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Increasing Distributed Generation Hosting Capacity Based on a Sequential Optimization Approach Using an Improved Salp Swarm Algorithm

Author

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  • Andrei M. Tudose

    (Department of Electrical Power Systems, National University of Science and Technology “Politehnica” Bucharest, 060042 Bucharest, Romania
    Academy of Romanian Scientists, 030167 Bucharest, Romania)

  • Dorian O. Sidea

    (Department of Electrical Power Systems, National University of Science and Technology “Politehnica” Bucharest, 060042 Bucharest, Romania
    Academy of Romanian Scientists, 030167 Bucharest, Romania)

  • Irina I. Picioroaga

    (Department of Electrical Power Systems, National University of Science and Technology “Politehnica” Bucharest, 060042 Bucharest, Romania
    Academy of Romanian Scientists, 030167 Bucharest, Romania)

  • Nicolae Anton

    (Department of Electrical Power Systems, National University of Science and Technology “Politehnica” Bucharest, 060042 Bucharest, Romania)

  • Constantin Bulac

    (Department of Electrical Power Systems, National University of Science and Technology “Politehnica” Bucharest, 060042 Bucharest, Romania)

Abstract

In recent years, a pronounced transition to the exploitation of renewable energy sources has be observed worldwide, driven by current climate concerns and the scarcity of conventional fuels. However, this paradigm shift is accompanied by new challenges for existing power systems. Therefore, the hosting capacity must be exhaustively assessed in order to maximize the penetration of distributed generation while mitigating any adverse impact on the electrical grid in terms of voltage and the operational boundaries of the equipment. In this regard, multiple aspects must be addressed in order to maintain the proper functioning of the system following the new installations’ capacities. This paper introduces a sequential methodology designed to determine the maximum hosting capacity of a power system through the optimal allocation of both active and reactive power. To achieve this goal, an Improved Salp Swarm Algorithm is proposed, aiming to establish the appropriate operational planning of the power grid considering extensive distributed generation integration, while still ensuring a safe operation. The case study validates the relevance of the proposed model, demonstrating a successful enhancement of hosting capacity by 14.5% relative to standard models.

Suggested Citation

  • Andrei M. Tudose & Dorian O. Sidea & Irina I. Picioroaga & Nicolae Anton & Constantin Bulac, 2023. "Increasing Distributed Generation Hosting Capacity Based on a Sequential Optimization Approach Using an Improved Salp Swarm Algorithm," Mathematics, MDPI, vol. 12(1), pages 1-21, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2023:i:1:p:48-:d:1306040
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    References listed on IDEAS

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    4. Esau Zulu & Ryoichi Hara & Hiroyuki Kita, 2023. "An Efficient Hybrid Particle Swarm and Gradient Descent Method for the Estimation of the Hosting Capacity of Photovoltaics by Distribution Networks," Energies, MDPI, vol. 16(13), pages 1-17, July.
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