Wind-to-Hydrogen and Battery-Based Microgrid Systems for Residential Building Applications: A Feasibility Study in Canada
Bibliographic record
Abstract
As climate change issues escalate globally, there is a growing shift towards renewable energy solutions. This study explores the viability of a wind-to-hydrogen microgrid (MG) system and compares it with a battery-based system for supplying electricity to a grid-connected residential house in Canada. Utilizing the HOMER platform, simulation models were developed to assess two configurations: wind turbine (WT)-hydrogen system and WT-battery. These models were optimized for renewable energy fractions (RFs) ranging from 0% to 80% and included components such as WTs, fuel cells (FCs), electrolysers, hydrogen storage tanks, and batteries. The results indicate that both wind-to-hydrogen and wind-battery systems are feasible for grid-connected residential use. While increasing the RF led to higher net present costs (NPC), the cost of electricity (COE) often decreased due to the ability to sell surplus energy back to the grid. Specifically, the WT-hydrogen system achieved a COE of 0.09 CA$/kWh, and an RF of 81.4%, compared to the battery-based system with the same COE, and an RF of 80.3%. Both systems reduced carbon dioxide emissions, with net energy purchases being negative for most months, indicating more energy was sold than bought. The WT-hydrogen system was only about 6.5% more expensive than the battery system, but its costs are expected to decrease, potentially making it more advantageous due to its carbon-free emissions and higher energy density. Policy support may be needed to encourage widespread adoption.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".