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Optimal Allocation of Photovoltaic Distributed Generations in Radial Distribution Networks

Author

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  • Samson Oladayo Ayanlade

    (Department of Electrical and Electronic Engineering, Faculty of Engineering and Technology, Lead City University, Ibadan 200255, Nigeria)

  • Funso Kehinde Ariyo

    (Department of Electronic and Electrical Engineering, Faculty of Technology, Obafemi Awolowo University, Ile-Ife 220101, Nigeria)

  • Abdulrasaq Jimoh

    (Department of Electronic and Electrical Engineering, Faculty of Technology, Obafemi Awolowo University, Ile-Ife 220101, Nigeria)

  • Kayode Timothy Akindeji

    (Smart Grid Research Center, Department of Electrical Power Engineering, Faculty of Engineering and the Built Environment, Durban University of Technology, Durban 4000, South Africa)

  • Adeleye Oluwaseye Adetunji

    (Department of Electrical and Electronic Engineering, Faculty of Engineering and Environmental Sciences, Osun State University, Osogbo 210001, Nigeria)

  • Emmanuel Idowu Ogunwole

    (Department of Electrical, Electronic and Computer Engineering, Cape Peninsula University of Technology, Cape Town 7535, South Africa)

  • Dolapo Eniola Owolabi

    (Department of Electronic and Electrical Engineering, Faculty of Engineering and Technology, Ladoke Akintola University of Technology, Ogbomoso 210214, Nigeria)

Abstract

Photovoltaic distributed generation (PVDG) is a noteworthy form of distributed energy generation that boasts a multitude of advantages. It not only produces absolutely no greenhouse gas emissions but also demands minimal maintenance. Consequently, PVDG has found widespread applications within distribution networks (DNs), particularly in the realm of improving network efficiency. In this research study, the dingo optimization algorithm (DOA) played a pivotal role in optimizing PVDGs with the primary aim of enhancing the performance of DNs. The crux of this optimization effort revolved around formulating an objective function that represented the cumulative active power losses that occurred across all branches of the network. The DOA was then effectively used to evaluate the most suitable capacities and positions for the PVDG units. To address the power flow challenges inherent to DNs, this study used the Newton–Raphson power flow method. To gauge the effectiveness of DOA in allocating PVDG units, it was rigorously compared to other metaheuristic optimization algorithms previously documented in the literature. The entire methodology was implemented using MATLAB and validated using the IEEE 33-bus DN. The performance of the network was scrutinized under normal, light, and heavy loading conditions. Subsequently, the approach was also applied to a practical Ajinde 62-bus DN. The research findings yielded crucial insights. For the IEEE 33-bus DN, it was determined that the optimal locations for PVDG units were buses 13, 25, and 33, with recommended capacities of 833, 532, and 866 kW, respectively. Similarly, in the context of the Ajinde 62-bus network, buses 17, 27, and 33 were identified as the prime locations for PVDGs, each with optimal sizes of 757, 150, and 1097 kW, respectively. Remarkably, the introduction of PVDGs led to substantial enhancements in network performance. For instance, in the IEEE 33-bus DN, the smallest voltage magnitude increased to 0.966 p.u. under normal loads, 0.9971 p.u. under light loads, and 0.96004 p.u. under heavy loads. These improvements translated into a significant reduction in active power losses—61.21% under normal conditions, 17.84% under light loads, and 33.31% under heavy loads. Similarly, in the case of the Ajinde 62-bus DN, the smallest voltage magnitude reached 0.9787 p.u., accompanied by an impressive 71.05% reduction in active power losses. In conclusion, the DOA exhibited remarkable efficacy in the strategic allocation of PVDGs, leading to substantial enhancements in DN performance across diverse loading conditions.

Suggested Citation

  • Samson Oladayo Ayanlade & Funso Kehinde Ariyo & Abdulrasaq Jimoh & Kayode Timothy Akindeji & Adeleye Oluwaseye Adetunji & Emmanuel Idowu Ogunwole & Dolapo Eniola Owolabi, 2023. "Optimal Allocation of Photovoltaic Distributed Generations in Radial Distribution Networks," Sustainability, MDPI, vol. 15(18), pages 1-26, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13933-:d:1243449
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    References listed on IDEAS

    as
    1. Muhammad Haris Khan & Abasin Ulasyar & Abraiz Khattak & Haris Sheh Zad & Mohammad Alsharef & Ahmad Aziz Alahmadi & Nasim Ullah, 2022. "Optimal Sizing and Allocation of Distributed Generation in the Radial Power Distribution System Using Honey Badger Algorithm," Energies, MDPI, vol. 15(16), pages 1-18, August.
    2. Elham Mahdavi & Seifollah Asadpour & Leonardo H. Macedo & Rubén Romero, 2023. "Reconfiguration of Distribution Networks with Simultaneous Allocation of Distributed Generation Using the Whale Optimization Algorithm," Energies, MDPI, vol. 16(12), pages 1-19, June.
    3. Amit Kumar Bairwa & Sandeep Joshi & Dilbag Singh, 2021. "Dingo Optimizer: A Nature-Inspired Metaheuristic Approach for Engineering Problems," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, June.
    4. Abdulaziz Alanazi & Tarek I. Alanazi, 2023. "Multi-Objective Framework for Optimal Placement of Distributed Generations and Switches in Reconfigurable Distribution Networks: An Improved Particle Swarm Optimization Approach," Sustainability, MDPI, vol. 15(11), pages 1-25, June.
    5. Ehab S. Ali & Sahar. M. Abd Elazim & Sultan H. Hakmi & Mohamed I. Mosaad, 2023. "Optimal Allocation and Size of Renewable Energy Sources as Distributed Generations Using Shark Optimization Algorithm in Radial Distribution Systems," Energies, MDPI, vol. 16(10), pages 1-27, May.
    6. 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.
    7. Minh Quan Duong & Thai Dinh Pham & Thang Trung Nguyen & Anh Tuan Doan & Hai Van Tran, 2019. "Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems," Energies, MDPI, vol. 12(1), pages 1-24, January.
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