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Advanced Pareto Front Non-Dominated Sorting Multi-Objective Particle Swarm Optimization for Optimal Placement and Sizing of Distributed Generation

Author

Listed:
  • Kumar Mahesh

    (Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia)

  • Perumal Nallagownden

    (Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia)

  • Irraivan Elamvazuthi

    (Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia)

Abstract

This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. The distributed generation consists of single and multiple numbers of active power DG, reactive power DG and simultaneous placement of active-reactive power DG. The optimization problem considers two multi-objective functions, i.e., power loss reduction and voltage stability improvements with voltage profile and power balance as constraints. First, the numerical output results of objective functions are obtained in the Pareto-optimal set. Later, fuzzy decision model is engendered for final selection of the compromised solution. The proposed method is employed and tested on standard IEEE 33 bus systems. Moreover, the results of proposed method are validated with other optimization algorithms as reported by others in the literature. The overall outcome shows that the proposed method for optimal placement and sizing gives higher capability and effectiveness to the final solution. The study also reveals that simultaneous placement of active-reactive power DG reduces more power losses, increases voltage stability and voltage profile of the system.

Suggested Citation

  • Kumar Mahesh & Perumal Nallagownden & Irraivan Elamvazuthi, 2016. "Advanced Pareto Front Non-Dominated Sorting Multi-Objective Particle Swarm Optimization for Optimal Placement and Sizing of Distributed Generation," Energies, MDPI, vol. 9(12), pages 1-23, November.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:12:p:982-:d:83769
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    References listed on IDEAS

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    1. Prakash, Prem & Khatod, Dheeraj K., 2016. "Optimal sizing and siting techniques for distributed generation in distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 111-130.
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    Cited by:

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    2. Xiaofeng Lv & Deyun Zhou & Yongchuan Tang & Ling Ma, 2018. "An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    3. Seyed Siavash Karimi Madahi & Andrija T. Sarić, 2020. "Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations," Energies, MDPI, vol. 13(20), pages 1-22, October.
    4. Mahesh Kumar & Perumal Nallagownden & Irraivan Elamvazuthi, 2017. "Optimal Placement and Sizing of Renewable Distributed Generations and Capacitor Banks into Radial Distribution Systems," Energies, MDPI, vol. 10(6), pages 1-25, June.
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    7. Navdeep Kaur & Sanjay Kumar Jain, 2017. "Multi-Objective Optimization Approach for Placement of Multiple DGs for Voltage Sensitive Loads," Energies, MDPI, vol. 10(11), pages 1-17, October.
    8. Elnazeer Ali Hamid Abdalla & Perumal Nallagownden & Nursyarizal Bin Mohd Nor & Mohd Fakhizan Romlie & Sabo Miya Hassan, 2018. "An Application of a Novel Technique for Assessing the Operating Performance of Existing Cooling Systems on a University Campus," Energies, MDPI, vol. 11(4), pages 1-24, March.

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