Short-term load probabilistic forecasting based on quantile regression convolutional neural network and Epanechnikov kernel density estimation
Electricity load forecasting plays an indispensable role in the electric power systems. However, its characteristics of uncertainty and complexity are hard to handle. This paper proposes a probabilistic load forecasting approach named QRCNN-E. Specifically, the deep convolutional neural network is a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-12-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484720314062 |