Optimal Design and Cost Analysis of Microgrid Hybrid Renewable Energy Systems with Hydrogen Production and Storage and Battery
Bibliographic record
Abstract
Concern about controlling climate change, and recognition of the urgent need to reduce the quantum of greenhouse gases emitted worldwide, has kindled interest in alternative sources of energy. Particular attention is currently on microgrid (MG) hybrid renewable energy systems. This work has been undertaken to appraise the viability of applying MGs with both hydrogen production and storage, and battery options to supply electricity for off-grid applications. Simulation models were created in HOMER platform to analyze and optimize the performance of the considered configurations for an off-grid residential building in Canada. Two distinct system arrangements were assessed, which comprised of photovoltaic (PV) panels, wind turbines (WTs), fuel cells (FCs), electrolysers, hydrogen tanks, battery storage, diesel generators, converters, and controllers. The outcomes demonstrated that both systems are viable selections. Furthermore, it was proven that the MG battery-based system is the better arrangement for the household considered that results to the minimum levelized cost of energy (COE) and a renewable fraction (RF) of $0.36/kWh and 82.2%, respectively, compared to the hydrogen-based one, which has a COE and an RF of $0.57/kWh and 70.1%, respectively. With increasing recognition of, and interest in hydrogen technology, it is hoped that advances and discoveries in this beneficial technology will naturally be made, leading to significant reductions in the present costliness of operating the system.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 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".