Energetic, environmental and economic aspects of a hybrid renewable energy system: a case study
Bibliographic record
Abstract
In this study, the solar irradiation and wind speed data of Balikesir in Turkey are analyzed to assess the techno-economic viability and environmental performance of a hybrid power system. Energy is estimated for a typical commercial poultry house, and a system is then designed to satisfy the load demand. As hybrid Optimization Model for Electric Renewable (HOMER) software is used for the simulation of four respective cases: Diesel only, photovoltaic (PV)–diesel–battery, wind–diesel–battery and photovoltaic–wind–diesel–battery. We also evaluate the cost, environmental advantages and benefit of the demand-side management (DSM) when renewable hybrid energy options are applied to the poultry farming. By implementing light control system and high-efficiency fans (with about 20% efficiency increase), annual electricity consumptions can be reduced by 15% with DSM. When DSM was applied to the cost of energy, certain parameters including unmet electric load, excess electricity and greenhouse gas emissions are calculated for each case. Greenhouse gas emissions are also investigated for the hybrid energy system (by integrating PV and wind turbine only into diesel system). The hybrid system thus reduces CO2 emissions from 21.8 to 10t, particulate matter (PM) from 4.1 to 1.9 kg, NOx from 0.421 to 0.221t. A break-even analysis is performed to decide the optimum distance where the hybrid energy system is more economical than the extension of the transmission line. Consequently, the results indicate that installation of the hybrid energy system is more economical than the conventional electricity network when the distance is more than 3.21 and 3.13 km for PV–wind–diesel–battery and wind–diesel–battery, respectively.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".