Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism
Introduction: Smart Grid (SG) as an intelligent system has become a key element in the efficient operation of the electrical grid. With the continuous increase in global energy demand and escalating environmental concerns, the importance of energy conservation and sustainable energy sources has beco...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-10-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1283026/full |
| _version_ | 1827800971289296896 |
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| author | Rujun Wang |
| author_facet | Rujun Wang |
| author_sort | Rujun Wang |
| collection | DOAJ |
| description | Introduction: Smart Grid (SG) as an intelligent system has become a key element in the efficient operation of the electrical grid. With the continuous increase in global energy demand and escalating environmental concerns, the importance of energy conservation and sustainable energy sources has become increasingly prominent. Especially in energy-intensive sectors such as large-scale buildings, energy supply and management face challenges. These structures require a significant amount of energy supply at specific times, but may encounter energy wastage issues at other times.Method: Smart Grid technology establishes a network that can transmit both electricity and data. By making full use of this data, intelligent decision-making is achieved, optimizing grid operations. Therefore, the application of Smart Grid technology to energy conservation has attracted attention and become a research focus. This study utilizes the TCN-BiGRU model, leveraging spatiotemporal sequence data and incorporating an attention mechanism to predict future energy consumption.Results: The research results indicate that the integration of Smart Grid technology, TCN, BiGRU, and the attention mechanism contributes to accurately and stably predicting energy consumption demands. This approach helps optimize energy scheduling, enhance energy utilization efficiency, and realize more intelligent, efficient, and sustainable energy management and utilization strategies.Discussion: This study provides an innovative solution for applying Smart Grid technology to energy conservation in large-scale buildings. This approach holds the potential to improve the efficiency of energy supply and management, promote sustainable energy utilization, and address the growing global energy demand and environmental issues. |
| first_indexed | 2024-03-11T20:18:10Z |
| format | Article |
| id | doaj.art-795e9e065ae2416c9cd5035168c4e136 |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-03-11T20:18:10Z |
| publishDate | 2023-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-795e9e065ae2416c9cd5035168c4e1362023-10-03T10:06:32ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2023-10-011110.3389/fenrg.2023.12830261283026Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanismRujun WangIntroduction: Smart Grid (SG) as an intelligent system has become a key element in the efficient operation of the electrical grid. With the continuous increase in global energy demand and escalating environmental concerns, the importance of energy conservation and sustainable energy sources has become increasingly prominent. Especially in energy-intensive sectors such as large-scale buildings, energy supply and management face challenges. These structures require a significant amount of energy supply at specific times, but may encounter energy wastage issues at other times.Method: Smart Grid technology establishes a network that can transmit both electricity and data. By making full use of this data, intelligent decision-making is achieved, optimizing grid operations. Therefore, the application of Smart Grid technology to energy conservation has attracted attention and become a research focus. This study utilizes the TCN-BiGRU model, leveraging spatiotemporal sequence data and incorporating an attention mechanism to predict future energy consumption.Results: The research results indicate that the integration of Smart Grid technology, TCN, BiGRU, and the attention mechanism contributes to accurately and stably predicting energy consumption demands. This approach helps optimize energy scheduling, enhance energy utilization efficiency, and realize more intelligent, efficient, and sustainable energy management and utilization strategies.Discussion: This study provides an innovative solution for applying Smart Grid technology to energy conservation in large-scale buildings. This approach holds the potential to improve the efficiency of energy supply and management, promote sustainable energy utilization, and address the growing global energy demand and environmental issues.https://www.frontiersin.org/articles/10.3389/fenrg.2023.1283026/fullsmart gridartificial intelligencedeep learningTCN-BiGRU modeldata analysisenergy consumption |
| spellingShingle | Rujun Wang Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism Frontiers in Energy Research smart grid artificial intelligence deep learning TCN-BiGRU model data analysis energy consumption |
| title | Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism |
| title_full | Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism |
| title_fullStr | Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism |
| title_full_unstemmed | Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism |
| title_short | Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism |
| title_sort | enhancing energy efficiency with smart grid technology a fusion of tcn bigru and attention mechanism |
| topic | smart grid artificial intelligence deep learning TCN-BiGRU model data analysis energy consumption |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1283026/full |
| work_keys_str_mv | AT rujunwang enhancingenergyefficiencywithsmartgridtechnologyafusionoftcnbigruandattentionmechanism |