Optimized Settings of Droop Parameters Using Stochastic Load Modeling for Effective DC Microgrids Operation

Fatih Cingoz, Ali Elrayyah, Yilmaz Sozer

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Droop control is a widely used technique for load sharing in dc microgrids (MGs). However, it has an inherent limitation that leads to voltage deviations at the dc bus. More importantly, its current-sharing performance is degraded due to voltage drops across transmission line impedances. Depending on the amount of these voltage drops over the dc bus, droop control leads to different current-sharing errors and dc bus voltage degradations. Therefore, MG topology and loading conditions (LCs) have a considerable effect on current-sharing accuracy and voltage regulation. In this paper, an optimization procedure accounting all necessary information is introduced to find optimal droop parameters for the droop mechanism. First, a proper optimization problem is defined with required constraints and a cost function formulated as a summation of the current-sharing errors and the voltage degradations occurring at various LCs. Then, an optimization tool named as particle swarm is implemented to converge a satisfactory solution. During the computations, the cost impact of the current-sharing error at each LC is weighted based on the probability of occurrence of that LC, which is obtained from the stochastic load model for the considered MG. The effectiveness of the optimal droop parameters is verified through a simulation performed on MATLAB/Simulink and a dc MG test bench is prototyped for experimental validation.

Original languageEnglish
Article number7762882
Pages (from-to)1358-1371
Number of pages14
JournalIEEE Transactions on Industry Applications
Volume53
Issue number2
DOIs
Publication statusPublished - 1 Mar 2017

Fingerprint

Electric potential
Degradation
Cost functions
Voltage control
MATLAB
Electric lines
Topology
Costs
Voltage drop

Keywords

  • DC microgrid (MG)
  • droop control
  • droop parameter
  • optimization
  • stochastic model

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

Cite this

Optimized Settings of Droop Parameters Using Stochastic Load Modeling for Effective DC Microgrids Operation. / Cingoz, Fatih; Elrayyah, Ali; Sozer, Yilmaz.

In: IEEE Transactions on Industry Applications, Vol. 53, No. 2, 7762882, 01.03.2017, p. 1358-1371.

Research output: Contribution to journalArticle

@article{7b646fb455d0491b9cb93dfbe6cf3b0b,
title = "Optimized Settings of Droop Parameters Using Stochastic Load Modeling for Effective DC Microgrids Operation",
abstract = "Droop control is a widely used technique for load sharing in dc microgrids (MGs). However, it has an inherent limitation that leads to voltage deviations at the dc bus. More importantly, its current-sharing performance is degraded due to voltage drops across transmission line impedances. Depending on the amount of these voltage drops over the dc bus, droop control leads to different current-sharing errors and dc bus voltage degradations. Therefore, MG topology and loading conditions (LCs) have a considerable effect on current-sharing accuracy and voltage regulation. In this paper, an optimization procedure accounting all necessary information is introduced to find optimal droop parameters for the droop mechanism. First, a proper optimization problem is defined with required constraints and a cost function formulated as a summation of the current-sharing errors and the voltage degradations occurring at various LCs. Then, an optimization tool named as particle swarm is implemented to converge a satisfactory solution. During the computations, the cost impact of the current-sharing error at each LC is weighted based on the probability of occurrence of that LC, which is obtained from the stochastic load model for the considered MG. The effectiveness of the optimal droop parameters is verified through a simulation performed on MATLAB/Simulink and a dc MG test bench is prototyped for experimental validation.",
keywords = "DC microgrid (MG), droop control, droop parameter, optimization, stochastic model",
author = "Fatih Cingoz and Ali Elrayyah and Yilmaz Sozer",
year = "2017",
month = "3",
day = "1",
doi = "10.1109/TIA.2016.2633538",
language = "English",
volume = "53",
pages = "1358--1371",
journal = "IEEE Transactions on Industry Applications",
issn = "0093-9994",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",

}

TY - JOUR

T1 - Optimized Settings of Droop Parameters Using Stochastic Load Modeling for Effective DC Microgrids Operation

AU - Cingoz, Fatih

AU - Elrayyah, Ali

AU - Sozer, Yilmaz

PY - 2017/3/1

Y1 - 2017/3/1

N2 - Droop control is a widely used technique for load sharing in dc microgrids (MGs). However, it has an inherent limitation that leads to voltage deviations at the dc bus. More importantly, its current-sharing performance is degraded due to voltage drops across transmission line impedances. Depending on the amount of these voltage drops over the dc bus, droop control leads to different current-sharing errors and dc bus voltage degradations. Therefore, MG topology and loading conditions (LCs) have a considerable effect on current-sharing accuracy and voltage regulation. In this paper, an optimization procedure accounting all necessary information is introduced to find optimal droop parameters for the droop mechanism. First, a proper optimization problem is defined with required constraints and a cost function formulated as a summation of the current-sharing errors and the voltage degradations occurring at various LCs. Then, an optimization tool named as particle swarm is implemented to converge a satisfactory solution. During the computations, the cost impact of the current-sharing error at each LC is weighted based on the probability of occurrence of that LC, which is obtained from the stochastic load model for the considered MG. The effectiveness of the optimal droop parameters is verified through a simulation performed on MATLAB/Simulink and a dc MG test bench is prototyped for experimental validation.

AB - Droop control is a widely used technique for load sharing in dc microgrids (MGs). However, it has an inherent limitation that leads to voltage deviations at the dc bus. More importantly, its current-sharing performance is degraded due to voltage drops across transmission line impedances. Depending on the amount of these voltage drops over the dc bus, droop control leads to different current-sharing errors and dc bus voltage degradations. Therefore, MG topology and loading conditions (LCs) have a considerable effect on current-sharing accuracy and voltage regulation. In this paper, an optimization procedure accounting all necessary information is introduced to find optimal droop parameters for the droop mechanism. First, a proper optimization problem is defined with required constraints and a cost function formulated as a summation of the current-sharing errors and the voltage degradations occurring at various LCs. Then, an optimization tool named as particle swarm is implemented to converge a satisfactory solution. During the computations, the cost impact of the current-sharing error at each LC is weighted based on the probability of occurrence of that LC, which is obtained from the stochastic load model for the considered MG. The effectiveness of the optimal droop parameters is verified through a simulation performed on MATLAB/Simulink and a dc MG test bench is prototyped for experimental validation.

KW - DC microgrid (MG)

KW - droop control

KW - droop parameter

KW - optimization

KW - stochastic model

UR - http://www.scopus.com/inward/record.url?scp=85018529764&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85018529764&partnerID=8YFLogxK

U2 - 10.1109/TIA.2016.2633538

DO - 10.1109/TIA.2016.2633538

M3 - Article

VL - 53

SP - 1358

EP - 1371

JO - IEEE Transactions on Industry Applications

JF - IEEE Transactions on Industry Applications

SN - 0093-9994

IS - 2

M1 - 7762882

ER -