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Optimal Power Flow of Integrated Renewable Energy System using a Thyristor Controlled SeriesCompensator and a Grey-Wolf Algorithm

Author

Listed:
  • M. Rambabu

    (Department of EEE, GMR Institute of Technology Rajam, Rajam, AP 532127, India)

  • G. V. Nagesh Kumar

    (Department of EEE, JNTUA CE Pulivendula, Pulivendula, AP 516390, India)

  • S. Sivanagaraju

    (Department of EEE, JNTUK Kakinada, Kakinada, AP 533001, India)

Abstract

Inrecent electrical power networks a number of failures due to overloading of the transmission lines, stability problems, mismatch in supply and demand, narrow scope for expanding the transmission network and other issues like global warming, environmental conditions, etc. have been noticed. In this paper, a thyristor-controlled series compensator (TCSC) is placed at the optimum position by using two indices for enhancing the power flows as well as the voltage security and power quality of the integrated system. A fusedseverity index is proposed for the optimal positionalong with a grey wolf algorithm-based optimal tuning of the TCSC for reduction of real power losses, fuel cost with valve-point effect, carbon emissions, and voltage deviation in a modern electrical network. The voltage stability index to evaluate the power flow of the line and a novel line stability indexto assessthe line capacityare used. The TCSC is placed at the highest value of the fusedseverity index. In addition, an intermittent severity index (IMSI) is used to find the most severely affected line and is used for relocating the TCSC to a better location under different contingencies.Lognormal and Weibull probability density functions (PDFs)are utilized forassessing the output ofphotovoltaic (PV) and wind power. The proposed methodhas been implemented on the IEEE 57 bus system to validate the methodology, and the results of the integrated system with and without TCSC are comparedunder normal and contingency conditions.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2215-:d:238780
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    References listed on IDEAS

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    1. Weisi Deng & Buhan Zhang & Hongfa Ding & Hang Li, 2017. "Risk-Based Probabilistic Voltage Stability Assessment in Uncertain Power System," Energies, MDPI, vol. 10(2), pages 1-19, February.
    2. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    3. Sichilalu, Sam & Mathaba, Tebello & Xia, Xiaohua, 2017. "Optimal control of a wind–PV-hybrid powered heat pump water heater," Applied Energy, Elsevier, vol. 185(P2), pages 1173-1184.
    4. Modarresi, Javad & Gholipour, Eskandar & Khodabakhshian, Amin, 2016. "A comprehensive review of the voltage stability indices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 1-12.
    5. B. Venkateswara Rao & G.V. Nagesh Kumar, 2015. "A Comparative Study of BAT and Firefly Algorithms for Optimal Placement and Sizing of Static VAR Compensator for Enhancement of Voltage Stability," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 4(1), pages 68-84, January.
    6. Eleonora Riva Sanseverino & Maria Luisa Di Silvestre & Romina Badalamenti & Ninh Quang Nguyen & Josep Maria Guerrero & Lexuan Meng, 2015. "Optimal Power Flow in Islanded Microgrids Using a Simple Distributed Algorithm," Energies, MDPI, vol. 8(10), pages 1-22, October.
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    Cited by:

    1. 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.
    2. Khaled Nusair & Lina Alhmoud, 2020. "Application of Equilibrium Optimizer Algorithm for Optimal Power Flow with High Penetration of Renewable Energy," Energies, MDPI, vol. 13(22), pages 1-35, November.

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