Heat rejection design for zero liquid discharge Shand coal-fired power station integrated with CO2 capture and storage
Bibliographic record
Abstract
The integration of CCS to a coal-fired power plant not only results in the increase in water consumption and cooling duty, but also additional water discharge especially from cooling the flue gas to the much lower temperature required for the CO2 capture process. This paper presents the design of a heat rejection system for the Shand Power Station that maintains a neutral liquid impact on the existing plant while adding SO2 and CO2 capture processes. Moreover, the effect of temperatures throughout the year on heat rejection load and power consumption is investigated. The heat rejection systems were designed and optimized by using Aspen HYSYS and Aspen EDR to accommodate 245 MWth which is the additional heat rejection required for the CO2 capture process, assuming that flue gas pre-cooling is accomplished from an external source. In the case of this study, the flue gas cooler heat integration, and a quench system serviced by cooling duty which is offset from the existing unit condenser due to the integration steam source provides the required flue gas pre-cooling. The hybrid heat rejection system, which uses a dry cooler in series with a wet cooler, cools the CO2 capture plants circulating water loop from 44.5 °C to 25 °C. The wet cooling is by a Wet Surface Air Cooler (WSAC), in order to provide a second layer of protection to ensure that none of the CO2 capture chemicals will be inadvertently released to the environment. The design dry bulb and wet bulb temperatures are based on the 85 percentiles of the Estevan’s weather data for 26 years from 1991 to 2017, and are 18 °C and 13.7 °C respectively. Water produced by the capture process was utilized as the primary source for the wet cooling in order to avoid increasing the overall water draw of the facility. Using the dry cooler for rejecting the higher grade heat, and the WSAC for the lower grade heat improves cooling water temperature, while also maintaining Zero Liquid Discharge (ZLD) status. The heat load on the dry cooling and wet cooling is 156.5 and 81.8 MWth which corresponds to 67 and 33% of the total heat respectively. The effect of annual variations in dry bulb and wet bulb temperatures on the heat load of the hybrid cooling system was investigated by using Thermoflex. It was noted that the annual average heat rejection load shifted toward wet cooling system due to the lower temperature and the need to evaporate water available from the CO2 capture process with the percentage of 58% for dry cooling and 42% for wet cooling. This resulted in reduction of fan power requirements. The average fan power consumption throughout a year is 2.58 MW which is only 52% of the design case (4.96 MW).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".