The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo aplica o algoritmo de Programação Evolucionária (EP) e uma técnica de avaliação de risco para obter uma solução ótima para o problema de Decisão de Programação de Manutenção de Unidade (UMSD), sujeito a custos econômicos e restrições de segurança de energia. A abordagem proposta emprega um modelo de avaliação de risco para avaliar a segurança do sistema de fornecimento de energia e utiliza o algoritmo EP para estabelecer o cronograma ideal de manutenção da unidade. A eficácia da metodologia proposta é verificada através de testes utilizando o IEEE Reliability Test System (RTS). Os resultados dos testes confirmam que a abordagem proposta pode garantir a segurança do sistema e superar os métodos de otimização determinística e estocástica existentes, tanto em termos da qualidade da solução quanto do esforço computacional necessário. Portanto, a metodologia proposta representa uma técnica particularmente eficaz para o UMSD.
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Chen-Sung CHANG, "Approach to the Unit Maintenance Scheduling Decision Using Risk Assessment and Evolution Programming Techniques" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 7, pp. 1900-1908, July 2010, doi: 10.1587/transinf.E93.D.1900.
Abstract: This paper applies the Evolutionary Programming (EP) algorithm and a risk assessment technique to obtain an optimal solution to the Unit Maintenance Scheduling Decision (UMSD) problem subject to economic cost and power security constraints. The proposed approach employs a risk assessment model to evaluate the security of the power supply system and uses the EP algorithm to establish the optimal unit maintenance schedule. The effectiveness of the proposed methodology is verified through testing using the IEEE Reliability Test System (RTS). The test results confirm that the proposed approach can to ensure that the system security and outperforms the existing deterministic and stochastic optimization methods both in terms of the quality of the solution and the computational effort required. Therefore, the proposed methodology represents a particular effective technique for the UMSD.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1900/_p
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@ARTICLE{e93-d_7_1900,
author={Chen-Sung CHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Approach to the Unit Maintenance Scheduling Decision Using Risk Assessment and Evolution Programming Techniques},
year={2010},
volume={E93-D},
number={7},
pages={1900-1908},
abstract={This paper applies the Evolutionary Programming (EP) algorithm and a risk assessment technique to obtain an optimal solution to the Unit Maintenance Scheduling Decision (UMSD) problem subject to economic cost and power security constraints. The proposed approach employs a risk assessment model to evaluate the security of the power supply system and uses the EP algorithm to establish the optimal unit maintenance schedule. The effectiveness of the proposed methodology is verified through testing using the IEEE Reliability Test System (RTS). The test results confirm that the proposed approach can to ensure that the system security and outperforms the existing deterministic and stochastic optimization methods both in terms of the quality of the solution and the computational effort required. Therefore, the proposed methodology represents a particular effective technique for the UMSD.},
keywords={},
doi={10.1587/transinf.E93.D.1900},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - Approach to the Unit Maintenance Scheduling Decision Using Risk Assessment and Evolution Programming Techniques
T2 - IEICE TRANSACTIONS on Information
SP - 1900
EP - 1908
AU - Chen-Sung CHANG
PY - 2010
DO - 10.1587/transinf.E93.D.1900
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2010
AB - This paper applies the Evolutionary Programming (EP) algorithm and a risk assessment technique to obtain an optimal solution to the Unit Maintenance Scheduling Decision (UMSD) problem subject to economic cost and power security constraints. The proposed approach employs a risk assessment model to evaluate the security of the power supply system and uses the EP algorithm to establish the optimal unit maintenance schedule. The effectiveness of the proposed methodology is verified through testing using the IEEE Reliability Test System (RTS). The test results confirm that the proposed approach can to ensure that the system security and outperforms the existing deterministic and stochastic optimization methods both in terms of the quality of the solution and the computational effort required. Therefore, the proposed methodology represents a particular effective technique for the UMSD.
ER -