| Issue |
E3S Web Conf.
Volume 118, 2019
2019 4th International Conference on Advances in Energy and Environment Research (ICAEER 2019)
|
|
|---|---|---|
| Article Number | 01053 | |
| Number of page(s) | 4 | |
| Section | Energy Engineering, Materials and Technology | |
| DOI | https://doi.org/10.1051/e3sconf/201911801053 | |
| Published online | 04 October 2019 | |
Bus Load Decomposition Method Based on Deep Learning
1
China Electric Power Research Institute Co., Ltd., 210000 Nanjing, China
2
State Grid Jiangsu Electric Power Co., Ltd., 210000 Nanjing, China
3
State Grid Zhejiang Electric Power Co., Ltd., 310000 Hangzhou, China
* Corresponding author: qiantiantian@epri.sgcc.com.cn
The current research work is mainly based on the decomposition of the total load of the family house into the electrical level load, and less research on the bus load of the high voltage level. To solve this problem, in this paper, a bus load composition decomposition algorithm based on Bi-directional Long Short-Term Memory (Bi-LSTM) is proposed. The experimental results show that this method can effectively identify the bus load with unknown components. Compared with the traditional recurrent neural network and long-term and short-term memory network, the proposed algorithm has better identification ability.
© The Authors, published by EDP Sciences, 2019
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