3D-CNN-Based Spatial Load Forecasting Method Considering the Spatial-Temporal Influences of Multi-Source Data on Loads among Adjacent Cells
Author:
Affiliation:
1. Guangzhou Power Supply Bureau Guangdong Power Grid Co., Ltd.,Guangzhou,China
2. School of Electrical Engineering, Zhejiang University,Hangzhou,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10511272/10512350/10512546.pdf?arnumber=10512546
Reference20 articles.
1. Review and Prospect of Distribution Network Planning Research Considering Access of Flexible Load;Qi;Autom. Electr. Power Syst.,2020
2. Load forecasting via Grey Model-Least Squares Support Vector Machine model and spatial-temporal distribution of electric consumption intensity
3. A Very Short-term Load Forecasting Method Based on Deep LSTM RNN at Zone Level;Zhang;Power Syst. Technol.,2019
4. Probabilistic spatial load forecasting for assessing the impact of electric load growth in power distribution networks
5. Spatial-Temporal Residential Short-Term Load Forecasting via Graph Neural Networks
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