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Optimal Allocation of Static Var Compensators in Electric Power Systems

Author

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  • Martin Ćalasan

    (Faculty of Electrical Engineering, University of Montenegro, 81000 Podgorica, Montenegro)

  • Tatjana Konjić

    (Faculty of Electrical Engineering, University of Sarajevo, 71000 Sarajevo, Bosna and Herzegovina)

  • Katarina Kecojević

    (Faculty of Electrical Engineering, University of Montenegro, 81000 Podgorica, Montenegro)

  • Lazar Nikitović

    (Faculty of Electrical Engineering, University of Montenegro, 81000 Podgorica, Montenegro)

Abstract

In the current age, power systems contain many modern elements, one example being Flexible AC Transmission System (FACTS) devices, which play an important role in enhancing the static and dynamic performance of the systems. However, due to the high costs of FACTS devices, the location, type, and value of the reactive power of these devices must be optimized to maximize their resulting benefits. In this paper, the problem of optimal power flow for the minimization of power losses is considered for a power system with or without a FACTS controller, such as a Static Var Compensator (SVC) device The impact of location and SVC reactive power values on power system losses are considered in power systems with and without the presence of wind power. Furthermore, constant and variable load are considered. The mentioned investigation is realized on both IEEE 9 and IEEE 30 test bus systems. Optimal SVC allocation are performed in program GAMS using CONOPT solver. For constant load data, the obtained results of an optimal SVC allocation and the minimal value of power losses are compared with known solutions from the literature. It is shown that the CONOPT solver is useful for finding the optimal location of SVC devices in a power system with or without the presence of wind energy. The comparison of results obtained using CONOPT solver and four metaheuristic method for minimization of power system losses are also investigated and presented.

Suggested Citation

  • Martin Ćalasan & Tatjana Konjić & Katarina Kecojević & Lazar Nikitović, 2020. "Optimal Allocation of Static Var Compensators in Electric Power Systems," Energies, MDPI, vol. 13(12), pages 1-24, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3219-:d:374391
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    References listed on IDEAS

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    1. Neculai Andrei, 2017. "Applications of Continuous Nonlinear Optimization," Springer Optimization and Its Applications, in: Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology, chapter 0, pages 47-117, Springer.
    2. Muhammad Nadeem & Kashif Imran & Abraiz Khattak & Abasin Ulasyar & Anamitra Pal & Muhammad Zulqarnain Zeb & Atif Naveed Khan & Malhar Padhee, 2020. "Optimal Placement, Sizing and Coordination of FACTS Devices in Transmission Network Using Whale Optimization Algorithm," Energies, MDPI, vol. 13(3), pages 1-24, February.
    3. Narimani, Mohammad Rasoul & Azizipanah-Abarghooee, Rasoul & Zoghdar-Moghadam-Shahrekohne, Behrouz & Gholami, Kayvan, 2013. "A novel approach to multi-objective optimal power flow by a new hybrid optimization algorithm considering generator constraints and multi-fuel type," Energy, Elsevier, vol. 49(C), pages 119-136.
    4. Warid Warid & Hashim Hizam & Norman Mariun & Noor Izzri Abdul-Wahab, 2016. "Optimal Power Flow Using the Jaya Algorithm," Energies, MDPI, vol. 9(9), pages 1-18, August.
    5. Ismael, Sherif M. & Abdel Aleem, Shady H.E. & Abdelaziz, Almoataz Y. & Zobaa, Ahmed F., 2019. "State-of-the-art of hosting capacity in modern power systems with distributed generation," Renewable Energy, Elsevier, vol. 130(C), pages 1002-1020.
    6. Junli Deng & Yuan Mao & Yun Yang, 2020. "Distribution Power Loss Reduction of Standalone DC Microgrids Using Adaptive Differential Evolution-Based Control for Distributed Battery Systems," Energies, MDPI, vol. 13(9), pages 1-15, April.
    7. Neculai Andrei, 2017. "Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology," Springer Optimization and Its Applications, Springer, number 978-3-319-58356-3, June.
    8. Xuanhu He & Wei Wang & Jiuchun Jiang & Lijie Xu, 2015. "An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow," Energies, MDPI, vol. 8(4), pages 1-26, March.
    9. Savić, Aleksandar & Đurišić, Željko, 2014. "Optimal sizing and location of SVC devices for improvement of voltage profile in distribution network with dispersed photovoltaic and wind power plants," Applied Energy, Elsevier, vol. 134(C), pages 114-124.
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