Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency
Hydrogen energy is regarded as a key path to combat climate change and promote sustainable economic and social development. The fluctuation of renewable energy leads to frequent start/stop cycles in hydrogen electrolysis equipment. However, electrochemical energy storage, with its fast response char...
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MDPI AG
2023-08-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/17/6132 |
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| author | Meng Niu Xiangjun Li Chen Sun Xiaoqing Xiu Yue Wang Mingyue Hu Haitao Dong |
| author_facet | Meng Niu Xiangjun Li Chen Sun Xiaoqing Xiu Yue Wang Mingyue Hu Haitao Dong |
| author_sort | Meng Niu |
| collection | DOAJ |
| description | Hydrogen energy is regarded as a key path to combat climate change and promote sustainable economic and social development. The fluctuation of renewable energy leads to frequent start/stop cycles in hydrogen electrolysis equipment. However, electrochemical energy storage, with its fast response characteristics, helps regulate the power of hydrogen electrolysis, enabling smooth operation. In this study, a multi-objective constrained operation optimization model for a wind/battery storage/alkaline electrolyzer system is constructed. Both profit maximization and power abandonment rate minimization are considered. In addition, some constraints, such as minimum start/stop times, upper and lower power limits, and input fluctuation limits, are also taken into account. Then, the non-dominated sorting genetic algorithm II (NSGA-II) algorithm and the entropy method are used to optimize the operation strategy of the hybrid energy system by considering dynamic hydrogen production efficiency, and through optimization to obtain the best hydrogen production power of the system under the two objectives. The change in dynamic hydrogen production efficiency is mainly related to the change in electrolyzer power, and the system can be better adjusted according to the actual supply of renewable energy to avoid the waste of renewable energy. Our results show that the distribution of Pareto solutions is uniform, which indicates the suitability of the NSGA-II algorithm. In addition, the optimal solution indicates that the battery storage and alkaline electrolyzer can complement each other in operation and achieve the absorption of wind power. The dynamic hydrogen production efficiency can make the electrolyzer operate more efficiently, which paves the way for system optimization. A sensitivity analysis reveals that the profit is sensitive to the price of hydrogen energy. |
| first_indexed | 2024-03-10T23:25:04Z |
| format | Article |
| id | doaj.art-cc2b6a7b1425494fa2e1b7fd32285265 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T23:25:04Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-cc2b6a7b1425494fa2e1b7fd322852652023-11-19T08:03:43ZengMDPI AGEnergies1996-10732023-08-011617613210.3390/en16176132Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production EfficiencyMeng Niu0Xiangjun Li1Chen Sun2Xiaoqing Xiu3Yue Wang4Mingyue Hu5Haitao Dong6National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, ChinaNational Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, ChinaNational Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, ChinaNational Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, ChinaNational Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, ChinaNational Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, ChinaNational Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, ChinaHydrogen energy is regarded as a key path to combat climate change and promote sustainable economic and social development. The fluctuation of renewable energy leads to frequent start/stop cycles in hydrogen electrolysis equipment. However, electrochemical energy storage, with its fast response characteristics, helps regulate the power of hydrogen electrolysis, enabling smooth operation. In this study, a multi-objective constrained operation optimization model for a wind/battery storage/alkaline electrolyzer system is constructed. Both profit maximization and power abandonment rate minimization are considered. In addition, some constraints, such as minimum start/stop times, upper and lower power limits, and input fluctuation limits, are also taken into account. Then, the non-dominated sorting genetic algorithm II (NSGA-II) algorithm and the entropy method are used to optimize the operation strategy of the hybrid energy system by considering dynamic hydrogen production efficiency, and through optimization to obtain the best hydrogen production power of the system under the two objectives. The change in dynamic hydrogen production efficiency is mainly related to the change in electrolyzer power, and the system can be better adjusted according to the actual supply of renewable energy to avoid the waste of renewable energy. Our results show that the distribution of Pareto solutions is uniform, which indicates the suitability of the NSGA-II algorithm. In addition, the optimal solution indicates that the battery storage and alkaline electrolyzer can complement each other in operation and achieve the absorption of wind power. The dynamic hydrogen production efficiency can make the electrolyzer operate more efficiently, which paves the way for system optimization. A sensitivity analysis reveals that the profit is sensitive to the price of hydrogen energy.https://www.mdpi.com/1996-1073/16/17/6132windbattery storagealkaline electrolyzerdynamic hydrogen production efficiencyoperation optimizationnon-dominated sorting genetic algorithm II (NSGA-II) |
| spellingShingle | Meng Niu Xiangjun Li Chen Sun Xiaoqing Xiu Yue Wang Mingyue Hu Haitao Dong Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency Energies wind battery storage alkaline electrolyzer dynamic hydrogen production efficiency operation optimization non-dominated sorting genetic algorithm II (NSGA-II) |
| title | Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency |
| title_full | Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency |
| title_fullStr | Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency |
| title_full_unstemmed | Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency |
| title_short | Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency |
| title_sort | operation optimization of wind battery storage alkaline electrolyzer system considering dynamic hydrogen production efficiency |
| topic | wind battery storage alkaline electrolyzer dynamic hydrogen production efficiency operation optimization non-dominated sorting genetic algorithm II (NSGA-II) |
| url | https://www.mdpi.com/1996-1073/16/17/6132 |
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