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A Quasi-Oppositional Heap-Based Optimization Technique for Power Flow Analysis by Considering Large Scale Photovoltaic Generator

Author

Listed:
  • Vedik Basetti

    (Department of Electrical and Electronics Engineering, SR University, Warangal 506371, India)

  • Shriram S. Rangarajan

    (Department of Electrical and Electronics Engineering, SR University, Warangal 506371, India
    Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA)

  • Chandan Kumar Shiva

    (Department of Electrical and Electronics Engineering, SR University, Warangal 506371, India)

  • Sumit Verma

    (Department of Industrial and Management Engineering, IIT Kanpur, Kanpur 208016, India)

  • Randolph E. Collins

    (Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA)

  • Tomonobu Senjyu

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

Abstract

Load flow analysis is an essential tool for the reliable planning and operation of interconnected power systems. The constant increase in power demand, apart from the increased intermittency in power generation due to renewable energy sources without proportionate augmentation in transmission system infrastructure, has driven the power systems to function nearer to their limits. Though the power flow (PF) solution may exist in such circumstances, the traditional Newton–Raphson based PF techniques may fail due to computational difficulties owing to the singularity of the Jacobian Matrix during critical conditions and faces difficulties in solving ill-conditioned systems. To address these problems and to assess the impact of large-scale photovoltaic generator (PVG) integration in power systems on power flow studies, a derivative-free quasi-oppositional heap-based optimization (HBO) (QOHBO) technique is proposed in the present paper. In the proposed approach, the concept of quasi-oppositional learning is applied to HBO to enhance the convergence speed. The efficacy and effectiveness of the proposed QOHBO-PF technique are verified by applying it to the standard IEEE and ill-conditioned systems. The robustness of the algorithm is validated under the maximum loadability limits and high R/X ratios, comparing the results with other well-known methods suggested in the literature. The results thus obtained show that the proposed QOHBO-PF technique has less computation time, further enhancement of reliability in the presence of PVG, and has the ability to provide multiple PF solutions that can be utilized for voltage stability analysis.

Suggested Citation

  • Vedik Basetti & Shriram S. Rangarajan & Chandan Kumar Shiva & Sumit Verma & Randolph E. Collins & Tomonobu Senjyu, 2021. "A Quasi-Oppositional Heap-Based Optimization Technique for Power Flow Analysis by Considering Large Scale Photovoltaic Generator," Energies, MDPI, vol. 14(17), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5382-:d:625056
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    References listed on IDEAS

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    1. HyungSeon Oh, 2019. "A Unified and Efficient Approach to Power Flow Analysis," Energies, MDPI, vol. 12(12), pages 1-20, June.
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    Cited by:

    1. Mohammed Hamouda Ali & Ahmed Tijani Salawudeen & Salah Kamel & Habeeb Bello Salau & Monier Habil & Mokhtar Shouran, 2022. "Single- and Multi-Objective Modified Aquila Optimizer for Optimal Multiple Renewable Energy Resources in Distribution Network," Mathematics, MDPI, vol. 10(12), pages 1-39, June.

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