Approach to the Unit Maintenance Scheduling Decision Using Risk Assessment and Evolution Programming Techniques
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E93-D No.7 pp.1900-1908
- Publication Date
- 2010/07/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E93.D.1900
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence, Data Mining
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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},}
Copy
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 -
English
