Distribution Network Reconfiguration Optimization Using a New Algorithm Hyperbolic Tangent Particle Swarm Optimization (HT-PSO)
David W. Puma (),
Y. P. Molina,
Brayan A. Atoccsa,
J. E. Luyo and
Zocimo Ñaupari
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David W. Puma: Faculty of Mechanical Engineering, National University of Engineering, Lima 15333, Peru
Y. P. Molina: Department of Electrical Engineering, Federal University of Paraíba, Joao Pessoa 58051-900, PB, Brazil
Brayan A. Atoccsa: Facultad de Ingeniería Eléctrica y de Potencia, Universidad Tecnológica del Perú, Lima 15306, Peru
J. E. Luyo: Faculty of Mechanical Engineering, National University of Engineering, Lima 15333, Peru
Zocimo Ñaupari: Faculty of Electrical Engineering, National University of Engineering, Lima 15333, Peru
Energies, 2024, vol. 17, issue 15, 1-13
Abstract:
This paper introduces an innovative approach to address the distribution network reconfiguration (DNR) challenge, aiming to reduce power loss through an advanced hyperbolic tangent particle swarm optimization (HT-PSO) method. This approach is distinguished by the adoption of a novel hyperbolic tangent function, which effectively limits the rate of change values, offering a significant improvement over traditional sigmoid function-based methods. A key feature of this new approach is the integration of a tunable parameter, δ , into the HT-PSO, enhancing the curve’s adaptability. The careful optimization of δ ensures superior control over the rate of change across the entire operational range. This enhanced control mechanism substantially improves the efficiency of the search and convergence processes in DNR. Comparative simulations conducted on 33- and 94-bus systems show an improvement in convergence, demonstrating a more exhaustive exploration of the search space than existing methods documented in the literature based on PSO and variations where functions are proposed for the rate of change of values.
Keywords: distribution network reconfiguration; optimization; hyperbolic tangent; particle swarm optimization; delta optimized value; rate of change; power losses (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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