Spatial-temporal load prediction of electric bus charging station based on S2TAT
In recent years, electric buses have advanced rapidly due to their green and low-carbon attributes. To address range anxiety and optimize charging strategies, accurately predicting charging load has become essential. This paper introduces a synchronous spatial-temporal attention transformer (S2TAT)...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | International Journal of Electrical Power & Energy Systems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061524006719 |
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| _version_ | 1832595416573542400 |
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| author | Guangnian Xiao Hailin Tong Yaqing Shu Anning Ni |
| author_facet | Guangnian Xiao Hailin Tong Yaqing Shu Anning Ni |
| author_sort | Guangnian Xiao |
| collection | DOAJ |
| description | In recent years, electric buses have advanced rapidly due to their green and low-carbon attributes. To address range anxiety and optimize charging strategies, accurately predicting charging load has become essential. This paper introduces a synchronous spatial-temporal attention transformer (S2TAT) model that models temporal and spatial dependencies simultaneously, utilizing operational data from new energy electric buses in Shanghai. To improve charging event prediction, we propose two key improvements: an adaptive adjacency matrix for dynamic spatial dependencies learning and a periodicity extraction mechanism for capturing cyclical patterns. These enhancements significantly boost prediction accuracy over baseline models. An ablation study further verifies the contributions of the model’s components. |
| format | Article |
| id | doaj-art-a5d521ab3db740ea9587cfe7232408f3 |
| institution | Kabale University |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-a5d521ab3db740ea9587cfe7232408f32025-01-19T06:24:04ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-03-01164110446Spatial-temporal load prediction of electric bus charging station based on S2TATGuangnian Xiao0Hailin Tong1Yaqing Shu2Anning Ni3School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China; Corresponding author.School of Economics and Management, Shanghai Maritime University, Shanghai 201306, ChinaSchool of Navigation, Wuhan University of Technology, Wuhan 430063, ChinaSchool of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaIn recent years, electric buses have advanced rapidly due to their green and low-carbon attributes. To address range anxiety and optimize charging strategies, accurately predicting charging load has become essential. This paper introduces a synchronous spatial-temporal attention transformer (S2TAT) model that models temporal and spatial dependencies simultaneously, utilizing operational data from new energy electric buses in Shanghai. To improve charging event prediction, we propose two key improvements: an adaptive adjacency matrix for dynamic spatial dependencies learning and a periodicity extraction mechanism for capturing cyclical patterns. These enhancements significantly boost prediction accuracy over baseline models. An ablation study further verifies the contributions of the model’s components.http://www.sciencedirect.com/science/article/pii/S0142061524006719Electric busCharging load predictionSpatial-temporal seriesTransformer model |
| spellingShingle | Guangnian Xiao Hailin Tong Yaqing Shu Anning Ni Spatial-temporal load prediction of electric bus charging station based on S2TAT International Journal of Electrical Power & Energy Systems Electric bus Charging load prediction Spatial-temporal series Transformer model |
| title | Spatial-temporal load prediction of electric bus charging station based on S2TAT |
| title_full | Spatial-temporal load prediction of electric bus charging station based on S2TAT |
| title_fullStr | Spatial-temporal load prediction of electric bus charging station based on S2TAT |
| title_full_unstemmed | Spatial-temporal load prediction of electric bus charging station based on S2TAT |
| title_short | Spatial-temporal load prediction of electric bus charging station based on S2TAT |
| title_sort | spatial temporal load prediction of electric bus charging station based on s2tat |
| topic | Electric bus Charging load prediction Spatial-temporal series Transformer model |
| url | http://www.sciencedirect.com/science/article/pii/S0142061524006719 |
| work_keys_str_mv | AT guangnianxiao spatialtemporalloadpredictionofelectricbuschargingstationbasedons2tat AT hailintong spatialtemporalloadpredictionofelectricbuschargingstationbasedons2tat AT yaqingshu spatialtemporalloadpredictionofelectricbuschargingstationbasedons2tat AT anningni spatialtemporalloadpredictionofelectricbuschargingstationbasedons2tat |