Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints
To further investigate the complementary characteristics among subsystems of the combined electricity–gas–heat system (CEGHS) and to enhance the renewable energy accommodation capability, this study proposes a comprehensive optimization scheduling framework. First, an optimization model is developed...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/10/2442 |
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| author | Sheng Zou Xuanjun Zong Quan Chen Wang Zhang Hongwei Zhou |
| author_facet | Sheng Zou Xuanjun Zong Quan Chen Wang Zhang Hongwei Zhou |
| author_sort | Sheng Zou |
| collection | DOAJ |
| description | To further investigate the complementary characteristics among subsystems of the combined electricity–gas–heat system (CEGHS) and to enhance the renewable energy accommodation capability, this study proposes a comprehensive optimization scheduling framework. First, an optimization model is developed with the objective of minimizing the total system cost, incorporating key coupling components such as combined heat and power units, gas turbines, and power-to-gas (P2G) facilities. Second, to address the limitations of traditional robust optimization in managing wind power uncertainty, a distributionally robust optimization scheduling model based on Hausdorff distance is constructed, employing a data-driven uncertainty set to accurately characterize wind power fluctuations. Furthermore, to tackle the computational challenges posed by complex nonlinear equations within the model, various linearization techniques are applied, and a two-stage distributionally robust optimization approach is introduced to enhance solution efficiency. Simulation studies on an improved CEGHS system validate the feasibility and effectiveness of the proposed model, demonstrating significant improvements in both economic performance and system robustness compared to conventional methods. |
| format | Article |
| id | doaj-art-262fbc9335c74761ba0fdb2da6de48d9 |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-262fbc9335c74761ba0fdb2da6de48d92025-08-20T03:14:31ZengMDPI AGEnergies1996-10732025-05-011810244210.3390/en18102442Optimization Scheduling of Integrated Energy Systems Considering Power Flow ConstraintsSheng Zou0Xuanjun Zong1Quan Chen2Wang Zhang3Hongwei Zhou4State Grid Jiangsu Electric Power Co., Ltd., Economic and Technical Research Institute, Nanjing 211106, ChinaState Grid Jiangsu Electric Power Co., Ltd., Economic and Technical Research Institute, Nanjing 211106, ChinaState Grid Jiangsu Electric Power Co., Ltd., Economic and Technical Research Institute, Nanjing 211106, ChinaState Grid Jiangsu Electric Power Co., Ltd., Economic and Technical Research Institute, Nanjing 211106, ChinaState Grid Jiangsu Electric Power Co., Ltd., Economic and Technical Research Institute, Nanjing 211106, ChinaTo further investigate the complementary characteristics among subsystems of the combined electricity–gas–heat system (CEGHS) and to enhance the renewable energy accommodation capability, this study proposes a comprehensive optimization scheduling framework. First, an optimization model is developed with the objective of minimizing the total system cost, incorporating key coupling components such as combined heat and power units, gas turbines, and power-to-gas (P2G) facilities. Second, to address the limitations of traditional robust optimization in managing wind power uncertainty, a distributionally robust optimization scheduling model based on Hausdorff distance is constructed, employing a data-driven uncertainty set to accurately characterize wind power fluctuations. Furthermore, to tackle the computational challenges posed by complex nonlinear equations within the model, various linearization techniques are applied, and a two-stage distributionally robust optimization approach is introduced to enhance solution efficiency. Simulation studies on an improved CEGHS system validate the feasibility and effectiveness of the proposed model, demonstrating significant improvements in both economic performance and system robustness compared to conventional methods.https://www.mdpi.com/1996-1073/18/10/2442integrated energy systemwind powerdata-drivenHausdorff distancecolumn and constraint generation algorithm |
| spellingShingle | Sheng Zou Xuanjun Zong Quan Chen Wang Zhang Hongwei Zhou Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints Energies integrated energy system wind power data-driven Hausdorff distance column and constraint generation algorithm |
| title | Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints |
| title_full | Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints |
| title_fullStr | Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints |
| title_full_unstemmed | Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints |
| title_short | Optimization Scheduling of Integrated Energy Systems Considering Power Flow Constraints |
| title_sort | optimization scheduling of integrated energy systems considering power flow constraints |
| topic | integrated energy system wind power data-driven Hausdorff distance column and constraint generation algorithm |
| url | https://www.mdpi.com/1996-1073/18/10/2442 |
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