Enhancing Whole Life Cycle Capacity Configuration for New Energy Hydrogen Production
Key Ideas
- Introduction of strategic enhancements in Whale Optimization Algorithm boosts convergence speed and accuracy.
- Case analysis results in six configuration schemes; Scheme 6 offers 7 years payback period and 12.08% internal rate of return.
- Improved Whale Optimization Algorithm outperforms conventional algorithms, elevating typical-day revenue by 3.18% to 7.44%.
- Capacity and operation scheduling optimization maximizes equipment utilization and ensures system stability.
The study focuses on addressing economic challenges in new energy hydrogen production systems through a proposed whole life cycle capacity configuration optimization model. By enhancing the Whale Optimization Algorithm with strategic improvements, the algorithm's efficiency in convergence and accuracy is significantly increased, as tested against five benchmark function types. Through case analysis, six different configuration and electrolyzer proportioning schemes are developed from a whole life cycle perspective. Scheme 6 emerges as the most promising, offering a payback period of 7 years and an internal rate of return of 12.08%. The Improved Whale Optimization Algorithm (IWOA) surpasses three traditional algorithms by enhancing typical-day revenue by percentages ranging from 3.18% to 7.44%. Emphasizing economic optimality on typical days in different seasons, the capacity configuration strategy aims to maximize equipment capacity utilization while ensuring system stability.