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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Main Authors: Haotian LU, Shaopeng LIU, Kai WANG
Format: Article
Language:English
Published: Energy Observer Magazine Co., Ltd. 2025-05-01
Series:南方能源建设
Subjects:
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