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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:
 [1];  [1];  [2]
  1. The Univ. of Texas at San Antonio, San Antonio, TX (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
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.
Bazrafshan, Mohammadhafez, Gatsis, Nikolaos, & Dall'Anese, Emiliano. Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks. United States. doi:10.1109/TPWRS.2018.2871377.
Bazrafshan, Mohammadhafez, Gatsis, Nikolaos, and Dall'Anese, Emiliano. Thu . "Placement and Sizing of Inverter-Based Renewable Systems in Multi-Phase Distribution Networks". United States. doi:10.1109/TPWRS.2018.2871377. https://www.osti.gov/servlets/purl/1476708.
@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 = {2018},
month = {9}
}

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