Design of an isolated renewable hybrid energy system: a case study
Bibliographic record
Abstract
Abstract In addition to the fact that most renewable energies such as solar and wind energy have become more competitive in the global energy market, thanks to the great development in conversion technologies, it believes that renewable energy can play a crucial role in global environmental issues. However, in Palestine, the situation is different from anywhere else; renewable energy is not only an economic option, but an absolute necessity to get out of the energy crisis that Palestinian cities suffer from long years ago and continue nowadays . The cornerstone of the present research is focusing on the availability of renewable energy resources in Jenin Governorate (JG)—West Bank (WB)—Palestine. Two-year time-series of hourly solar, wind, biomass, and 1-year hourly electrical load data are used in the analysis in this paper. The energy potentials were estimated using System Advisor Model software (SAM), and the optimum combination and sizing of the hybrid renewable energy system were determined using Hybrid Optimization of Multiple Energy Resources (HOMER). The proposed Hybrid Renewable Energy System (HRES) consists of an 80 MW PV solar field, 66 MW wind farm, and 50 MW biomass system with an initial investment of $323 M. The proposed HRES generates 389 GWh/yr and is enough to meet 100% of the electrical demand of JG (372 GWh/yr) with excess in electricity generation of about 4.57% and the unmeet electric load is about 109.6 MWh/yr which is equivalent to less than 2 h off in a year. The estimated Levelized Cost of Energy (LCOE) was found as 0.313 $/kWh.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".