Multi-parameter Overload Capacity Evaluation of Power Transformer Based on Improved Neural Network
- 10.2991/icaees-15.2015.123How to use a DOI?
- Transformers; Overloading Capacity; Modified BP Neural Network
Normally, transformer overloading capacity is calculated using method in guide for loading mineral-oil-immersed transformers. However, the method is not so accurate for every transformer. Therefore, a modified BP neural network based on transformer overloading calculation model is proposed. With BP neural network, computers can learn history data of transformer overloading and compute overloading time. This model combines a conditions parameter of cooling devices to make the result more accurate. The calculation data of case study using modified BP neural network model reveal that this model can get reasonable overloading time. Moreover, the overloading time is based on transformer stabilized operation, which is very practical significance.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yufeng Chen AU - Hui Wang AU - Zhihong Guo AU - Xiumin Du AU - Yi Yang AU - Chuanshuang He AU - Gehao Sheng PY - 2015/07 DA - 2015/07 TI - Multi-parameter Overload Capacity Evaluation of Power Transformer Based on Improved Neural Network BT - Proceedings of the 3rd International Conference on Advances in Energy and Environmental Science 2015 PB - Atlantis Press SP - 670 EP - 677 SN - 2352-5401 UR - https://doi.org/10.2991/icaees-15.2015.123 DO - 10.2991/icaees-15.2015.123 ID - Chen2015/07 ER -