Techno-economic analysis of renewable energy source options for a district heating project
Bibliographic record
Abstract
With the increased interest in exploiting renewable energy sources for district heating applications, the economic comparison of viable options has been considered as an important step in making a sound decision. In this paper, the economic performance of several energy options for a district heating system in Vancouver, British Columbia, is studied. The considered district heating system includes a 10 MW peaking/ backup natural gas boiler to provide about 40% of the annual energy requirement and a 2.5 MW base-load system. The energy options for the base-load system include: wood pellet, sewer heat, and geothermal heat. Present values of initial and operating costs of each system were calculated over 25-year service life of the systems, considering depreciation and salvage as a negative cost item. It was shown that the wood pellet heat producing technologies provided less expensive energy followed by the sewer heat recovery, geothermal and natural gas systems. Among wood pellet technologies, the grate burner was a less expensive option than powder and gasifier technologies. It was found that using natural gas as a fuel source for the peaking/backup system accounted for more than 40% of the heat production cost for the considered district heating center. This is mainlymore » due to the high natural gas prices which cause high operating costs over the service life of the district heating system. Variations in several economic inputs did not change the ranking of the technology options in the sensitivity analysis. However, it was found that the results were more sensitive to changes in operating costs of the system than changes in initial investment. It is economical to utilize wood pellet boilers to provide the base-load energy requirement of district heating systems Moreover, the current business approach to use natural gas systems for peaking and backup in district heating systems could increase the cost of heat production significantly.« less
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".