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Optimal Asset Management of Distribution Transformers Considering Life Cycle Costs |
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| รหัสดีโอไอ | |
| Creator | Natthapong panjumpa |
| Title | Optimal Asset Management of Distribution Transformers Considering Life Cycle Costs |
| Contributor | Rongrit Chatthaworn |
| Publisher | Faculty of Engineering Mahasasakham University |
| Publication Year | 2564 |
| Journal Title | Engineering Access |
| Journal Vol. | 7 |
| Journal No. | 2 |
| Page no. | 159-168 |
| Keyword | Distribution transformer, Genetic algorithm, Maintenance and replacement schedule, Maintenance costs, Optimization model |
| URL Website | https://ph02.tci-thaijo.org/index.php/mijet/index |
| Website title | THAIJO Engineering Access |
| ISSN | 2730-4176 |
| Abstract | The optimal maintenance and replacement of distribution transformers can reduce the costs of maintenance and replacement and increase the transformer availability which can increase the system reliability as well. From the previous research works, they considered either maintenance or replacement of industrial equipment to determine the most appropriate scheme. Both maintenance and replacement of equipment have not been simultaneously considered before. Moreover, the asset value of the equipment has not been taken into account. Consequently, this paper presents the mathematical model of the optimal scheduling of transformer maintenance and replacement considering the asset value and the life cycle cost of the transformer. The purpose of the developed model is to minimize total cost while maintaining the defined level of transformer reliability. The considered costs compose of failure cost, maintenance and replacement costs. The Genetic Algorithm (GA) was applied to solve the optimization problem of the proposed model using MATLAB. The numeric results are presented as a graph for the system planner to decide for replacing and maintaining the transformer based on the life cycle cost of the transformer. The results from the proposed mathematical model can reduce the total cost by 36 % compared with the total cost before using the optimal schedule. |
