Feasibility and techno-economic analysis of stand-alone and grid-connected PV/Wind/Diesel/Batt hybrid energy system: A case study
Bibliographic record
Abstract
In this study, the economic and environmental benefits of stand-alone and grid integration are thoroughly analyzed with different system configurations of a PV/Wind/Diesel/Battery based hybrid energy system (HES) for five different climatic regions using hybrid optimization model for electric renewables (HOMER). A detailed techno-economic study of optimized hybrid systems is further examined by integrating the grid-connected option. The environmental benefits of HESs are discussed. The sensitivity of various sell-back price to the national grid is also investigated. Additionally, the barriers and opportunities of installing such projects in the off-grid regions are discussed. Results indicate that the cost of energy (COE, $/kWh) and the net present cost (NPC, $) of the stand-alone hybrid PV/Diesel/Battery for the Rajshahi region are slightly lower compared to other areas, considering the cost and environmental emissions. The same system in Chattogram shows great potential both financially and environmentally, over the other climatic zones. The grid-connected HES with the sell-back option offers significant cost-benefits (0.07$/kWh), even over the grid tariff (0.10$/kWh). Similar revenues can be attained with the grid-connected PV/Battery-based system as substantial amount of excess energy could be supplied to the grid facilities. In the grid integrated HES, around 45,582 kg-CO2/yr could be saved compared to grid only system, whereas this amount is 32,905 kg-CO2/yr over the stand-alone hybrid PV/Diesel/Battery one.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".