Design and Analysis of a Distributed Water Heat Pump System for Near- and Net-Zero Energy Commercial Buildings
Bibliographic record
Abstract
This objective of this project is to determine the energy and environmental potential of distributed common loop water source heat pump system in a near or net-zero commercial office building, which has simultaneous heating and cooling load in winter and shoulder seasons. It is expected that the perimeter zones will have heating demand during those months, while the core zones will have consistent cooling demand throughout the year. The motive is to reclaim the rejected heat from the cooling operation and transfer it to the zones requiring heating. The building under study is a 60,000 ft2 three storey commercial office building, which has private offices along the perimeter, and open work area in the core. In the first part of the analysis, the base building has been modelled and simulated to the minimum requirements of ASHRAE 90.1-Energy Standard for Buildings except Low-Rise Residential Buildings using simulation software eQuest 3.65. The Heating Ventilation and Airconditioning (HVAC) system used is four-pipe fan coil system serving individual zones. The fan coil units use a centralized natural gas boiler and a variable capacity centrifugal chiller as external source of heating and cooling respectively. The base case consumes a total of 524.54 x 1000 kWh of electricity and 1,056 million Btu of natural gas annually. The second part is the modelling and simulation of a proposed case, which uses the same building envelope, occupancy, lighting and equipment as the base case. The HVAC system used is a distributed common loop heat pump system connected to a cooling tower for heat rejection, and a condensing boiler for heat addition. During the occupied hours, when simultaneous cooling and heating loads exist in the building, the cooling zone heat pumps rejects exhaust heat into the common loop, and the heat is subsequently used by the heat pumps operating in heating mode. Using this method, the heat pump system reduces its dependence on the cooling tower and the boiler, which only operate to maintain the loop temperature in an acceptable range. There is 9,510 kWh (1.81%) increase in electricity consumption by proposed case comparing to the base building. Natural gas consumption has been reduced by 353.65 million Btu (33.48%). Annual utility bill has increased by $1,483.00 which is 1.88% higher than the base case. 15.7 tonnes of greenhouse gas can be reduced if the proposed case is adopted.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".