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An Efficient Hybrid Particle Swarm and Gradient Descent Method for the Estimation of the Hosting Capacity of Photovoltaics by Distribution Networks

Author

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  • Esau Zulu

    (Faculty of Information Science and Technology, Hokkaido University, Sapporo 060-0808, Japan)

  • Ryoichi Hara

    (Faculty of Information Science and Technology, Hokkaido University, Sapporo 060-0808, Japan)

  • Hiroyuki Kita

    (Faculty of Information Science and Technology, Hokkaido University, Sapporo 060-0808, Japan)

Abstract

With many distribution networks adopting photovoltaic (PV) generation systems in their networks, there is a significant risk of over-voltages, reverse power flow, line congestion, and increased harmonics. Therefore, there is a need to estimate the amount of PV that can be injected into the distribution network without pushing the network towards these threats. The largest amount of PV a distribution system can accommodate is the PV hosting capacity (PVHC). The paper proposes an efficient method for estimating the PVHC of distribution networks that combines particle swarm optimization (PSO) and the gradient descent algorithm (GD). PSO has a powerful exploration of the solution space but poor exploitation of the local search. On the other hand, GD has great exploitation of local search to obtain local optima but needs better global search capabilities. The proposed method aims to harness the advantages of both PSO and GD while alleviating the ills of each. The numerical case studies show that the proposed method is more efficient, stable, and superior to the other meta-heuristic approaches.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:5207-:d:1188297
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    References listed on IDEAS

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    1. Prusty, B Rajanarayan & Jena, Debashisha, 2017. "A critical review on probabilistic load flow studies in uncertainty constrained power systems with photovoltaic generation and a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1286-1302.
    2. Ismael, Sherif M. & Abdel Aleem, Shady H.E. & Abdelaziz, Almoataz Y. & Zobaa, Ahmed F., 2019. "State-of-the-art of hosting capacity in modern power systems with distributed generation," Renewable Energy, Elsevier, vol. 130(C), pages 1002-1020.
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    Cited by:

    1. 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 1-22, December.

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