Energy management for modular proton exchange membrane water electrolyzers under fluctuating solar inputs: a constrained nonlinear optimization approach
Bibliographic record
Abstract
This study introduces an advanced nonlinear optimization-based energy management system (EMS) specifically designed for modular Proton Exchange Membrane Water Electrolyzers (PEMWE) under fluctuating solar energy conditions. To optimize system efficiency, reduce degradation, and maintain balanced stack operation, the Rotary Power Allocation Strategy (RPAS) employs a dynamic power distribution method that allocates power among multiple stacks based on current demand. A validated electrochemical model calibrated through laboratory experiments and genetic algorithm optimization serves as the foundation for the analysis. Benchmarking in this study has demonstrated the superiority of the proposed strategy to established EMS methods, such as rule-based, fuzzy logic, composite optimization, and decentralized multi-agent scheduling. In terms of system efficiency, it has been demonstrated that there is an increase of 63 % in system efficiency, a greater hydrogen yield exceeding 4200 kg per year, and a considerable reduction in stack voltage degradation. The strategy effectively addresses key limitations associated with conventional EMS approaches, ensuring consistent and equitable stack usage, thus providing a robust, scalable solution for renewable energy-driven hydrogen production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".