A simplified Probabilistic Safety Assesment of a Steam-Methane Reforming Hydrogen Production Plant coupled to a High-Temperature Gas Cooled Nuclear Reactor

A Probabilistic Safety Assessment (PSA) is being developed for a steam-methane reforming hydrogen production plant linked to a High-Temperature Gas Cooled Nuclear Reactor (HTGR). This work is based on the Japan Atomic Energy Research Institute’s (JAERI) High Temperature Test Reactor (HTTR) prototype in Japan. This study has two major objectives: calculate the risk to onsite and offsite individuals, and calculate the frequency of different types of damage to the complex. A simplified HAZOP study was performed to identify initiating events, based on existing studies. The initiating events presented here are methane pipe break, helium pipe break, and PPWC heat exchanger pipe break. Generic data was used for the fault tree analysis and the initiating event frequency. Saphire was used for the PSA analysis. The results show that the average frequency of an accident at this complex is 2.5E-06, which is divided into the various end states. The dominant sequences result in graphite oxidation which does not pose a health risk to the population. The dominant sequences that could affect the population are those that result in a methane explosion and occur 6.6E-8/year, while the other sequences are much less frequent. The health risk presents itself if there are people in the vicinity who could be affected by the explosion. This analysis also demonstrates that an accident in one of the plants has little effect on the other. This is true given the design base distance between the plants, the fact that the reactor is underground, as well as other safety characteristics of the HTGR. Sensitivity studies are being performed in order to determine where additional and improved data is needed.

Estudio del abastecimiento energético para un barrio modelo utilizando cogeneración con pila de combustible

El alcance del proyecto es describir las directrices técnicas, la definición de criterios, y la estrategia de suministro de energía (Electricidad. Calefacción y Agua Caliente Sanitaria (ACS)) a un barrio modelo situado en un entorno urbano. De inicio se estudia los diversos modelos energéticos atendiendo a la normativa y tecnología, que se pueden aplicar en un conjunto residencial, dando como resultado el modelo propuesto de abastecimiento energético, mediante calefacción de distrito, que incorporara el diseño de una planta de producción de energía termo-eléctrica o Central de Energías basada en la tecnología de condensación de baja temperatura para calefacción y A.C.S. incluyendo una cogeneración con pila de combustible. Al mismo tiempo se han calculado y diseñado una serie de chimeneas externas para dar cumplida necesidad técnica y legal al proyecto. Estos estudios nos sirven de punto de partida para analizar la amortización de la inversión y por tanto la rentabilidad y viabilidad del proyecto, comparándose con los costes económicos derivados de la generación por sistemas convencionales. Para finalizar se hace mención a las ventajas medioambientales y a los grados de seguridad en la planta de producción ABSTRACT The scope of this work is the description of an energy supply project ( Electricity, heat and hot water ) to a housing development in a urban neibourhood , including technical criteria in their different options. Initially, several solutions are studied based on available technologies and legal restrictions. The final proposal is based on the district hearing model including electricity production in cogeneration via fuel cell technology as well as heating and hot water produced by low temperature condensation boilers It includes calculations and design criteria of the exhaust gases system and chimeneys in compliance with legal requirement in urban areas. This work also includes an economical model including payback, IRR and VAN analysis and an economical comparaison with the standard solutions. Finally, environmental advantages of the preferred solution over other standards as well as safety issues are also presented.

Design of a solar incubator. Part 1: Monitoring temperature and enthalpy gradients under commercial production

The real increase in energy prices and the intention of reducing pollutant emissions in developed countries makes interesting to use solar energy in all the processes where its application is possible. As it is demonstrated in countries sited at latitudes with optimal conditions of solar radiation and temperature, it is possible to use solar energy as heat source for small-scale hatchery [1,2], but beyond, making a design for proper installation; it is possible to use solar energy as main or support energy source in medium and large size incubators . Monitoring of a normal actual process using temperature and relative humidity sensors is necessary to know the actual operating conditions that the solar heating system must be designed and sized for. Moreover, the identification and analysis of temperature and enthalpy gradients inside the incubator is of major importance.

On track for solar grade silicon through a siemens process-type laboratory reactor: operating conditions and energy savings

Polysilicon cost impacts significantly on the photovoltaics (PV) cost and on the energy payback time. Nowadays, the besetting production process is the so called Siemens process, polysilicon deposition by chemical vapor deposition (CVD) from Trichlorosilane. Polysilicon purification level for PV is to a certain extent less demanding that for microelectronics. At the Instituto de Energía Solar (IES) research on this subject is performed through a Siemens process-type laboratory reactor. Through the laboratory CVD prototype at the IES laboratories, valuable information about the phenomena involved in the polysilicon deposition process and the operating conditions is obtained. Polysilicon deposition by CVD is a complex process due to the big number of parameters involved. A study on the influence of temperature and inlet gas mixture composition on the polysilicon deposition growth rate, based on experimental experience, is shown. Moreover, CVD process accounts for the largest contribution to the energy consumption of the polysilicon production. In addition, radiation phenomenon is the major responsible for low energetic efficiency of the whole process. This work presents a model of radiation heat loss, and the theoretical calculations are confirmed experimentally through a prototype reactor at our disposal, yielding a valuable know-how for energy consumption reduction at industrial Siemens reactors.

