A multivariate natural gas load forecasting method based on residual recurrent neural network
Abstract Current natural gas load forecasting encounters with the conundrum of unsatisfying accuracy and interpretability. To address the challenge, a multi‐variate forecasting method is proposed, which contains three phases: First, an integrate history‐climate‐holiday factor set is established to p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-10-01
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| Series: | Electronics Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ell2.12927 |
| _version_ | 1827795118586855424 |
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| author | Xueqing Ni Dongsheng Yang Jia Qin Xin Wang |
| author_facet | Xueqing Ni Dongsheng Yang Jia Qin Xin Wang |
| author_sort | Xueqing Ni |
| collection | DOAJ |
| description | Abstract Current natural gas load forecasting encounters with the conundrum of unsatisfying accuracy and interpretability. To address the challenge, a multi‐variate forecasting method is proposed, which contains three phases: First, an integrate history‐climate‐holiday factor set is established to provide multi‐perspective for a more explainable forecast; Second, factor fusion interaction between features and instances is carried out based on hierarchical contrastive learning, which contributes to inter‐intra factors potential relationships exploration. Third, a multivariate forecasting model named ResRNN is trained using fused target dataset. Due to its innovation in structure and loss, forecasting accuracy is further improved. Finally, the authors’ method's superiority is confirmed by several groups of comparative experiments and results demonstrate that it outperforms mainstream methods. |
| first_indexed | 2024-03-11T18:43:36Z |
| format | Article |
| id | doaj.art-5b51300e7e2c45dcaaa872f82b688936 |
| institution | Directory Open Access Journal |
| issn | 0013-5194 1350-911X |
| language | English |
| last_indexed | 2024-03-11T18:43:36Z |
| publishDate | 2023-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | Electronics Letters |
| spelling | doaj.art-5b51300e7e2c45dcaaa872f82b6889362023-10-12T05:37:32ZengWileyElectronics Letters0013-51941350-911X2023-10-015919n/an/a10.1049/ell2.12927A multivariate natural gas load forecasting method based on residual recurrent neural networkXueqing Ni0Dongsheng Yang1Jia Qin2Xin Wang3College of Information Science and Engineering Northeastern University Shenyang ChinaCollege of Information Science and Engineering Northeastern University Shenyang ChinaCollege of Information Science and Engineering Northeastern University Shenyang ChinaCollege of Information Science and Engineering Northeastern University Shenyang ChinaAbstract Current natural gas load forecasting encounters with the conundrum of unsatisfying accuracy and interpretability. To address the challenge, a multi‐variate forecasting method is proposed, which contains three phases: First, an integrate history‐climate‐holiday factor set is established to provide multi‐perspective for a more explainable forecast; Second, factor fusion interaction between features and instances is carried out based on hierarchical contrastive learning, which contributes to inter‐intra factors potential relationships exploration. Third, a multivariate forecasting model named ResRNN is trained using fused target dataset. Due to its innovation in structure and loss, forecasting accuracy is further improved. Finally, the authors’ method's superiority is confirmed by several groups of comparative experiments and results demonstrate that it outperforms mainstream methods.https://doi.org/10.1049/ell2.12927load forecastingnetwork analysisrecurrent neural nets |
| spellingShingle | Xueqing Ni Dongsheng Yang Jia Qin Xin Wang A multivariate natural gas load forecasting method based on residual recurrent neural network Electronics Letters load forecasting network analysis recurrent neural nets |
| title | A multivariate natural gas load forecasting method based on residual recurrent neural network |
| title_full | A multivariate natural gas load forecasting method based on residual recurrent neural network |
| title_fullStr | A multivariate natural gas load forecasting method based on residual recurrent neural network |
| title_full_unstemmed | A multivariate natural gas load forecasting method based on residual recurrent neural network |
| title_short | A multivariate natural gas load forecasting method based on residual recurrent neural network |
| title_sort | multivariate natural gas load forecasting method based on residual recurrent neural network |
| topic | load forecasting network analysis recurrent neural nets |
| url | https://doi.org/10.1049/ell2.12927 |
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