Optimal Planning and Dynamic Operation of Thyristor-Switched Capacitors in Distribution Networks Using the Atan-Sinc Optimization Algorithm with IPOPT Refinement

This paper proposes an innovative hybrid optimization framework for the optimal installation and operation of thyristor-switched capacitors (TSCs) within medium-voltage distribution networks, targeting both energy losses reduction and cost efficiency. The core of the approach combines the exploratory capabilities of the atan-sinc optimization algorithm (ASOA), a recent metaheuristic inspired by mathematical functions, with the local refinement power of the IPOPT solver within a master–slave architecture. This integrated method addresses the inherent complexity of a multi-objective, mixed-integer nonlinear programming problem that seeks to balance conflicting goals: minimizing annual system losses and investment costs. Extensive testing on IEEE 33- and 69-bus systems under fixed and dynamic reactive power injection scenarios demonstrates that our framework consistently delivers superior solutions when compared to traditional and state-of-the-art algorithms. Notably, the variable operation case yields energy savings of up to 12%, translating into annual monetary gains exceeding USD 1000 in comparison with the fixed support scenario.The solutions produce well-distributed Pareto fronts that illustrate valuable trade-offs, allowing system planners to make informed decisions. The findings confirm that the proposed strategy constitutes a scalable, and robust tool for reactive power planning, supporting the deployment of smarter and more resilient distribution systems.

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Publication Details

Journal
Sci
Published
2025-10-07
DOI
https://doi.org/10.3390/sci7040143
Citations
1
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.73
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article

Optimal Planning and Dynamic Operation of Thyristor-Switched Capacitors in Distribution Networks Using the Atan-Sinc Optimization Algorithm with IPOPT Refinement

Luis Fernando Grisales-Noreña, Rubén Iván Bolaños, Oscar Danilo Montoya
1 citations
Sci
Optimal Power Flow Distribution
0.73
article

Optimal Planning and Dynamic Operation of Thyristor-Switched Capacitors in Distribution Networks Using the Atan-Sinc Optimization Algorithm with IPOPT Refinement

Luis Fernando Grisales-Noreña, Rubén Iván Bolaños, Oscar Danilo Montoya
article en
1 citations

Abstract

This paper proposes an innovative hybrid optimization framework for the optimal installation and operation of thyristor-switched capacitors (TSCs) within medium-voltage distribution networks, targeting both energy losses reduction and cost efficiency. The core of the approach combines the exploratory capabilities of the atan-sinc optimization algorithm (ASOA), a recent metaheuristic inspired by mathematical functions, with the local refinement power of the IPOPT solver within a master–slave architecture. This integrated method addresses the inherent complexity of a multi-objective, mixed-integer nonlinear programming problem that seeks to balance conflicting goals: minimizing annual system losses and investment costs. Extensive testing on IEEE 33- and 69-bus systems under fixed and dynamic reactive power injection scenarios demonstrates that our framework consistently delivers superior solutions when compared to traditional and state-of-the-art algorithms. Notably, the variable operation case yields energy savings of up to 12%, translating into annual monetary gains exceeding USD 1000 in comparison with the fixed support scenario.The solutions produce well-distributed Pareto fronts that illustrate valuable trade-offs, allowing system planners to make informed decisions. The findings confirm that the proposed strategy constitutes a scalable, and robust tool for reactive power planning, supporting the deployment of smarter and more resilient distribution systems.

SciVol. 7(4)
Universidad Distrital Francisco José de Caldas (CO), Instituto Tecnológico Metropolitano (CO), University of Córdoba (ES), Universidad del Valle (CO)
Openalex Percentile: Top 23%
Optimal Power Flow Distribution
0.73
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