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Enregistrement W1540131126 · doi:10.5772/18505

Water Splitting Technologies for Hydrogen Cogeneration from Nuclear Energy

2011· book-chapter· en· W1540131126 sur OpenAlexafffund
Zhaolin Wang, F. Greg

Notice bibliographique

RevueInTech eBooks · 2011
Typebook-chapter
Langueen
DomaineEngineering
ThématiqueChemical Looping and Thermochemical Processes
Établissements canadiensOntario Tech University
Organismes subventionnairesAtomic Energy of Canada Limited
Mots-clésCogenerationHydrogen technologiesEnvironmental scienceFossil fuelEnergy carrierHydrogen productionHydrogenWaste managementOil refineryHydrogen fuelElectricity generationGreenhouse gasNuclear powerElectricityHydrogen economyEngineeringChemistryElectrical engineeringNuclear physicsPower (physics)

Résumé

récupéré en direct d'OpenAlex

Currently, nuclear energy is mainly utilized for the generation of electricity that is distributed to end users via power transmission networks.However, there are also other distribution forms.For example, hydrogen produced from nuclear energy is a promising future energy carrier that can be delivered to end users for purposes of heating homes, fuel supply for hydrogen vehicles and other residential applications, while simultaneously lowering the greenhouse gas emissions of otherwise using fossil fuels [Forsberg, 2002[Forsberg, , 2007]].Current industrial demand for hydrogen exists in the upgrading of heavy oils such as oil sands, refineries, fertilizers, automotive fuels, and manufacturing applications among others.Hydrogen production is currently a large, rapidly growing and profitable industry.The worldwide hydrogen market is currently estimated at about $300 billion per year, growing at about 10% per year, growing to 40% per year by 2020 and expected to reach several trillions of dollars per year by 2020 [Naterer et al., 2008].This chapter will examine the usage of nuclear energy for the cogeneration of electricity and hydrogen with water splitting technologies.In section 2 of this chapter, various hydrogen production methods will be briefly introduced and compared.The potential economics and reduction of greenhouse gas emissions with nuclear hydrogen production are examined.In section 3, matching the heat requirements of various thermochemical hydrogen cycles to the available heat from nuclear reactors (especially Generation IV) will be studied from the aspects of heat grade, magnitude, and distribution inside the cycles.The requirement of an intermediate heat exchanger between the nuclear reactor and hydrogen production plant is discussed.Long distance heat transport is examined from the aspects of the performance of working fluids, flow characteristics, and heat losses in the transport pipeline.In section 4, layout options for the integration of nuclear reactors and hydrogen production plants are discussed.In section 5, modulations of nuclear energy output and hydrogen cogeneration scales are studied, regarding the increase of the nuclear energy portion on the power grid through the adjustment of the hydrogen production rate so as to lower the needs for fossil fuels.The options for keeping the total nuclear energy output at a constant value and simultaneously varying the electricity output onto the power grid in order to approach a load following profile for peak and off-peak hours are discussed.In section 6, conclusions are provided for the cogeneration of hydrogen with nuclear heat. www.intechopen.comNuclear Power -Deployment, Operation and Sustainability 448 Environmental and economic benefits of nuclear hydrogen production methodsThe growing demand for hydrogen will have a significant impact on the economy.However, currently the major production methods for hydrogen are not clean, although its usage is clean.More than 95% of the global hydrogen is directly produced from fossil fuels, i.e., about 48% from steam methane reforming (SMR), 30% from refinery/chemical offgases, and 18% from coal gasification [NYSERDA , 2010; IEA, 2010].Water electrolysis accounts for less than 4%, and even this 4% is not "clean" because the electricity used is not fully generated from clean sources.The usage of fossil fuels to produce hydrogen has been resulting in major greenhouse gas emissions and other hazadous pollutants.Table 1 shows the CO 2 emission levels of various production methods [Wang et al., 2010].On average, the CO 2 emissions are 19 tonnes per tonne of hydrogen production, which results in 959 million tonnes of CO 2 emissions per annum.Therefore, the future hydrogen economy must be based on clean production technologies.Scientists and engineers have been attempting for years to develop new technologies for clean and efficient hydrogen production.Among the technologies, photoelectrochemical water splitting, water electrolysis with off-peak hours electricity, high temperature electrolysis (HTE), and thermochemical water splitting are promising clean options.To evaluate these options, the clean extent of the energy source, thermal efficiency and economics are the three major criteria.In terms of the clean extent, photoelectrochemical water splitting utilizes sunlight to split water into hydrogen and oxygen [Sivula et al., 2010].However, due to the intermittent nature of sunlight, this production method cannot deliver a continuous flow of hydrogen production at night and other times when sunlight is not available.Water electrolysis can utilize off-peak hour electricity from the power grid that can improve the hydrogen production economics, due to the lower price of electricity at offpeak hours.However, it may not be clean production because the power sources contributing to the power grid are not fully clean.As shown in Table 1, water electrolysis cannot even provide a better scenario than steam methane reforming and coal gasification if using the existing power grid.To make the water electrolysis "clean", the electricity must be derived from a clean source.Regarding high temperature electrolysis and thermochemical water splitting methods that utilize some heat as a portion of energy input, the same situation exists because the heat must also be derived from clean sources so as to deliver a clean production method.Solar, wind, and nuclear energy are sustainable options for energy sources [Steinfeld, 2005;Schultz et al., 2003;Kreith et al., 2007].Among these options, nuclear energy is more mature and widespread than solar and wind in current industry.Overcoming the intermittency of solar and wind energy is a long-term challenging task.Therefore, to integrate nuclear power with hydrogen production is a promising option. Method SMR Coal gasification Water electrolysisCO 2 emissions (a) CO 2 /H 2 (Moles /mole) 0.51 1.21 1.00 (b) (a) Heat from fossil fuel combustion and electricity from the existing power grid.(b) 84% of the electricity from fossil power generation (Alberta, Canada [Government of Alberta, 2008]).Table 1.CO 2 emissions with current production methods and energy sources www.intechopen.com

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,027

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,002
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,003

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,187
Écart entre enseignants0,171 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2011
Routes d'admission2
Résumé présentoui

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