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Optimization of a Fuel Cost and Enrichment of Line Loadability for a Transmission System by Using Rapid Voltage Stability Index and Grey Wolf Algorithm Technique

Author

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  • Rambabu Muppidi

    (Department of Electrical and Electronics, GMR Institute of Technology, Rajam 532127, India)

  • Ramakrishna S. S. Nuvvula

    (Department of Electrical and Electronics, GMR Institute of Technology, Rajam 532127, India)

  • S. M. Muyeen

    (Department of Electrical Engineering, Qatar University, Doha 2713, Qatar)

  • SK. A. Shezan

    (Department of Electrical Engineering, Engineering Institute of Technology, Melbourne 3008, Australia
    Department of Electrical and Electronic Engineering, Green University of Bangladesh, Dhaka 1027, Bangladesh)

  • Md. Fatin Ishraque

    (Department of Electrical, Electronic and Communication Engineering, Pabna University of Science and Technology, Pabna 6600, Bangladesh)

Abstract

Efficient transmission of power is a pressing concern in modern power systems as it could relieve additional investments (e.g., right of way) and may improve stability. Non-uniform loading of transmission lines (which normally occurs due to the inefficient transmission of power) may lead to overloading of a few lines. These lines would then be prone to voltage instability. However, this problem would be aggravated under the network contingency condition. This paper focuses on improving the line loadability of the transmission system by considering the benchmark voltage stability index named rapid voltage stability index. The optimal loadability problem is considered using the grey wolf algorithm. The proposed work is implemented on a standard IEEE 30 bus test system using MATLAB software by addressing the problem by using line stability voltage index and grey wolf algorithm in optimal power flow. Minimizations of cost of generation, carbon emissions, voltage deviation, and line losses have been considered as objectives and improve the line loadability of the transmission system. The simulation results show that the proposed method is very effective in improving line loadability, reducing line congestion and fuel cost. Furthermore, the methodology is tested rigorously under various contingency conditions and is shown to be very effective. The proposed method relieves transmission line congestion and reduces fuel costs using the rapid voltage stability index (RVSI) is tested on an IEEE 30-bus standard test system utilizing MATLAB for various contingency lines

Suggested Citation

  • Rambabu Muppidi & Ramakrishna S. S. Nuvvula & S. M. Muyeen & SK. A. Shezan & Md. Fatin Ishraque, 2022. "Optimization of a Fuel Cost and Enrichment of Line Loadability for a Transmission System by Using Rapid Voltage Stability Index and Grey Wolf Algorithm Technique," Sustainability, MDPI, vol. 14(7), pages 1-19, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:4347-:d:788234
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    References listed on IDEAS

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    1. M. Rambabu & G. V. Nagesh Kumar & S. Sivanagaraju, 2019. "Optimal Power Flow of Integrated Renewable Energy System using a Thyristor Controlled SeriesCompensator and a Grey-Wolf Algorithm," Energies, MDPI, vol. 12(11), pages 1-18, June.
    2. Panda, Ambarish & Tripathy, M., 2015. "Security constrained optimal power flow solution of wind-thermal generation system using modified bacteria foraging algorithm," Energy, Elsevier, vol. 93(P1), pages 816-827.
    3. Talaat, M. & Farahat, M.A. & Mansour, Noura & Hatata, A.Y., 2020. "Load forecasting based on grasshopper optimization and a multilayer feed-forward neural network using regressive approach," Energy, Elsevier, vol. 196(C).
    4. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).
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    1. Alireza Pourdaryaei & Amidaddin Shahriari & Mohammad Mohammadi & Mohammad Reza Aghamohammadi & Mazaher Karimi & Kimmo Kauhaniemi, 2023. "A New Approach for Long-Term Stability Estimation Based on Voltage Profile Assessment for a Power Grid," Energies, MDPI, vol. 16(5), pages 1-21, March.

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