Research Article
Power–hydrogen system configuration integrating an improved Honey Badger Algorithm and mixed-integer programming
@ARTICLE{10.4108/ew.14130, author={Mingyuan Lai and Dandan Li and Guoxian Luo and Jieren Tan}, title={Power--hydrogen system configuration integrating an improved Honey Badger Algorithm and mixed-integer programming}, journal={EAI Endorsed Transactions on Energy Web}, volume={13}, number={1}, publisher={EAI}, journal_a={EW}, year={2026}, month={7}, keywords={capacity configuration, bi-level optimization, renewable energy integration, economic dispatch, system coordination}, doi={10.4108/ew.14130} }- Mingyuan Lai
Dandan Li
Guoxian Luo
Jieren Tan
Year: 2026
Power–hydrogen system configuration integrating an improved Honey Badger Algorithm and mixed-integer programming
EW
EAI
DOI: 10.4108/ew.14130
Abstract
INTRODUCTION: Wind power variability challenges system regulation as renewables expand. Hydrogen storage provides long-term balancing. OBJECTIVES: To optimize the operation and configuration of a wind-storage-hydrogen-gas turbine system. METHODS: An Improved Honey Badger Algorithm (IHBA) with chaotic mapping and nonlinear parameters was combined with Mixed-Integer Programming (MIP) in a bi-level framework. RESULTS: Using real data from Eastern Inner Mongolia, IHBA achieved a fitness of 0.424, outperforming PSO, GA and original HBA by 20.3%, 14.9% and 8.0%. The optimal system included 47.9 MW wind, 94.3 MWh battery, 23.8 MW electrolyzer, 38.9 t H₂ storage, 13.7 MW fuel cell and 7.1 MW H₂-blended turbine, at a minimal cost of 4.57×10⁸ CNY. Annual H₂ output reached 68,900 Nm³, storage level 0.2-0.8, LCOE 0.438 CNY/kWh and payback period 18.4 years. Additionally, comparisons across multiple energy sources, sensitivity and robustness analyses, and ablation experiments indicate that the system configuration is stable and the algorithm optimization performs reliably, providing a solid reference for design. CONCLUSION: The IHBA-MIP framework is efficient and cost-effective for power-hydrogen system design, aiding large-scale renewable integration.
Copyright © 2026 Mingyuan Lai et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
