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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Vydané v:Electronics (Basel) Ročník 10; číslo 12; s. 1452
Hlavní autori: Castiblanco-Pérez, Cristian Mateo, Toro-Rodríguez, David Esteban, Montoya, Oscar Danilo, Giral-Ramírez, Diego Armando
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 17.06.2021
Predmet:
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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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics10121452