Journal of Modern Power Systems and Clean Energy

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Home > Archive>Volume 13, Issue 3, 2025 >940-952. DOI:10.35833/MPCE.2024.000649
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Optimal Placement of Electric Springs in Unbalanced Distribution Networks Using Improved Backward/forward Sweep Method Based Genetic Algorithm
Author:
Affiliation:

1.ENAP-Research Group, University of Guanajuato, Irapuato, Mexico;2.School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico;3.ENAP-Research Group, Faculty of Engineering, Autonomous University of Queretaro, San Juan del Río, Mexico;4.Electronic Engineering Department, University of Guanajuato, Salamanca, Mexico;5.ENAP-Research Group, National Technological Institute of Mexico, ITS Irapuato, Irapuato, Mexico

Fund Project:

This work was supported by Consejo Nacional de Humanidades, Ciencia y Tecnología (CONAHCYT)—México (No. 863547), the fellowship 2021-000001-01NACF-00604 given to the G. H. Valencia-Rivera; and the scholarships 175599, 64698, 253652, and 296574, given to G. Tapia-Tinoco, A. Garcia-Perez, D. Granados-Lieberman, and M. Valtierra-Rodriguez, respectively, through the Sistema Nacional de Investigadoras e Investigadores (SNII)-CONAHCYT-México.

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    Abstract:

    A novel planning tool for optimizing the placement of electric springs (ESs) in unbalanced distribution networks is introduced in this study. The total voltage deviation is used as the optimization criterion and is calculated when the ESs operate at their maximum reactive power either in the inductive or capacitive modes. The power rating of the ES is adjusted on the basis of the available active power at the bus. And in the optimization problem, it is expressed as the power ratio of the noncritical load (NCL) and critical load (CL). The implemented ES model is flexible, which can be used on any bus and any phase. The model determines the output voltage from the parameters and operating conditions at the point of common coupling (PCC). These conditions are integrated using the backward/forward sweep method (BFSM) and are updated during power flow calculations. The problem is described as a mixed-integer nonlinear problem and solved efficiently using an improved BFSM-based genetic algorithm, which computes power flow and ES placement simultaneously. The effectiveness of this method is evaluated through testing in IEEE 13-bus and 34-bus systems.

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History
  • Received:June 20,2024
  • Revised:October 25,2024
  • Online: May 27,2025

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