Standalone hybrid <scp>PV</scp>/wind/diesel‐electric generator system for a <scp>COVID</scp>‐19 quarantine center
Bibliographic record
Abstract
This work is motivated by the need in overcoming the electricity crisis in Gaza, which is initiated due to political reasons and the spread of COVID-19. Building quarantine centers is one of the most important means used in combating the COVID-19, but connecting these centers to the electricity distribution network at the appropriate time is not always possible and increases the burden on the local utility company. This article proposed a hybrid off-grid energy system (HES) to effectively energize the quarantine COVID-19 center in Gaza economically and environmentally. To achieve this aim, the estimated load profile of the quarantine center is fed to the HOMER-Pro program. In addition, the various systems components are introduced to the program, then modeled, and optimized. The developed approach was tested using a real case study considering realistic input data. HOMER-Pro program is used to simulate and optimize the system design. The results revealed the potential of the HES to provide environment-friendly, cost-effective, and affordable electricity for the studied quarantine center, as compared to just the diesel generators system. For the considered case study, it is found that the PV-wind-diesel generators HES can cover the connected load with the lowest cost ($ 0.348/kWh) in comparison to other possible HES structures. Taking into consideration the price of harmful emissions, the wining system shows a reduction of 54.89% of the cost of energy (CoE) compared to other systems. For the considered case study, it is found that a combination of 150 kW PV, 200 kW wind, and two diesel generators with capacities of 500 and 250 kW can hold 100% of the electrical load required to keep the quarantine COVID-19 center in operation. The initial capital cost of this HES is $510,576 where the share of wind energy, solar PV, inverter, and diesel-electric generators are $320,000, $83,076, $25,000, and $82,500, respectively. The replacemen cost ($55,918) is due to diesel generators. The total operation and maintainance cost (O&M) is $268,737, that is, 25.6% for wind turbines, 1.2% for inverters, and 70.7% for diesel electric generators. The PV/wind/diesel generators HES generate 1,659,038 kWh of electricity. The total energy requirement of 1,442,553 kWh, which means a surplus of 212,553 kWh of energy/year. The total energy (kWh) is an integration of energy sources which are 427,276 (25.8%), 274,500 (16.5%), and 857,263 (57.7%), due to wind, solar and diesel generators respectively. The cost of yearly consumed fuel is $437,828.769. The payback period for the winning system is 1.8 years. Finally, it is proved that the developed approach gives a reasonable solution to the decision-makers to find a fast, economic and reliable solution to energize the quarantine centers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".