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Title: Novel Methods to Determine Feeder Locational PV Hosting Capacity and PV Impact Signatures

Abstract

Often PV hosting capacity analysis is performed for a limited number of distribution feeders. For medium - voltage distribution feeders, previous results generally analyze less than 20 feeders, and then the results are extrapolated out to similar types of feeders. Previous hosting capacity research has often focused on determining a single value for the hosting capacity for the entire feeder, whereas this research expands previous hosting capacity work to investigate all the regions of the feeder that may allow many different hosting capacity values wit h an idea called locational hosting capacity (LHC)to determine the largest PV size that can be interconnected at different locations (buses) on the study feeders. This report discusses novel methods for analyzing PV interconnections with advanced simulati on methods. The focus is feeder and location - specific impacts of PV that determine the locational PV hosting capacity. Feeder PV impact signature are used to more precisely determine the local maximum hosting capacity of individual areas of the feeder. T he feeder signature provides improved interconnection screening with certain zones that show the risk of impact to the distribution feeder from PV interconnections.

Authors:
 [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1367426
Report Number(s):
SAND2017-4954
653194
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
30 DIRECT ENERGY CONVERSION

Citation Formats

Reno, Matthew J., Coogan, Kyle, Seuss, John, and Broderick, Robert Joseph. Novel Methods to Determine Feeder Locational PV Hosting Capacity and PV Impact Signatures. United States: N. p., 2017. Web. doi:10.2172/1367426.
Reno, Matthew J., Coogan, Kyle, Seuss, John, & Broderick, Robert Joseph. Novel Methods to Determine Feeder Locational PV Hosting Capacity and PV Impact Signatures. United States. doi:10.2172/1367426.
Reno, Matthew J., Coogan, Kyle, Seuss, John, and Broderick, Robert Joseph. Mon . "Novel Methods to Determine Feeder Locational PV Hosting Capacity and PV Impact Signatures". United States. doi:10.2172/1367426. https://www.osti.gov/servlets/purl/1367426.
@article{osti_1367426,
title = {Novel Methods to Determine Feeder Locational PV Hosting Capacity and PV Impact Signatures},
author = {Reno, Matthew J. and Coogan, Kyle and Seuss, John and Broderick, Robert Joseph},
abstractNote = {Often PV hosting capacity analysis is performed for a limited number of distribution feeders. For medium - voltage distribution feeders, previous results generally analyze less than 20 feeders, and then the results are extrapolated out to similar types of feeders. Previous hosting capacity research has often focused on determining a single value for the hosting capacity for the entire feeder, whereas this research expands previous hosting capacity work to investigate all the regions of the feeder that may allow many different hosting capacity values wit h an idea called locational hosting capacity (LHC)to determine the largest PV size that can be interconnected at different locations (buses) on the study feeders. This report discusses novel methods for analyzing PV interconnections with advanced simulati on methods. The focus is feeder and location - specific impacts of PV that determine the locational PV hosting capacity. Feeder PV impact signature are used to more precisely determine the local maximum hosting capacity of individual areas of the feeder. T he feeder signature provides improved interconnection screening with certain zones that show the risk of impact to the distribution feeder from PV interconnections.},
doi = {10.2172/1367426},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2017},
month = {Mon May 01 00:00:00 EDT 2017}
}

Technical Report:

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