Performance assessment of a Stirling engine plant for local micro-cogeneration
Bibliographic record
Abstract
In this paper, we evaluate the viability of a 9.5-kWe wooden pellet-fueled Stirling engine-based micro-cogeneration plant as a substitute for small-scale district heating. The district heating systems against which the micro-cogeneration plant is compared are based either on a pellet-fueled boiler or a ground-source heat pump. The micro-cogeneration and district heating plants are compared in terms of primary energy consumption, CO2 emissions, and feasibility of the investment. The comparison also considers an optimally operated individual 0.7-kWe pellet-fueled Stirling engine micro-cogeneration system with exhaust gas heat recovery. The study is conducted in two different climates and contributes to the knowledge base by addressing: (i) hourly changes in the Finnish electricity generation mix; and (ii) uncertainty related to what systems are used as reference and the treatment of displaced grid electricity. Our computational results suggest that when operated at constant power, the 9.5-kWe Stirling engine plant results in reduced annual primary energy use compared with any of the alternative systems. The results are not sensitive to climate or the energy efficiency or number of buildings. In comparison with the pellet-fueled district heating plant, the annual use of primary energy and CO2 emissions are reduced by a minimum of 25 and 19%, respectively. Owing to a significant displacement of grid electricity, the system's net primary energy consumption appears negative when the total built area served by the plant is less than 1200 m2. On the economic side, the maximum investment cost threshold of a CHP-based district heating system serving 10 houses or more can typically be positive when compared with oil and pellet systems, but negative when compared with a corresponding heat pump system. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".