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Minimization of Active Power Loss Using Enhanced Particle Swarm Optimization

Author

Listed:
  • Samson Ademola Adegoke

    (Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa)

  • Yanxia Sun

    (Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa)

  • Zenghui Wang

    (Department of Electrical Engineering, University of South Africa, Florida 1709, South Africa)

Abstract

Identifying the weak buses in power system networks is crucial for planning and operation since most generators operate close to their operating limits, resulting in generator failures. This work aims to identify the critical/weak node and reduce the system’s power loss. The line stability index ( L m n ) and fast voltage stability index (FVSI) were used to identify the critical node and lines close to instability in the power system networks. Enhanced particle swarm optimization (EPSO) was chosen because of its ability to communicate with better individuals, making it more efficient to obtain a prominent solution. EPSO and other PSO variants minimized the system’s actual/real losses. Nodes 8 and 14 were identified as the critical nodes of the IEEE 9 and 14 bus systems, respectively. The power loss of the IEEE 9 bus system was reduced from 9.842 MW to 7.543 MW, and for the IEEE 14 bus system, the loss was reduced from 13.775 MW of the base case to 12.253 MW for EPSO. EPSO gives a better active power loss reduction and improves the node’s voltage profile than other PSO variants and algorithms in the literature. This suggests the feasibility and suitability of EPSO to improve the grid voltage quality.

Suggested Citation

  • Samson Ademola Adegoke & Yanxia Sun & Zenghui Wang, 2023. "Minimization of Active Power Loss Using Enhanced Particle Swarm Optimization," Mathematics, MDPI, vol. 11(17), pages 1-17, August.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3660-:d:1224504
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    References listed on IDEAS

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    1. Samson Ademola Adegoke & Yanxia Sun, 2023. "Diminishing Active Power Loss and Improving Voltage Profile Using an Improved Pathfinder Algorithm Based on Inertia Weight," Energies, MDPI, vol. 16(3), pages 1-14, January.
    2. Mini Vishnu & Sunil Kumar T. K., 2020. "An Improved Solution for Reactive Power Dispatch Problem Using Diversity-Enhanced Particle Swarm Optimization," Energies, MDPI, vol. 13(11), pages 1-21, June.
    3. Shengrang Cao & Xiaoqun Ding & Qingyan Wang & Bingyan Chen, 2015. "Opposition-Based Improved PSO for Optimal Reactive Power Dispatch and Voltage Control," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-8, June.
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    Cited by:

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    2. Rabea Jamil Mahfoud & Nizar Faisal Alkayem & Emmanuel Fernandez-Rodriguez & Yuan Zheng & Yonghui Sun & Shida Zhang & Yuquan Zhang, 2024. "Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks," Mathematics, MDPI, vol. 12(2), pages 1-33, January.

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