A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration.
Microgrid systems incorporating carbon trading mechanisms and demand response (DR) demonstrate significant potential for facilitating low-carbon societies and advancing sustainable energy development. The optimal operation of microgrid systems faces challenges due to: (1) response rate disparities a...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0327523 |
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| author | Jue Wang Zhiwei Cheng Dejun Lu Mingxiang Zhu Dengfeng Zhang |
| author_facet | Jue Wang Zhiwei Cheng Dejun Lu Mingxiang Zhu Dengfeng Zhang |
| author_sort | Jue Wang |
| collection | DOAJ |
| description | Microgrid systems incorporating carbon trading mechanisms and demand response (DR) demonstrate significant potential for facilitating low-carbon societies and advancing sustainable energy development. The optimal operation of microgrid systems faces challenges due to: (1) response rate disparities among cooling, heating, and power equipment, (2) load prediction inaccuracies, and (3) complex interdependencies in multi-energy device coupling. To address these challenges, we propose a two-layer rolling optimization framework with multi-time scale scheduling for CCHP microgrid systems. First, wind and photovoltaic power generation are predicted using a CNN-ATT-BiLSTM model, with comparative analysis against standalone CNN, BiLSTM and CNN-LSTM models. Second, we establish a multi-time scale optimization model for CCHP-MG systems, with operating cost minimization as the objective function. Finally, we evaluate four operational scenarios incorporating DR and carbon trading mechanisms, with comparative cost analysis. Case study results demonstrate that the proposed model simultaneously satisfies cooling/heating/power demand while mitigating stochastic supply-demand fluctuations through multi-temporal resolution coordination. |
| format | Article |
| id | doaj-art-08a475f0588c48e5b0d2de71b8a19bdf |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-08a475f0588c48e5b0d2de71b8a19bdf2025-08-20T03:31:40ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01207e032752310.1371/journal.pone.0327523A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration.Jue WangZhiwei ChengDejun LuMingxiang ZhuDengfeng ZhangMicrogrid systems incorporating carbon trading mechanisms and demand response (DR) demonstrate significant potential for facilitating low-carbon societies and advancing sustainable energy development. The optimal operation of microgrid systems faces challenges due to: (1) response rate disparities among cooling, heating, and power equipment, (2) load prediction inaccuracies, and (3) complex interdependencies in multi-energy device coupling. To address these challenges, we propose a two-layer rolling optimization framework with multi-time scale scheduling for CCHP microgrid systems. First, wind and photovoltaic power generation are predicted using a CNN-ATT-BiLSTM model, with comparative analysis against standalone CNN, BiLSTM and CNN-LSTM models. Second, we establish a multi-time scale optimization model for CCHP-MG systems, with operating cost minimization as the objective function. Finally, we evaluate four operational scenarios incorporating DR and carbon trading mechanisms, with comparative cost analysis. Case study results demonstrate that the proposed model simultaneously satisfies cooling/heating/power demand while mitigating stochastic supply-demand fluctuations through multi-temporal resolution coordination.https://doi.org/10.1371/journal.pone.0327523 |
| spellingShingle | Jue Wang Zhiwei Cheng Dejun Lu Mingxiang Zhu Dengfeng Zhang A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration. PLoS ONE |
| title | A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration. |
| title_full | A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration. |
| title_fullStr | A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration. |
| title_full_unstemmed | A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration. |
| title_short | A multi-time scale rolling optimization framework for low-carbon operation of CCHP microgrids with demand response integration. |
| title_sort | multi time scale rolling optimization framework for low carbon operation of cchp microgrids with demand response integration |
| url | https://doi.org/10.1371/journal.pone.0327523 |
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