Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling
Generator maintenance scheduling presents many engineering issues that provide power system personnel with a variety of challenges, and one can hardly afford to neglect these engineering issues in the future. Additionally, there is vital need for further development of the repair planning task compl...
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doaj-04d4be832a7841019201ecb7b9f78f0b2020-11-25T03:59:41ZengMDPI AGEnergies1996-10732020-10-01135381538110.3390/en13205381Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance SchedulingPavel Y. Gubin0Vladislav P. Oboskalov1Anatolijs Mahnitko2Roman Petrichenko3Ural Power Engineering Institute, Ural Federal University, 620002 Yekaterinburg, RussiaUral Power Engineering Institute, Ural Federal University, 620002 Yekaterinburg, RussiaInstitute of Power Engineering, Riga Technical University, LV-1048 Riga, LatviaInstitute of Power Engineering, Riga Technical University, LV-1048 Riga, LatviaGenerator maintenance scheduling presents many engineering issues that provide power system personnel with a variety of challenges, and one can hardly afford to neglect these engineering issues in the future. Additionally, there is vital need for further development of the repair planning task complexity in order to take into account the vast majority of power flow constraints. At present, the question still remains as to which approach is the simplest and most effective, as well as appropriate for further application in the power flow-oriented statement of the repair planning problem. This research compared directed search, differential evolution, and very fast simulated annealing methods based on a number of numerical calculations and made conclusions about their prospective utilization in terms of a more complicated mathematical formulation of the repair planning task. A comparison of results shows that the effectiveness of directed search methods should not be underestimated, and that the pure differential evolution and very fast simulated annealing approaches are not essentially reliable for repair planning. The experimental results demonstrate the perspectivity of unifying single-procedure methods in order to net out risk associated with specific features of these approaches.https://www.mdpi.com/1996-1073/13/20/5381schedulinggeneratordifferential evolutionsimulated annealingmaintenancedirected search |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pavel Y. Gubin Vladislav P. Oboskalov Anatolijs Mahnitko Roman Petrichenko |
spellingShingle |
Pavel Y. Gubin Vladislav P. Oboskalov Anatolijs Mahnitko Roman Petrichenko Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling Energies scheduling generator differential evolution simulated annealing maintenance directed search |
author_facet |
Pavel Y. Gubin Vladislav P. Oboskalov Anatolijs Mahnitko Roman Petrichenko |
author_sort |
Pavel Y. Gubin |
title |
Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling |
title_short |
Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling |
title_full |
Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling |
title_fullStr |
Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling |
title_full_unstemmed |
Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling |
title_sort |
simulated annealing, differential evolution and directed search methods for generator maintenance scheduling |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2020-10-01 |
description |
Generator maintenance scheduling presents many engineering issues that provide power system personnel with a variety of challenges, and one can hardly afford to neglect these engineering issues in the future. Additionally, there is vital need for further development of the repair planning task complexity in order to take into account the vast majority of power flow constraints. At present, the question still remains as to which approach is the simplest and most effective, as well as appropriate for further application in the power flow-oriented statement of the repair planning problem. This research compared directed search, differential evolution, and very fast simulated annealing methods based on a number of numerical calculations and made conclusions about their prospective utilization in terms of a more complicated mathematical formulation of the repair planning task. A comparison of results shows that the effectiveness of directed search methods should not be underestimated, and that the pure differential evolution and very fast simulated annealing approaches are not essentially reliable for repair planning. The experimental results demonstrate the perspectivity of unifying single-procedure methods in order to net out risk associated with specific features of these approaches. |
topic |
scheduling generator differential evolution simulated annealing maintenance directed search |
url |
https://www.mdpi.com/1996-1073/13/20/5381 |
work_keys_str_mv |
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