Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm Algorithm
[Objective] The hydrogen production system utilizes solar energy to convert water into hydrogen, aiming to reduce carbon emissions and improve the efficiency of renewable energy utilization. However, the randomness and volatility of photovoltaic power output severely impact the stable hydrogen suppl...
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| Format: | Article |
| Language: | English |
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Energy Observer Magazine Co., Ltd.
2025-05-01
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| Series: | 南方能源建设 |
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| Online Access: | https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024-373 |
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| author | Haotian LU Shaopeng LIU Kai WANG |
| author_facet | Haotian LU Shaopeng LIU Kai WANG |
| author_sort | Haotian LU |
| collection | DOAJ |
| description | [Objective] The hydrogen production system utilizes solar energy to convert water into hydrogen, aiming to reduce carbon emissions and improve the efficiency of renewable energy utilization. However, the randomness and volatility of photovoltaic power output severely impact the stable hydrogen supply of the system. [Method] This paper proposed a capacity optimization method for photovoltaic hydrogen production systems based on a multi-objective particle swarm algorithm. In the photovoltaic hydrogen production system, chemical energy battery packs and hydrogen storage tanks were integrated to construct a photovoltaic hydrogen production-storage-supply model. A system operation strategy prioritizing hydrogen storage was designed. [Result] Taking the economic cost of the system, curtailment rate of solar power, and electricity purchase rate as optimization objectives, the multi-objective particle swarm algorithm was employed to solve the capacity configuration of the system components. The optimization results demonstrated that, while ensuring a continuous and stable hydrogen supply, the economic cost, curtailment rate, and electricity purchase rates of the system were effectively reduced. [Conclusion] The results of case analysis indicate that the proposed capacity optimization method can effectively reduce the economic costs of the system, decrease curtailment and electricity purchases, and significantly enhance the operational stability. |
| format | Article |
| id | doaj-art-6f7882cbdcde4b088e38bc4a266e02cf |
| institution | DOAJ |
| issn | 2095-8676 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Energy Observer Magazine Co., Ltd. |
| record_format | Article |
| series | 南方能源建设 |
| spelling | doaj-art-6f7882cbdcde4b088e38bc4a266e02cf2025-08-20T03:06:00ZengEnergy Observer Magazine Co., Ltd.南方能源建设2095-86762025-05-0112313314310.16516/j.ceec.2024-3732024-373Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm AlgorithmHaotian LU0Shaopeng LIU1Kai WANG2East China Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Shanghai 200063, ChinaSchool of Computer Science, Guangdong Polytechnic Normal University, Guangzhou 510665, Guangdong, ChinaEast China Electric Power Design Institute Co., Ltd. of China Power Engineering Consulting Group, Shanghai 200063, China[Objective] The hydrogen production system utilizes solar energy to convert water into hydrogen, aiming to reduce carbon emissions and improve the efficiency of renewable energy utilization. However, the randomness and volatility of photovoltaic power output severely impact the stable hydrogen supply of the system. [Method] This paper proposed a capacity optimization method for photovoltaic hydrogen production systems based on a multi-objective particle swarm algorithm. In the photovoltaic hydrogen production system, chemical energy battery packs and hydrogen storage tanks were integrated to construct a photovoltaic hydrogen production-storage-supply model. A system operation strategy prioritizing hydrogen storage was designed. [Result] Taking the economic cost of the system, curtailment rate of solar power, and electricity purchase rate as optimization objectives, the multi-objective particle swarm algorithm was employed to solve the capacity configuration of the system components. The optimization results demonstrated that, while ensuring a continuous and stable hydrogen supply, the economic cost, curtailment rate, and electricity purchase rates of the system were effectively reduced. [Conclusion] The results of case analysis indicate that the proposed capacity optimization method can effectively reduce the economic costs of the system, decrease curtailment and electricity purchases, and significantly enhance the operational stability.https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024-373capacity optimizationphotovoltaic hydrogen productionmulti-objective particle swarmeconomic efficiencycurtailment rateelectricity purchasing rate |
| spellingShingle | Haotian LU Shaopeng LIU Kai WANG Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm Algorithm 南方能源建设 capacity optimization photovoltaic hydrogen production multi-objective particle swarm economic efficiency curtailment rate electricity purchasing rate |
| title | Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm Algorithm |
| title_full | Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm Algorithm |
| title_fullStr | Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm Algorithm |
| title_full_unstemmed | Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm Algorithm |
| title_short | Capacity Optimization Method for Photovoltaic Hydrogen Production Systems Based on Multi-Objective Particle Swarm Algorithm |
| title_sort | capacity optimization method for photovoltaic hydrogen production systems based on multi objective particle swarm algorithm |
| topic | capacity optimization photovoltaic hydrogen production multi-objective particle swarm economic efficiency curtailment rate electricity purchasing rate |
| url | https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024-373 |
| work_keys_str_mv | AT haotianlu capacityoptimizationmethodforphotovoltaichydrogenproductionsystemsbasedonmultiobjectiveparticleswarmalgorithm AT shaopengliu capacityoptimizationmethodforphotovoltaichydrogenproductionsystemsbasedonmultiobjectiveparticleswarmalgorithm AT kaiwang capacityoptimizationmethodforphotovoltaichydrogenproductionsystemsbasedonmultiobjectiveparticleswarmalgorithm |