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

Aswad Adib, Joao Onofre Pereira Pinto () and Madhu S. Chinthavali
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Aswad Adib: Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Joao Onofre Pereira Pinto: Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Madhu S. Chinthavali: Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA

Energies, 2023, vol. 16, issue 13, 1-10

Abstract: 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.

Keywords: high-penetration of DERs; GA-based optimization; megawatt-scale reactive power units; multi-platform simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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