Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural Network

This paper proposes a load forecasting method based on LSTM model, fully explores the regularity of historical load data of industrial park enterprises, inputs the data features into LSTM units for feature extraction, and applies the attention-based model for load forecasting. The experiments show t...

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Main Authors: Guannan Wang, Pei Yang, Jiayi Chen
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2021/1435334
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author Guannan Wang
Pei Yang
Jiayi Chen
author_facet Guannan Wang
Pei Yang
Jiayi Chen
author_sort Guannan Wang
collection DOAJ
description This paper proposes a load forecasting method based on LSTM model, fully explores the regularity of historical load data of industrial park enterprises, inputs the data features into LSTM units for feature extraction, and applies the attention-based model for load forecasting. The experiments show that the accuracy of our prediction model and early warning model is better than that of the baseline and can reach the standard of application in practice; this model can also be used for early warning of local sudden large loads and identification of enterprise power demand. Therefore, the validity of the method proposed in this paper is verified using the historical dataset of industrial parks, and relevant technical products and business models are formed to provide value-added services to users by combining existing practical cases for the specific scenario of industrial parks.
format Article
id doaj-art-adc6a49a757b440bbfe5b640de28feba
institution Kabale University
issn 1026-0226
1607-887X
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-adc6a49a757b440bbfe5b640de28feba2025-08-20T03:39:41ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2021-01-01202110.1155/2021/14353341435334Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural NetworkGuannan Wang0Pei Yang1Jiayi Chen2State Grid Xiongan Financial Technology Group Co., Ltd., Beijing, ChinaState Grid Xiongan Financial Technology Group Co., Ltd., Beijing, ChinaState Grid Xiongan Financial Technology Group Co., Ltd., Beijing, ChinaThis paper proposes a load forecasting method based on LSTM model, fully explores the regularity of historical load data of industrial park enterprises, inputs the data features into LSTM units for feature extraction, and applies the attention-based model for load forecasting. The experiments show that the accuracy of our prediction model and early warning model is better than that of the baseline and can reach the standard of application in practice; this model can also be used for early warning of local sudden large loads and identification of enterprise power demand. Therefore, the validity of the method proposed in this paper is verified using the historical dataset of industrial parks, and relevant technical products and business models are formed to provide value-added services to users by combining existing practical cases for the specific scenario of industrial parks.http://dx.doi.org/10.1155/2021/1435334
spellingShingle Guannan Wang
Pei Yang
Jiayi Chen
Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural Network
Discrete Dynamics in Nature and Society
title Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural Network
title_full Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural Network
title_fullStr Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural Network
title_full_unstemmed Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural Network
title_short Short-Term Electric Load Prediction and Early Warning in Industrial Parks Based on Neural Network
title_sort short term electric load prediction and early warning in industrial parks based on neural network
url http://dx.doi.org/10.1155/2021/1435334
work_keys_str_mv AT guannanwang shorttermelectricloadpredictionandearlywarninginindustrialparksbasedonneuralnetwork
AT peiyang shorttermelectricloadpredictionandearlywarninginindustrialparksbasedonneuralnetwork
AT jiayichen shorttermelectricloadpredictionandearlywarninginindustrialparksbasedonneuralnetwork