Feasibility Study of Stand-Alone PV-Wind-Biomass Hybrid Energy System in Australia
Bibliographic record
Abstract
This paper presents a feasibility study of photovoltaic (PV), wind, biomass and battery storage based hybrid renewable energy (HRE) system providing electricity to residential area in Australia. The system with load of 200 kWh · day <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> is analyzed through the environmental and economic aspects. The study computes the net present cost (NPC, $), cost of energy (COE, $ · KWh <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) and the emissions (kg · year <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ) of greenhouse gas (GHG) of the HRE system running under the specific renewable energy resource mentioned above. The monthly daily mean global solar irradiance and wind speed data of the capitals of the seven regions of the six states and various territories of Australia (Queensland, Northern Territory, South Australia, Tasmania, Victoria, Western Australia and New South Wales) are generated by the RETScreen Clean Energy Project Analysis Software produced by Natural Resources Canada. The long-term continuous implementation of the system is simulated. The software HOMER produced by the National Renewable Energy Laboratory is used as a simulating tool. Their cost and emissions are compared with each other among the systems. It is found that an off-grid PV-wind-biomass HRE system is an effective way of emissions reduction and it does not increase the investment of the energy system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".