-Series Approach: Preprint},
author = {Mather, Barry},
abstractNote = {The increasing deployment of distribution-connected photovoltaic (DPV) systems requires utilities to complete complex interconnection studies. Relatively simple interconnection study methods worked well for low penetrations of photovoltaic systems, but more complicated quasi-static time-series (QSTS) analysis is required to make better interconnection decisions as DPV penetration levels increase. Tools and methods must be developed to support this. This paper presents a variable-time-step solver for QSTS analysis that significantly shortens the computational time and effort to complete a detailed analysis of the operation of a distribution circuit with many DPV systems. Specifically, it demonstrates that the proposed variable-time-step solver can reduce the required computational time by as much as 84% without introducing any important errors to metrics, such as the highest and lowest voltage occurring on the feeder, number of voltage regulator tap operations, and total amount of losses realized in the distribution circuit during a 1-yr period. Further improvement in computational speed is possible with the introduction of only modest errors in these metrics, such as a 91 percent reduction with less than 5 percent error when predicting voltage regulator operations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {8}
}

Conference:
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