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GA-Based Voltage Optimization of Distribution Feeder with High-Penetration of DERs Using Megawatt-Scale Units

Journal Article · · Energies
DOI:https://doi.org/10.3390/en16134842· OSTI ID:1987765
 [1];  [1];  [1]
  1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

In this paper, genetic algorithm (GA)-based voltage optimization of a modified IEEE-34 node distribution feeder with high penetration of distributed energy resources (DERs) is proposed using two megawatt-scale reactive power sources. Traditional voltage support units present in distribution grids are not suitable for DER-rich feeders, while voltage support using small-scale DERs present in the feeder requires considerable communication effort to reach a global solution. In this work, two megawatt-scale units are placed to improve the voltage profile across the IEEE 34-node feeder, which has been modified to include several PV units and an energy storage unit. The megawatt-scale units are optimized using GA for fast and accurate operation. The performance of the proposed scheme is verified using simulation results with a multi-platform setup where the modified IEEE-34 node feeder is modeled in OpenDSS while the GA optimization scheme is programmed in MATLAB.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Electricity (OE)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1987765
Journal Information:
Energies, Journal Name: Energies Journal Issue: 13 Vol. 16; ISSN 1996-1073
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English

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