Notice bibliographique
Résumé
Pulverized coal power plants which fire lignites and other low-rank high-moisture coals generally operate with reduced efficiencies and increased stack emissions due to the impacts of high fuel moisture on stack heat loss and pulverizer and fan power. A process that uses plant waste heat sources to evaporate a portion of the fuel moisture from the lignite feedstock in a moving bed fluidized bed dryer (FBD) was developed in the U.S. by a team led by Great River Energy (GRE). The demonstration was conducted with Department of Energy (DOE) funding under DOE Award Number DE-FC26-04NT41763. The objectives of GRE's Lignite Fuel Enhancement project were to demonstrate reduction in lignite moisture content by using heat rejected from the power plant, apply technology at full scale at Coal Creek Station (CCS), and commercialize it. The Coal Creek Project has involved several stages, beginning with lignite drying tests in a laboratory-scale FBD at the Energy Research Center (ERC) and development of theoretical models for predicting dryer performance. Using results from these early stage research efforts, GRE built a 2 ton/hour pilot-scale dryer, and a 75 ton/hour prototype drying system at Coal Creek Station. Operated over a range of drying conditions, the results from the pilot-scale and prototype-scale dryers confirmed the performance of the basic dryer design concept and provided the knowledge base needed to scale the process up to commercial size. Phase 2 of the GRE's Lignite Fuel Enhancement project included design, construction and integration of a full-scale commercial coal drying system (four FBDs per unit) with Coal Creek Units 1 and 2 heat sources and coal handling system. Two series of controlled tests were conducted at Coal Creek Unit 1 with wet and dried lignite to determine effect of dried lignite on unit performance and emissions. Wet lignite was fired during the first, wet baseline, test series conducted in September 2009. The second test series was performed in March/April 2010 after commercial coal drying system was commissioned. Preliminary tests with dried coal were performed in March/April 2010. During the test Unit 2 was in outage and, therefore, test unit (Unit 1) was carrying entire station load and, also, supplying all auxiliary steam extractions. This resulted in higher station service, lower gross power output, and higher turbine cycle heat rate. Although, some of these effects could be corrected out, this would introduce uncertainty in calculated unit performance and effect of dried lignite on unit performance. Baseline tests with dried coal are planned for second half of 2010 when both units at Coal Creek will be in service to establish baseline performance with dried coal and determine effect of coal drying on unit performance. Application of GRE's coal drying technology will significantly enhance the value of lignite as a fuel in electrical power generation power plants. Although existing lignite power plants are designed to burn wet lignite, the reduction in moisture content will increase efficiency, reduce pollution and CO{sub 2} emissions, and improve plant economics. Furthermore, the efficiency of ultra supercritical units burning high-moisture coals will be improved significantly by using dried coal as a fuel. To date, Great River Energy has had 63 confidentiality agreements signed by vendors and suppliers of equipment and 15 utilities. GRE has had agreements signed from companies in Canada, Australia, China, India, Indonesia, and Europe.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».