Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes w...

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Veröffentlicht in:Electronics (Basel) Jg. 10; H. 12; S. 1452
Hauptverfasser: Castiblanco-Pérez, Cristian Mateo, Toro-Rodríguez, David Esteban, Montoya, Oscar Danilo, Giral-Ramírez, Diego Armando
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 17.06.2021
Schlagworte:
Approximation
Codification
Cost control
Electricity
Energy
Energy costs
Genetic algorithms
Linear programming
Methods
Mixed integer
Nonlinear programming
Operating costs
Optimization
Optimization algorithms
Placement
Robustness (mathematics)
Sizing
Static synchronous compensators
Variables
ISSN:2079-9292, 2079-9292
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Abstract In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.
AbstractList In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.
Author Castiblanco-Pérez, Cristian Mateo
Montoya, Oscar Danilo
Toro-Rodríguez, David Esteban
Giral-Ramírez, Diego Armando
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  givenname: Diego Armando
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  surname: Giral-Ramírez
  fullname: Giral-Ramírez, Diego Armando
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Snippet In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of...
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SubjectTerms Approximation
Codification
Cost control
Electricity
Energy
Energy costs
Genetic algorithms
Linear programming
Methods
Mixed integer
Nonlinear programming
Operating costs
Optimization
Optimization algorithms
Placement
Robustness (mathematics)
Sizing
Static synchronous compensators
Variables
Title Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm
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