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Optimal Power Flow Using Particle Swarm Optimization Hybrid Inertia Weight and Constriction Factor Algorithm (PSOHIC) Case Study: Thermal Generator System of 150 kV Sulbagsel

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  • Muhammad Natsir Rahman

Abstract

The increasing use of electricity encourages electricity scientists to create or build mathematical models to improve the quality of electric power. This study uses IEEE 26 bus system data to validate the method and 150 kV thermal generator data from the South Sulawesi (Sulbagsel) system as a case study. The method used is PSOHIC. The simulation results for the 150 kV Sulbagsel system data show that PSOHIC converges more quickly, namely in the 8th iteration. The standard PSO converges at the 25th iteration. The IPSO algorithm converges at the 20th iteration. At the same time, the MIPSO algorithm converges at the 12th iteration. The power flow simulation results show that with PSOHIC, the power loss of 16.48 MW is smaller than the current system of 19.10 MW, that is, the power loss is reduced by 0.1613%. The production cost with PSOHIC is IDR 281,860.91/hour, cheaper than MIPSO, IPSO and PSO.

Suggested Citation

  • Muhammad Natsir Rahman, 2023. "Optimal Power Flow Using Particle Swarm Optimization Hybrid Inertia Weight and Constriction Factor Algorithm (PSOHIC) Case Study: Thermal Generator System of 150 kV Sulbagsel," Technium, Technium Science, vol. 17(1), pages 179-185.
    • Handle: RePEc:tec:techni:v:17:y:2023:i:1:p:179-185
    DOI: 10.47577/technium.v17i.10070
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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