Attention Based Spatial-Temporal Graph Convolutional Networks for Short-term Load Forecasting

Rong Liu; Luan Chen

doi:10.1088/1742-6596/2078/1/012051

Attention Based Spatial-Temporal Graph Convolutional Networks for Short-term Load Forecasting

Journal of Physics Conference Series ◽

10.1088/1742-6596/2078/1/012051 ◽

2021 ◽

Vol 2078 (1) ◽

pp. 012051

Author(s):

Rong Liu ◽

Luan Chen

Keyword(s):

Power System ◽

Network Structure ◽

Power Grid ◽

Load Forecasting ◽

Experimental Results ◽

Short Term ◽

Convolutional Network ◽

Convolutional Networks ◽

Short Term Load Forecasting ◽

Temporal Graph

Abstract To predict the load of the power system with a known network structure, this paper proposes a novel attention based spatial-temporal graph convolutional network (ASTGCN) model to predict the node load in the power grid. The experimental results show the good performance of ASTGCN.

Short-term load forecasting of power system based on time convolutional network

2019 8th International Symposium on Next Generation Electronics (ISNE) ◽

10.1109/isne.2019.8896684 ◽

2019 ◽

Cited By ~ 1

Author(s):

Hanmo Wang ◽

Yang Zhao ◽

Sha Tan

Keyword(s):

Power System ◽

Load Forecasting ◽

Short Term ◽

Convolutional Network ◽

Short Term Load Forecasting

Research on Short-Term Load Forecasting Method of Power System Based on Seq2Seq-Attention Model

2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2) ◽

10.1109/ei250167.2020.9346583 ◽

2020 ◽

Author(s):

Wei Hu ◽

Yi Zhang ◽

Qiuting Guo ◽

Xu Huang ◽

Gang Li ◽

...

Keyword(s):

Power System ◽

Load Forecasting ◽

Short Term ◽

Attention Model ◽

Forecasting Method ◽

Short Term Load Forecasting

Comparison of forecasting methods for power system short-term load forecasting based on neural networks

2016 IEEE International Conference on Information and Automation (ICIA) ◽

10.1109/icinfa.2016.7831806 ◽

2016 ◽

Cited By ~ 6

Author(s):

Linlin Zhuang ◽

Hai Liu ◽

Jimin Zhu ◽

Shulin Wang ◽

Yong Song

Keyword(s):

Neural Networks ◽

Power System ◽

Load Forecasting ◽

Short Term ◽

Forecasting Methods ◽

Short Term Load Forecasting

An overview of short term load forecasting in electrical power system using fuzzy controller

2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) ◽

10.1109/icrito.2016.7784969 ◽

2016 ◽

Cited By ~ 2

Author(s):

Shruthi Matthew ◽

Siraparapu Satyanarayana

Keyword(s):

Power System ◽

Fuzzy Controller ◽

Electrical Power ◽

Load Forecasting ◽

Electrical Power System ◽

Short Term ◽

Short Term Load Forecasting

The Short Term Load Forecasting of RBF Neural Network Power System Based on Fuzzy Control

Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016) ◽

10.2991/icence-16.2016.28 ◽

2016 ◽

Author(s):

Jiangnan Ni ◽

Guo Jin

Keyword(s):

Neural Network ◽

Fuzzy Control ◽

Power System ◽

Rbf Neural Network ◽

Load Forecasting ◽

Short Term ◽

Short Term Load Forecasting ◽

Network Power

Short-Term Load Forecasting for Jordan Power System Based on NARX-ELMAN Neural Network and ARMA Model

IEEE Canadian Journal of Electrical and Computer Engineering ◽

10.1109/icjece.2021.3076124 ◽

2021 ◽

Vol 44 (3) ◽

pp. 356-363

Author(s):

Lina Alhmoud ◽

Qusay Nawafleh

Keyword(s):

Neural Network ◽

Power System ◽

Load Forecasting ◽

Arma Model ◽

Short Term ◽

Elman Neural Network ◽

Short Term Load Forecasting

Short-term Load Forecasting Based on Electricity Price in LSTM in Power Grid

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/569/4/042046 ◽

2019 ◽

Vol 569 ◽

pp. 042046

Author(s):

Ruyi Cai ◽

Shixin Li ◽

Jiecai Tian ◽

Liqiang Ren

Keyword(s):

Power Grid ◽

Load Forecasting ◽

Electricity Price ◽

Short Term ◽

Short Term Load Forecasting

Short-term Load Forecasting Method for Power System Based on Adaptive Neural Fuzzy Inference System

2020 Chinese Control And Decision Conference (CCDC) ◽

10.1109/ccdc49329.2020.9164846 ◽

2020 ◽

Author(s):

Song Li ◽

Jie-sheng Wang ◽

Min-wei Wang

Keyword(s):

Power System ◽

Fuzzy Inference System ◽

Fuzzy Inference ◽

Load Forecasting ◽

Short Term ◽

Inference System ◽

Forecasting Method ◽

Short Term Load Forecasting ◽

Neural Fuzzy

A CNN Based Model for Short-Term Load Forecasting: A Real Case Study on the Romanian Power System

2020 55th International Universities Power Engineering Conference (UPEC) ◽

10.1109/upec49904.2020.9209768 ◽

2020 ◽

Author(s):

Andrei M. Tudose ◽

Dorian O. Sidea ◽

Irina I. Picioroaga ◽

Valentin A. Boicea ◽

Constatin Bulac

Keyword(s):

Power System ◽

Load Forecasting ◽

Real Case ◽

Short Term ◽

Short Term Load Forecasting

A Method Based on Wavelet Neural Network for Power System Short Term Load Forecasting

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.521.303 ◽

2014 ◽

Vol 521 ◽

pp. 303-306 ◽

Cited By ~ 1

Author(s):

Hong Mei Zhong ◽

Jie Liu ◽

Qi Fang Chen ◽

Nian Liu

Keyword(s):

Neural Network ◽

Power System ◽

Bp Neural Network ◽

Load Forecasting ◽

Wavelet Neural Network ◽

Signal Spectrum ◽

Short Term ◽

Short Term Load Forecasting ◽

Load Sequence ◽

Daily Load

The short-term load of Power System is uncertain and the daily-load signal spectrum is continuous. The approach of Wavelet Neural Network (WNN) is proposed by combing the wavelet transform (WT) and neural network. By the WT, the time-based short-term load sequence can be decomposed into different scales sequences, which is used to training the BP neural network. The short-term load is forecasted by the trained BP neural network. Select the load of a random day in Lianyungang to study, according to the numerical simulation results, the method proves to achieve good performances.