Capacity Optimization for Coordinated Operation of Hybrid Electrolytic Cells Based on Wavelet Packet
Hydrogen production through electrolysis of water can achieve efficient, stable and diversified utilization of renewable energy. To this end, a hybrid electrolyzer system for hydrogen production based on bi-layer optimization is constructed. Firstly, the wind and photovoltaic power is decomposed into high-frequency and low-frequency components by an adaptive wavelet packet. The low-frequency power is allocated to the alkaline electrolyzers (AWE) to ensure its stability, and the high-frequency power is allocated to the proton exchange membrane electrolyzers (PEM) with a faster response characteristic, thereby improving the energy utilization rate. This paper proposes a bi-layer optimization model, in which the upper-layer objective is to minimize the cost of mixed hydrogen production, and the lower-layer optimization objective is to maximize the utilization rate of renewable energy. The differential evolution algorithm optimizes the upper-layer objective, with results sent to the lower layer. Then, the YALMIP toolbox is used to solve the lower-layer objective. Through case analysis, the optimal proportion of AWE and PEM hydrogen electrolyzers obtained by this optimization method is 89.5 and 10.5, respectively. Compared with a single type of electrolyzer, the method proposed in this paper effectively improves the energy utilization efficiency and reduces the cost of hydrogen production.
Authors
- Yi Yang (ORCID: https://orcid.org/0000-0002-7843-9844)
- Bowen Zhou (ORCID: https://orcid.org/0000-0002-7400-6603)
- Shunjiang Wang (ORCID: https://orcid.org/0000-0002-1762-4835)
- Juan Zhang (ORCID: https://orcid.org/0000-0002-7545-0239)
- Bo Yang (ORCID: https://orcid.org/0000-0002-8107-8322)
- Xu Yang (ORCID: https://orcid.org/0000-0001-9158-9524)
- Guiping Zhou (ORCID: https://orcid.org/0000-0002-3351-8098)
Institutions
- Northeastern University (CN)
Publication Details
- Journal
- Sustainability
- Published
- 2025-07-13
- DOI
- https://doi.org/10.3390/su17146412
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China