Increasing distributed generation hosting capacity in distribution networks: A CO2emission analysis

Ozy D. Melgar-Dominguez, José R.S. Mantovani, Mahdi Pourakbari-Kasmaei, Matti Lehtonen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

4 Citations (Scopus)

Abstract

This work aims at proposing a strategy based on an environmental and technical perspective to assess the amount of distributed generation (DG) that can be deployed into an electric distribution network (EDN). The presented approach seeks to minimize the carbon emissions and energy losses while the installed capacity of renewable DG units is maximized. To enable the DG integration without requiring EDN upgrading, the operations of capacitor banks (CBs) and voltage regulators (VR) devices are optimized simultaneously. To analyze the relationship between the installed DG and demand consumption, the effects of voltage-dependent loads are investigated. Several test cases are studied in a 42-node distribution network. Results show that by applying operating actions and determining the hosting capacity of the EDN for deploying DG units, environmental and technical benefits could be achieved.

Original languageEnglish
Title of host publicationProceedings of 2020 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2020
PublisherIEEE
Pages1010-1014
Number of pages5
ISBN (Electronic)9781728171005
DOIs
Publication statusPublished - 26 Oct 2020
MoE publication typeA4 Article in a conference publication
EventIEEE PES Europe Conference on Innovative Smart Grid Technologies - Virtual, Online
Duration: 26 Oct 202028 Oct 2020

Publication series

NameIEEE PES Innovative Smart Grid Technologies Conference Europe
PublisherIEEE
ISSN (Print)2165-4816
ISSN (Electronic)2165-4824

Conference

ConferenceIEEE PES Europe Conference on Innovative Smart Grid Technologies
Abbreviated titleISGT Europe
CityVirtual, Online
Period26/10/202028/10/2020
OtherVirtual conference

Keywords

  • DG hosting capacity
  • Emissions reduction
  • Exponential demand model

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