Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks

Bazrafshan, Mohammadhafez; Gatsis, Nikolaos; Dall'Anese, Emiliano

doi:10.1109/TPWRS.2018.2871377

Title: Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks

Abstract

This study develops a tractable formulation for optimal placement and sizing of inverter-based renewable systems in multi-phase distribution networks. The goal of the formulation is to minimize the cost of inverter installation, average power import, and average distributed generation curtailment. Threephase and single-phase inverter models are presented that preserve the underlying mappings between renewable uncertainty to power injection. The uncertainty of distributed generators (DGs) and loads are characterized by a finite set of scenarios. Linear multi-phase power flow approximations are used in conjunction with scenario reduction techniques to arrive at a tractable twostage stochastic formulation for optimal DG placement and sizing. First-stage decisions are locations for DG deployment and capacity sizes, and second-stage decisions include DG real power curtailment, reactive power support, as well as feeder voltage profile. The resulting formulation is a mixed-integer second-order cone program and can be solved efficiently either by existing optimization solvers or by relaxing the binary variables to the [0,1] interval. Simulation studies on standard multi-phase IEEE test feeders promise that optimal stochastic planning of DGs reduces costs during validation, compared to a scheme where uncertainty is only represented by its average value.

Authors:

Bazrafshan, Mohammadhafez ^[1]; Gatsis, Nikolaos ^[1]; Dall'Anese, Emiliano ^[2]

The Univ. of Texas at San Antonio, San Antonio, TX (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States)

Publication Date:: Thu Sep 20 00:00:00 EDT 2018

Research Org.:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Org.:: USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:: 1476708

Report Number(s):: NREL/JA-5D00-70143
Journal ID: ISSN 0885-8950

Grant/Contract Number:: AC36-08GO28308

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Power Systems

Additional Journal Information:: Journal Volume: 34; Journal Issue: 2; Journal ID: ISSN 0885-8950

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 24 POWER TRANSMISSION AND DISTRIBUTION; placement and sizing of distributed generators; distribution networks; multi-phase power flow; mixed-integer second order cone program; scenario reduction

Citation Formats


                    Bazrafshan, Mohammadhafez, Gatsis, Nikolaos, and Dall'Anese, Emiliano. Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks.  United States: N. p., 2018. 
Web.  doi:10.1109/TPWRS.2018.2871377.

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                    Bazrafshan, Mohammadhafez, Gatsis, Nikolaos, & Dall'Anese, Emiliano. Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks.  United States.  https://doi.org/10.1109/TPWRS.2018.2871377

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                    Bazrafshan, Mohammadhafez, Gatsis, Nikolaos, and Dall'Anese, Emiliano. Thu .  
"Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks".  United States.  https://doi.org/10.1109/TPWRS.2018.2871377.  https://www.osti.gov/servlets/purl/1476708.

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@article{osti_1476708,

  title        = {Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks},

  author       = {Bazrafshan, Mohammadhafez and Gatsis, Nikolaos and Dall'Anese, Emiliano},

  abstractNote = {This study develops a tractable formulation for optimal placement and sizing of inverter-based renewable systems in multi-phase distribution networks. The goal of the formulation is to minimize the cost of inverter installation, average power import, and average distributed generation curtailment. Threephase and single-phase inverter models are presented that preserve the underlying mappings between renewable uncertainty to power injection. The uncertainty of distributed generators (DGs) and loads are characterized by a finite set of scenarios. Linear multi-phase power flow approximations are used in conjunction with scenario reduction techniques to arrive at a tractable twostage stochastic formulation for optimal DG placement and sizing. First-stage decisions are locations for DG deployment and capacity sizes, and second-stage decisions include DG real power curtailment, reactive power support, as well as feeder voltage profile. The resulting formulation is a mixed-integer second-order cone program and can be solved efficiently either by existing optimization solvers or by relaxing the binary variables to the [0,1] interval. Simulation studies on standard multi-phase IEEE test feeders promise that optimal stochastic planning of DGs reduces costs during validation, compared to a scheme where uncertainty is only represented by its average value.},

  doi          = {10.1109/TPWRS.2018.2871377},

  journal      = {IEEE Transactions on Power Systems},

  number       = 2,

  volume       = 34,

  place        = {United States},

  year         = {Thu Sep 20 00:00:00 EDT 2018},

  month        = {Thu Sep 20 00:00:00 EDT 2018}

}

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https://doi.org/10.1109/TPWRS.2018.2871377

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Cited by: 18 works

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Fig. 1: Optimization and validation steps.

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Works referencing / citing this record:

Optimal allocation of distributed generations using hybrid technique with fuzzy logic controller radial distribution system
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Stochastic Planning of Distributed PV Generation
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Bazrafshan, Mohammadhafez; Yalamanchili, Likhitha; Gatsis, Nikolaos
Energies, Vol. 12, Issue 3
DOI: 10.3390/en12030459

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