Next Article in Journal
Improved Equilibrium Optimization Algorithm Using Elite Opposition-Based Learning and New Local Search Strategy for Feature Selection in Medical Datasets
Next Article in Special Issue
Optimal Selection of Conductors in Three-Phase Distribution Networks Using a Discrete Version of the Vortex Search Algorithm
Previous Article in Journal
1D–2D Numerical Model for Wave Attenuation by Mangroves as a Porous Structure
Previous Article in Special Issue
Accurate and Efficient Derivative-Free Three-Phase Power Flow Method for Unbalanced Distribution Networks
Article

Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach

1
Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá D.C. 11021, Colombia
2
Laboratorio Inteligente de Energía, Universidad Tecnológica de Bolívar, Cartagena 131001, Colombia
3
Facultad de Ingeniería, Universidad Tecnológica de Pereira, Pereira 660003, Colombia
4
Grupo GIIEN, Facultad de Ingeniería, Institución Universitaria Pascual Bravo, Medellín 050036, Colombia
*
Author to whom correspondence should be addressed.
Academic Editors: George Tsakalidis and Kostas Vergidis
Received: 14 May 2021 / Revised: 2 June 2021 / Accepted: 5 June 2021 / Published: 9 June 2021
(This article belongs to the Special Issue Recent Advances in Process Modeling and Optimisation)
This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator and the generation of solutions using a Gaussian normal distribution based on the exploration and exploitation schemes of the vortex search algorithm. The master stage is entrusted with determining the configuration of the phases by using an integer codification. In the slave stage, a power flow for imbalanced distribution grids based on the three-phase version of the successive approximation method was used to determine the costs of daily energy losses. The objective of the optimization model is to minimize the annual operative costs of the network by considering the daily active and reactive power curves. Numerical results from a modified version of the IEEE 37-node test feeder demonstrate that it is possible to reduce the annual operative costs of the network by approximately 20% by using optimal load balancing. In addition, numerical results demonstrated that the improved version of the CBGA is at least three times faster than the classical CBGA, this was obtained in the peak load case for a test feeder composed of 15 nodes; also, the improved version of the CBGA was nineteen times faster than the vortex search algorithm. Other comparisons with the sine–cosine algorithm and the black hole optimizer confirmed the efficiency of the proposed optimization method regarding running time and objective function values. View Full-Text
Keywords: three-phase distribution networks; phase-balancing problem; improved Chu and Beasley genetic algorithm; mutation multi-point criteria; vortex search algorithm; normal Gaussian distribution three-phase distribution networks; phase-balancing problem; improved Chu and Beasley genetic algorithm; mutation multi-point criteria; vortex search algorithm; normal Gaussian distribution
Show Figures

Figure 1

MDPI and ACS Style

Montoya, O.D.; Molina-Cabrera, A.; Grisales-Noreña, L.F.; Hincapié, R.A.; Granada, M. Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach. Computation 2021, 9, 67. https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060067

AMA Style

Montoya OD, Molina-Cabrera A, Grisales-Noreña LF, Hincapié RA, Granada M. Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach. Computation. 2021; 9(6):67. https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060067

Chicago/Turabian Style

Montoya, Oscar D., Alexander Molina-Cabrera, Luis F. Grisales-Noreña, Ricardo A. Hincapié, and Mauricio Granada. 2021. "Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach" Computation 9, no. 6: 67. https://0-doi-org.brum.beds.ac.uk/10.3390/computation9060067

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop