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Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints

Author

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  • Thuan Thanh Nguyen

    (Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam)

  • Bach Hoang Dinh

    (Power System Optimization Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)

  • Thai Dinh Pham

    (Institute of Research and Development, Duy Tan University, Danang 550000, Vietnam)

  • Thang Trung Nguyen

    (Power System Optimization Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam)

Abstract

This paper presents a highly effective method of installing both capacitors and PV systems in distribution systems for the purpose of reducing total power loss in branches. Three study cases with the installation of one capacitor, two capacitors and three capacitors were implemented and then the optimal solutions were used to install one more photovoltaic (PV) system. One PV system with 20% active power of all loads and less than active power of all loads was tested for two different conditions: (1) with geography location constraint and (2) without geography location constraint for PV system placement. The results from two systems consisting of 33 and 69 nodes were obtained by using the Stochastic Fractal Search Optimization Algorithm (SFSOA). Simulation results show that this method can determine the appropriate location and size of capacitors to reduce the total power losses more effectively than other existing methods. Furthermore, the paper also demonstrates the real impact of using both capacitors and PV systems to reduce active power loss as well as improve the voltage profile of distribution systems. This paper also finds that if it is possible to place PV systems in all nodes in distribution systems, the benefit from reducing total loss is highly significant and the investment of PV system placement is highly encouraged. As a result, it is recommended that capacitors and PV systems be used in distribution networks, and we claim that two important factors of the installed components consisting of location and size can be determined effectively by using SFSOA.

Suggested Citation

  • Thuan Thanh Nguyen & Bach Hoang Dinh & Thai Dinh Pham & Thang Trung Nguyen, 2020. "Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7806-:d:416966
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    References listed on IDEAS

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    1. Bayat, A. & Bagheri, A., 2019. "Optimal active and reactive power allocation in distribution networks using a novel heuristic approach," Applied Energy, Elsevier, vol. 233, pages 71-85.
    2. Essam A. Al-Ammar & Ghazi A. Ghazi & Wonsuk Ko, 2018. "Impact of Ambient Temperature on Shunt Capacitor Placement in a Distorted Radial Distribution System," Energies, MDPI, vol. 11(6), pages 1-17, June.
    3. Thang Trung Nguyen & Thai Dinh Pham & Le Chi Kien & Le Van Dai, 2020. "Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems," Complexity, Hindawi, vol. 2020, pages 1-34, February.
    4. Reza Sirjani, 2017. "Optimal Capacitor Placement in Wind Farms by Considering Harmonics Using Discrete Lightning Search Algorithm," Sustainability, MDPI, vol. 9(9), pages 1-20, September.
    5. Nguyen, Thang Trung & Vo, Dieu Ngoc & Dinh, Bach Hoang, 2018. "An effectively adaptive selective cuckoo search algorithm for solving three complicated short-term hydrothermal scheduling problems," Energy, Elsevier, vol. 155(C), pages 930-956.
    6. Damir Jakus & Rade Čađenović & Josip Vasilj & Petar Sarajčev, 2020. "Optimal Reconfiguration of Distribution Networks Using Hybrid Heuristic-Genetic Algorithm," Energies, MDPI, vol. 13(7), pages 1-21, March.
    7. Shanghua Guo & Jian Lin & Yuming Zhao & Longjun Wang & Gang Wang & Guowei Liu, 2020. "A Reliability-Based Network Reconfiguration Model in Distribution System with DGs and ESSs Using Mixed-Integer Programming," Energies, MDPI, vol. 13(5), pages 1-15, March.
    8. Chandan Kishore & Smarajit Ghosh & Vinod Karar, 2018. "Symmetric Fuzzy Logic and IBFOA Solutions for Optimal Position and Rating of Capacitors Allocated to Radial Distribution Networks," Energies, MDPI, vol. 11(4), pages 1-14, March.
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    Cited by:

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    2. Illia Diahovchenko & Lubov Petrichenko, 2022. "Comparative Analysis of Power Distribution Systems with Individual Prosumers Owing Photovoltaic Installations and Solar Energy Communities in Terms of Profitability and Hosting Capacity," Energies, MDPI, vol. 15(23), pages 1-20, November.
    3. Zbigniew Kłosowski & Łukasz Mazur, 2023. "Influence of the Type of Receiver on Electrical Energy Losses in Power Grids," Energies, MDPI, vol. 16(15), pages 1-22, July.
    4. Hasan M. Salman & Jagadeesh Pasupuleti & Ahmad H. Sabry, 2023. "Review on Causes of Power Outages and Their Occurrence: Mitigation Strategies," Sustainability, MDPI, vol. 15(20), pages 1-34, October.

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