A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method
In general, microgrids have a high renewable energy abandonment rate and high grid construction and operation costs. To improve the microgrid renewable energy utilization rate, the economic advantages, and environmental safety of power grid operation, we propose a hybrid energy storage capacity opti...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/20/7593 |
| _version_ | 1797473573938397184 |
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| author | Xianjing Zhong Xianbo Sun Yuhan Wu |
| author_facet | Xianjing Zhong Xianbo Sun Yuhan Wu |
| author_sort | Xianjing Zhong |
| collection | DOAJ |
| description | In general, microgrids have a high renewable energy abandonment rate and high grid construction and operation costs. To improve the microgrid renewable energy utilization rate, the economic advantages, and environmental safety of power grid operation, we propose a hybrid energy storage capacity optimization method for a wind–solar–diesel grid-connected microgrid system, based on an augmented ε- constraint method. First, the battery is coupled with a seasonal hydrogen energy storage system to establish a hybrid energy storage model that avoids the shortcomings of traditional microgrid systems, such as a single energy storage mode and a small capacity. Second, by considering the comprehensive cost and carbon emissions of the power grid within the planning period as the objective function, the abandonment rate of renewable energy as the evaluation index, and the electric energy storage and seasonal hydrogen energy storage system operating conditions as the main constraints, the capacity allocation model of the microgrid can be constructed. Finally, an augmented ε- constraint method is implemented to optimize the model above; the entropy–TOPSIS method is used to select the configuration scheme. By comparative analysis, the results show that the optimization method can effectively improve the local absorption rate of wind and solar radiation, and significantly reduce the carbon emissions of microgrids. |
| first_indexed | 2024-03-09T20:17:27Z |
| format | Article |
| id | doaj.art-5dccb3db8d844c708a65cb23ce935779 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T20:17:27Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-5dccb3db8d844c708a65cb23ce9357792023-11-23T23:57:25ZengMDPI AGEnergies1996-10732022-10-011520759310.3390/en15207593A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint MethodXianjing Zhong0Xianbo Sun1Yuhan Wu2College of Intelligent Science and Engineering, Hubei Minzu University, Enshi 445000, ChinaCollege of Intelligent Science and Engineering, Hubei Minzu University, Enshi 445000, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, ChinaIn general, microgrids have a high renewable energy abandonment rate and high grid construction and operation costs. To improve the microgrid renewable energy utilization rate, the economic advantages, and environmental safety of power grid operation, we propose a hybrid energy storage capacity optimization method for a wind–solar–diesel grid-connected microgrid system, based on an augmented ε- constraint method. First, the battery is coupled with a seasonal hydrogen energy storage system to establish a hybrid energy storage model that avoids the shortcomings of traditional microgrid systems, such as a single energy storage mode and a small capacity. Second, by considering the comprehensive cost and carbon emissions of the power grid within the planning period as the objective function, the abandonment rate of renewable energy as the evaluation index, and the electric energy storage and seasonal hydrogen energy storage system operating conditions as the main constraints, the capacity allocation model of the microgrid can be constructed. Finally, an augmented ε- constraint method is implemented to optimize the model above; the entropy–TOPSIS method is used to select the configuration scheme. By comparative analysis, the results show that the optimization method can effectively improve the local absorption rate of wind and solar radiation, and significantly reduce the carbon emissions of microgrids.https://www.mdpi.com/1996-1073/15/20/7593microgridseasonal hydrogen energy storagehybrid energy storage systemaugmented ε- constraint methodmultiobjective optimization |
| spellingShingle | Xianjing Zhong Xianbo Sun Yuhan Wu A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method Energies microgrid seasonal hydrogen energy storage hybrid energy storage system augmented ε- constraint method multiobjective optimization |
| title | A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method |
| title_full | A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method |
| title_fullStr | A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method |
| title_full_unstemmed | A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method |
| title_short | A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε- Constraint Method |
| title_sort | capacity optimization method for a hybrid energy storage microgrid system based on an augmented ε constraint method |
| topic | microgrid seasonal hydrogen energy storage hybrid energy storage system augmented ε- constraint method multiobjective optimization |
| url | https://www.mdpi.com/1996-1073/15/20/7593 |
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