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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Aswad Adib & Joao Onofre Pereira Pinto & Madhu S. Chinthavali, 2023. "GA-Based Voltage Optimization of Distribution Feeder with High-Penetration of DERs Using Megawatt-Scale Units," Energies, MDPI, vol. 16(13), pages 1-10, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4842-:d:1175947
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    References listed on IDEAS

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    1. Ouafa Laribi & Krzysztof Rudion, 2021. "Optimized Planning of Distribution Grids Considering Grid Expansion, Battery Systems and Dynamic Curtailment," Energies, MDPI, vol. 14(17), pages 1-27, August.
    2. Muhammad Riaz & Sadiq Ahmad & Irshad Hussain & Muhammad Naeem & Lucian Mihet-Popa, 2022. "Probabilistic Optimization Techniques in Smart Power System," Energies, MDPI, vol. 15(3), pages 1-39, January.
    3. Wei Wu & Shih-Chieh Chou & Karthickeyan Viswanathan, 2023. "Optimal Dispatching of Smart Hybrid Energy Systems for Addressing a Low-Carbon Community," Energies, MDPI, vol. 16(9), pages 1-19, April.
    4. Ahmed S. Menesy & Hamdy M. Sultan & Ibrahim O. Habiballah & Hasan Masrur & Kaisar R. Khan & Muhammad Khalid, 2023. "Optimal Configuration of a Hybrid Photovoltaic/Wind Turbine/Biomass/Hydro-Pumped Storage-Based Energy System Using a Heap-Based Optimization Algorithm," Energies, MDPI, vol. 16(9), pages 1-26, April.
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