Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage
Off-grid renewable energy hydrogen production is a crucial approach to enhancing renewable energy utilization and improving power system stability. However, the strong stochastic fluctuations of wind and solar power pose significant challenges to electrolyzer reliability. While hybrid energy storage...
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2025-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/11/2970 |
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| author | Yiwen Geng Qi Liu Hao Zheng Shitong Yan |
| author_facet | Yiwen Geng Qi Liu Hao Zheng Shitong Yan |
| author_sort | Yiwen Geng |
| collection | DOAJ |
| description | Off-grid renewable energy hydrogen production is a crucial approach to enhancing renewable energy utilization and improving power system stability. However, the strong stochastic fluctuations of wind and solar power pose significant challenges to electrolyzer reliability. While hybrid energy storage systems (HESS) can mitigate power fluctuations, traditional power allocation rules based solely on electrolyzer power limits and HESS state of charge (SOC) boundaries result in insufficient energy supply capacity and unstable electrolyzer operation. To address this, this paper proposes a two-stage power optimization method integrating rule-based allocation with algorithmic optimization for wind–solar hydrogen production systems, considering reserved energy storage. In Stage I, hydrogen production power and HESS initial allocation are determined through the deep coupling of real-time electrolyzer operating conditions with reserved energy. Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. The proposed method enhances hydrogen production stability and HESS supply capacity while reducing renewable curtailment rates and average production costs. Case studies demonstrate its superiority over three conventional rule-based power allocation methods. |
| format | Article |
| id | doaj-art-e93c1a090a1e4166a2e1d0a30219f0d9 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-e93c1a090a1e4166a2e1d0a30219f0d92025-08-20T03:46:49ZengMDPI AGEnergies1996-10732025-06-011811297010.3390/en18112970Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of StorageYiwen Geng0Qi Liu1Hao Zheng2Shitong Yan3School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaOff-grid renewable energy hydrogen production is a crucial approach to enhancing renewable energy utilization and improving power system stability. However, the strong stochastic fluctuations of wind and solar power pose significant challenges to electrolyzer reliability. While hybrid energy storage systems (HESS) can mitigate power fluctuations, traditional power allocation rules based solely on electrolyzer power limits and HESS state of charge (SOC) boundaries result in insufficient energy supply capacity and unstable electrolyzer operation. To address this, this paper proposes a two-stage power optimization method integrating rule-based allocation with algorithmic optimization for wind–solar hydrogen production systems, considering reserved energy storage. In Stage I, hydrogen production power and HESS initial allocation are determined through the deep coupling of real-time electrolyzer operating conditions with reserved energy. Stage II employs an improved multi-objective particle swarm optimization (IMOPSO) algorithm to optimize HESS power allocation, minimizing unit hydrogen production cost and reducing average battery charge–discharge depth. The proposed method enhances hydrogen production stability and HESS supply capacity while reducing renewable curtailment rates and average production costs. Case studies demonstrate its superiority over three conventional rule-based power allocation methods.https://www.mdpi.com/1996-1073/18/11/2970off-grid wind–solar hydrogen productionsystem power optimizationtwo-stage optimizationhybrid energy storagerenewable energy utilization enhancement |
| spellingShingle | Yiwen Geng Qi Liu Hao Zheng Shitong Yan Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage Energies off-grid wind–solar hydrogen production system power optimization two-stage optimization hybrid energy storage renewable energy utilization enhancement |
| title | Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage |
| title_full | Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage |
| title_fullStr | Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage |
| title_full_unstemmed | Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage |
| title_short | Two-Stage Collaborative Power Optimization for Off-Grid Wind–Solar Hydrogen Production Systems Considering Reserved Energy of Storage |
| title_sort | two stage collaborative power optimization for off grid wind solar hydrogen production systems considering reserved energy of storage |
| topic | off-grid wind–solar hydrogen production system power optimization two-stage optimization hybrid energy storage renewable energy utilization enhancement |
| url | https://www.mdpi.com/1996-1073/18/11/2970 |
| work_keys_str_mv | AT yiwengeng twostagecollaborativepoweroptimizationforoffgridwindsolarhydrogenproductionsystemsconsideringreservedenergyofstorage AT qiliu twostagecollaborativepoweroptimizationforoffgridwindsolarhydrogenproductionsystemsconsideringreservedenergyofstorage AT haozheng twostagecollaborativepoweroptimizationforoffgridwindsolarhydrogenproductionsystemsconsideringreservedenergyofstorage AT shitongyan twostagecollaborativepoweroptimizationforoffgridwindsolarhydrogenproductionsystemsconsideringreservedenergyofstorage |