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Simultaneous Distribution Network Reconfiguration and Optimal Allocation of Renewable-Based Distributed Generators and Shunt Capacitors under Uncertain Conditions

Author

Listed:
  • Mahmoud M. Sayed

    (Electrical Power and Machines Department, Faculty of Engineering, Cairo University, Cairo 12613, Egypt)

  • Mohamed Y. Mahdy

    (Electrical Power and Machines Department, Faculty of Engineering, Cairo University, Cairo 12613, Egypt)

  • Shady H. E. Abdel Aleem

    (Department of Electrical Engineering, Valley High Institute of Engineering and Technology, Science Valley Academy, Qalubia 44971, Egypt)

  • Hosam K. M. Youssef

    (Electrical Power and Machines Department, Faculty of Engineering, Cairo University, Cairo 12613, Egypt)

  • Tarek A. Boghdady

    (Electrical Power and Machines Department, Faculty of Engineering, Cairo University, Cairo 12613, Egypt)

Abstract

Smart grid technology has received ample attention in past years to develop the traditional power distribution network and to enable the integration of distributed generation units (DGs) to satisfy increasing demand loads and to improve network performance. In addition to DGs, integration of shunt capacitors (SCs) along with network reconfiguration can also play an important role in improving network performance. Besides, network reconfiguration can help to increase the distributed generation hosting capacity of the network. Some of the research in the literature have presented and discussed the problem of optimal integration of renewable DGs and SCs along with optimal network reconfiguration, while the network load variability and/or the intermittent nature of renewable DGs are neglected. For the work presented in this paper, the SHADE optimization algorithm along with the SOE reconfiguration method have been employed for solving the aforementioned optimization problem with consideration of uncertainty related to both the network load and the output power of the renewable DGs. Maximizing the hosting capacity (HC) of the DGs and reducing network power losses in addition to improving the voltage profile have been considered as optimization objectives. Five different case studies have been conducted considering 33-bus and 59-bus distribution networks. The obtained results validate the effectiveness and the superiority of the employed techniques for maximizing the HC up to 17% and reducing power losses up to 95%. Besides, the results also depict the effect of SC integration and the consideration of uncertainties on achieving the optimization objectives with realistic modeling of the optimization problem.

Suggested Citation

  • Mahmoud M. Sayed & Mohamed Y. Mahdy & Shady H. E. Abdel Aleem & Hosam K. M. Youssef & Tarek A. Boghdady, 2022. "Simultaneous Distribution Network Reconfiguration and Optimal Allocation of Renewable-Based Distributed Generators and Shunt Capacitors under Uncertain Conditions," Energies, MDPI, vol. 15(6), pages 1-27, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2299-:d:776248
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    References listed on IDEAS

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    Cited by:

    1. Bruno Silva Torres & Luiz Eduardo Borges da Silva & Camila Paes Salomon & Carlos Henrique Valério de Moraes, 2022. "Integrating Smart Grid Devices into the Traditional Protection of Distribution Networks," Energies, MDPI, vol. 15(7), pages 1-28, March.
    2. Ola Badran & Jafar Jallad, 2023. "Multi-Objective Decision Approach for Optimal Real-Time Switching Sequence of Network Reconfiguration Realizing Maximum Load Capacity," Energies, MDPI, vol. 16(19), pages 1-32, September.
    3. Zifa Liu & Jieyu Li & Yunyang Liu & Puyang Yu & Junteng Shao, 2022. "Collaborative Optimized Operation Model of Multi-Character Distribution Network Considering Multiple Uncertain Factors and Demand Response," Energies, MDPI, vol. 15(12), pages 1-19, June.

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