Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem

Leonel M. Carvalho; Fabio Loureiro; Jean Sumaili; Hrvoje Keko; Vladimiro Miranda; Carolina G. Marcelino; Elizabeth F. Wanner

doi:10.1109/ISAP.2015.7325576

Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem

Leonel M. Carvalho, Fabio Loureiro, Jean Sumaili, Hrvoje Keko, Vladimiro Miranda, Carolina G. Marcelino, Elizabeth F. Wanner

Resultado de pesquisa › revisão de pares

16 Citações (Scopus)

Resumo

The optimal solution provided by metaheuristics can be viewed as a random variable, whose behavior depends on the value of the algorithm's strategic parameters and on the type of penalty function used to enforce the problem's soft constraints. This paper reports the use of parametric and non-parametric statistics to compare three different penalty functions implemented to solve the Security Constrained Optimal Power Flow (SCOPF) problem using the new enhanced metaheuristic Differential Evolutionary Particle Swarm Optimization (DEEPSO). To obtain the best performance for the three types of penalty functions, the strategic parameters of DEEPSO are optimized by using an iterative algorithm based on the two-way analysis of variance (ANOVA). The results show that the modeling of soft constraints significantly influences the best achievable performance of the optimization algorithm.

Idioma original	Inglês
Título da publicação do anfitrião	2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015
Editora	Institute of Electrical and Electronics Engineers Inc.
ISBN (eletrónico)	9781509001903
DOIs	https://doi.org/10.1109/ISAP.2015.7325576
Estado da publicação	Publicadas - 10 nov. 2015
Publicado externamente	Sim
Evento	18th International Conference on Intelligent System Application to Power Systems, ISAP 2015 - Porto Duração: 11 set. 2015 → 17 set. 2015

Série de publicação

Nome	2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015

Conferência

Conferência	18th International Conference on Intelligent System Application to Power Systems, ISAP 2015
País/Território	Portugal
Cidade	Porto
Período	11/09/15 → 17/09/15

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Publisher Copyright:
© 2015 IEEE.

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10.1109/ISAP.2015.7325576

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Carvalho, L. M., Loureiro, F., Sumaili, J., Keko, H., Miranda, V., Marcelino, C. G., & Wanner, E. F. (2015). Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem. Em 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015 Artigo 7325576 (2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISAP.2015.7325576

Carvalho, Leonel M. ; Loureiro, Fabio ; Sumaili, Jean et al. / Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem. 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015. Institute of Electrical and Electronics Engineers Inc., 2015. (2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015).

@inproceedings{35fcc9776f764b3a99ad90a19cc8ceec,

title = "Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem",

abstract = "The optimal solution provided by metaheuristics can be viewed as a random variable, whose behavior depends on the value of the algorithm's strategic parameters and on the type of penalty function used to enforce the problem's soft constraints. This paper reports the use of parametric and non-parametric statistics to compare three different penalty functions implemented to solve the Security Constrained Optimal Power Flow (SCOPF) problem using the new enhanced metaheuristic Differential Evolutionary Particle Swarm Optimization (DEEPSO). To obtain the best performance for the three types of penalty functions, the strategic parameters of DEEPSO are optimized by using an iterative algorithm based on the two-way analysis of variance (ANOVA). The results show that the modeling of soft constraints significantly influences the best achievable performance of the optimization algorithm.",

keywords = "ANOVA, DEEPSO, EPSO, Non-parametric statistics, OPF",

author = "Carvalho, {Leonel M.} and Fabio Loureiro and Jean Sumaili and Hrvoje Keko and Vladimiro Miranda and Marcelino, {Carolina G.} and Wanner, {Elizabeth F.}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015 ; Conference date: 11-09-2015 Through 17-09-2015",

year = "2015",

month = nov,

day = "10",

doi = "10.1109/ISAP.2015.7325576",

language = "English",

series = "2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015",

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Carvalho, LM, Loureiro, F, Sumaili, J, Keko, H, Miranda, V, Marcelino, CG & Wanner, EF 2015, Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem. em 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015., 7325576, 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015, Institute of Electrical and Electronics Engineers Inc., 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015, Porto, Portugal, 11/09/15. https://doi.org/10.1109/ISAP.2015.7325576

Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem. / Carvalho, Leonel M.; Loureiro, Fabio; Sumaili, Jean et al.
2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7325576 (2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015).

Resultado de pesquisa › revisão de pares

TY - GEN

T1 - Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem

AU - Carvalho, Leonel M.

AU - Loureiro, Fabio

AU - Sumaili, Jean

AU - Keko, Hrvoje

AU - Miranda, Vladimiro

AU - Marcelino, Carolina G.

AU - Wanner, Elizabeth F.

PY - 2015/11/10

Y1 - 2015/11/10

N2 - The optimal solution provided by metaheuristics can be viewed as a random variable, whose behavior depends on the value of the algorithm's strategic parameters and on the type of penalty function used to enforce the problem's soft constraints. This paper reports the use of parametric and non-parametric statistics to compare three different penalty functions implemented to solve the Security Constrained Optimal Power Flow (SCOPF) problem using the new enhanced metaheuristic Differential Evolutionary Particle Swarm Optimization (DEEPSO). To obtain the best performance for the three types of penalty functions, the strategic parameters of DEEPSO are optimized by using an iterative algorithm based on the two-way analysis of variance (ANOVA). The results show that the modeling of soft constraints significantly influences the best achievable performance of the optimization algorithm.

AB - The optimal solution provided by metaheuristics can be viewed as a random variable, whose behavior depends on the value of the algorithm's strategic parameters and on the type of penalty function used to enforce the problem's soft constraints. This paper reports the use of parametric and non-parametric statistics to compare three different penalty functions implemented to solve the Security Constrained Optimal Power Flow (SCOPF) problem using the new enhanced metaheuristic Differential Evolutionary Particle Swarm Optimization (DEEPSO). To obtain the best performance for the three types of penalty functions, the strategic parameters of DEEPSO are optimized by using an iterative algorithm based on the two-way analysis of variance (ANOVA). The results show that the modeling of soft constraints significantly influences the best achievable performance of the optimization algorithm.

KW - ANOVA

KW - DEEPSO

KW - EPSO

KW - Non-parametric statistics

KW - OPF

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T3 - 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015

BT - 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015

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Carvalho LM, Loureiro F, Sumaili J, Keko H, Miranda V, Marcelino CG et al. Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem. Em 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7325576. (2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015). doi: 10.1109/ISAP.2015.7325576

Statistical tuning of DEEPSO soft constraints in the Security Constrained Optimal Power Flow problem

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