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Operational Cost Minimization of Electrical Distribution Network during Switching for Sustainable Operation

Author

Listed:
  • Hamza Mubarak

    (Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Munir Azam Muhammad

    (Department of Electrical Engineering, Main Campus, Iqra University, Karachi 75300, Pakistan)

  • Nurulafiqah Nadzirah Mansor

    (Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Hazlie Mokhlis

    (Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Shameem Ahmad

    (Power Electronics and Renewable Energy Research Laboratory, Department of Electrical Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Tofael Ahmed

    (Department of Electrical & Electronic Engineering, Chittagong University of Engineering & Technology, Chittagong 4349, Bangladesh)

  • Muhammad Sufyan

    (Department of Electrical Engineering, Main Campus, Iqra University, Karachi 75300, Pakistan)

Abstract

Continuous increases in electrical energy demand and the deregulation of power systems have forced utility companies to provide high-quality and reliable services to maintain a sustainable operation and reduce electricity price. One way to continue providing the required services while simultaneously reducing operational costs is through minimizing power losses and voltage deviation in the distribution network. For this purpose, Network Reconfiguration (NR) is commonly adopted by employing the switching operation to enhance overall system performance. In the past, work proposed by researchers to attain switching sequence operation was based on hamming distance approach. This approach caused the search space to grow with the increase in total Hamming distance between the initial and the final configuration. Therefore, a method is proposed in this paper utilizing a Mixed Integer Second Order Cone Programming (MISOCP) to attain optimal NR to address this issue. The Hamming dataset approach is opted to reduce search space by considering only radial configuration solutions to achieve an optimal switching sequence. In addition, a detailed economic analysis has been performed to determine the saving after the implementation of the proposed switching sequence. The effectiveness of the proposed technique is validated through simulations on IEEE 33-bus distribution network and a practical 71-bus network in Malaysia. The result shows that the proposed method determined the optimal network configuration by minimizing the power losses for the 33 bus and 71-bus system by 34.14% and 25.5% from their initial configuration, respectively to maintain sustainable operation.

Suggested Citation

  • Hamza Mubarak & Munir Azam Muhammad & Nurulafiqah Nadzirah Mansor & Hazlie Mokhlis & Shameem Ahmad & Tofael Ahmed & Muhammad Sufyan, 2022. "Operational Cost Minimization of Electrical Distribution Network during Switching for Sustainable Operation," Sustainability, MDPI, vol. 14(7), pages 1-23, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:4196-:d:785049
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    References listed on IDEAS

    as
    1. Hamza Mubarak & Nurulafiqah Nadzirah Mansor & Hazlie Mokhlis & Mahazani Mohamad & Hasmaini Mohamad & Munir Azam Muhammad & Mohammad Al Samman & Suhail Afzal, 2021. "Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    2. Gopinath Subramani & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Frede Blaabjerg & Josep M. Guerrero, 2017. "Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving," Energies, MDPI, vol. 10(11), pages 1-17, November.
    3. Badran, Ola & Mekhilef, Saad & Mokhlis, Hazlie & Dahalan, Wardiah, 2017. "Optimal reconfiguration of distribution system connected with distributed generations: A review of different methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 854-867.
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    Cited by:

    1. Abdallah Abdellatif & Hamza Mubarak & Shameem Ahmad & Tofael Ahmed & G. M. Shafiullah & Ahmad Hammoudeh & Hamdan Abdellatef & M. M. Rahman & Hassan Muwafaq Gheni, 2022. "Forecasting Photovoltaic Power Generation with a Stacking Ensemble Model," Sustainability, MDPI, vol. 14(17), pages 1-21, September.
    2. Fangfang Zheng & Xiaofang Meng & Lidi Wang & Nannan Zhang, 2023. "Operation Optimization Method of Distribution Network with Wind Turbine and Photovoltaic Considering Clustering and Energy Storage," Sustainability, MDPI, vol. 15(3), pages 1-22, January.

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