SUSTAINABLE POWER GENERATION IN LAKSHADWEEP: EVALUATING THE EFFECTIVENESS OF HYBRID ENERGY SYSTEMS WITH HOMER PRO SIMULATION
Bibliographic record
Abstract
Most of the inhabited islands are heavily dependent on expensive imported oil derivatives or far-flung grid connections for energy. Lakshadweep Island is a remote archipelago in the Arabian Sea that heavily depends on diesel generators, which becomes expensive and adds up to major environmental problems. This study deals with these issues through the design and analysis of sustainable hybrid energy systems using the simulation software HOMER Pro. The cost, emissions, and energy reliability form the basis for which three configurations are considered: diesel generator-wind (DG-W), diesel generator-solar (DG-S), and diesel generator-wind-solar (DG-W-S). Among the three configurations considered, the optimum best configuration is the suggested hybrid system of DG-W-S with a 1 MW diesel generator, 1.65 MW Vestas V82 wind turbine, and 1941 kW of solar panels. All of these at a levelized cost of electricity (LCOE) of $0.432 per kWh. The system will also cut annual CO2 emissions to 2,484,839 kg, while over 59% of the electricity generation comes from renewables, to add sustainability and energy independence to the land. This hybrid system, developed to fill renewable variability with a diesel backup, covers the power requirement continuously and sufficiently to meet local demand. Contributions of the work include a new scalable hybrid energy framework tailor-made for remote, grid-isolated regions. The proposed system shall look into how transitions to sustainable energy can be practically and affordably achieved, since benefits are extended to system operators, policymakers, and communities. Applications may extend to policy formulations, energy infrastructure planning, and integration of production of green hydrogen in offshore renewable technologies in similar settings. This provides the blueprint toward achieving energy security and environmental sustainability in a remote location by addressing the existing challenges and delivering actionable insights.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".