Heat losses in a CVD reactor for polysilicon: comprehensive model and experimental validation

This work addresses heat losses in a CVD reactor for polysilicon production. Contributions to the energy consumption of the so-called Siemens process are evaluated, and a comprehensive model for heat loss is presented. A previously-developed model for radiative heat loss is combined with conductive heat loss theory and a new model for convective heat loss. Theoretical calculations are developed and theoretical energy consumption of the polysilicon deposition process is obtained. The model is validated by comparison with experimental results obtained using a laboratory-scale CVD reactor. Finally, the model is used to calculate heat consumption in a 36-rod industrial reactor; the energy consumption due to convective heat loss per kilogram of polysilicon produced is calculated to be 22-30 kWh/kg along a deposition process.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Understanding and improving the chemical vapor deposition process for solar grade silicon production

Esta Tesis Doctoral se centra en la investigación del proceso de producción de polisilicio para aplicaciones fotovoltaicas (FV) por la vía química; mediante procesos de depósito en fase vapor (CVD). El polisilicio para la industria FV recibe el nombre de silicio de grado solar (SoG Si). Por un lado, el proceso que domina hoy en día la producción de SoG Si está basado en la síntesis, destilación y descomposición de triclorosilano (TCS) en un reactor CVD -denominado reactor Siemens-. El material obtenido mediante este proceso es de muy alta pureza, pero a costa de un elevado consumo energético. Así, para alcanzar los dos principales objetivos de la industria FV basada en silicio, bajos costes de producción y bajo tiempo de retorno de la energía invertida en su fabricación, es esencial disminuir el consumo energético de los reactores Siemens. Por otro lado, una alternativa al proceso Siemens considera la descomposición de monosilano (MS) en un reactor de lecho fluidizado (FBR). Este proceso alternativo tiene un consumo energético mucho menor que el de un reactor Siemens, si bien la calidad del material resultante es también menor; pero ésta puede ser suficiente para la industria FV. A día de hoy los FBR deben aún abordar una serie de retos para que su menor consumo energético sea una ventaja suficiente comparada con otras desventajas de estos reactores. En resumen, la investigación desarrollada se centra en el proceso de depósito de polysilicio por CVD a partir de TCS -reactor Siemens-; pero también se investiga el proceso de producción de SoG Si en los FBR exponiendo las fortalezas y debilidades de esta alternativa. Para poder profundizar en el conocimiento del proceso CVD para la producción de polisilicio es clave el conocimiento de las reacciones químicas fundamentales y cómo éstas influencian la calidad del producto resultante, al mismo tiempo que comprender los fenómenos responsables del consumo energético. Por medio de un reactor Siemens de laboratorio en el que se llevan a cabo un elevado número de experimentos de depósito de polisilicio de forma satisfactoria se adquiere el conocimiento previamente descrito. Se pone de manifiesto la complejidad de los reactores CVD y de los problemas asociados a la pérdidas de calor de estos procesos. Se identifican las contribuciones a las pérdidas de calor de los reactores CVD, éstas pérdidas de calor son debidas principalmente a los fenómenos de radiación y, conducción y convección vía gases. En el caso de los reactores Siemens el fenómeno que contribuye en mayor medida al alto consumo energético son las pérdidas de calor por radiación, mientras que en los FBRs tanto la radiación como el calor transferido por transporte másico contribuyen de forma importante. Se desarrolla un modelo teórico integral para el cálculo de las pérdidas de calor en reactores Siemens. Este modelo está formado a su vez por un modelo para la evaluación de las pérdidas de calor por radiación y modelos para la evaluación de las pérdidas de calor por conducción y convección vía gases. Se ponen de manifiesto una serie de limitaciones del modelo de pérdidas de calor por radiación, y se desarrollan una serie de modificaciones que mejoran el modelo previo. El modelo integral se valida por medio un reactor Siemens de laboratorio, y una vez validado se presenta su extrapolación a la escala industrial. El proceso de conversión de TCS y MS a polisilicio se investiga mediante modelos de fluidodinámica computacional (CFD). Se desarrollan modelados CFD para un reactor Siemens de laboratorio y para un prototipo FBR. Los resultados obtenidos mediante simulación son comparados, en ambos casos, con resultados experimentales. Los modelos desarrollados se convierten en herramientas para la identificación de aquellos parámetros que tienen mayor influencia en los procesos CVD. En el caso del reactor Siemens, ambos modelos -el modelo integral y el modelado CFD permiten el estudio de los parámetros que afectan en mayor medida al elevado consumo energético, y mediante su análisis se sugieren modificaciones para este tipo de reactores que se traducirían en un menor número de kilovatios-hora consumidos por kilogramo de silicio producido. Para el caso del FBR, el modelado CFD permite analizar el efecto de una serie de parámetros sobre la distribución de temperaturas en el lecho fluidizado; y dicha distribución de temperaturas está directamente relacionada con los principales retos de este tipo de reactores. Por último, existen nuevos conceptos de depósito de polisilicio; éstos se aprovechan de la ventaja teórica de un mayor volumen depositado por unidad de tiempo -cuando una mayor superficie de depósito está disponible- con el objetivo de reducir la energía consumida por los reactores Siemens. Estos conceptos se exploran mediante cálculos teóricos y pruebas en el reactor Siemens de laboratorio. ABSTRACT This Doctoral Thesis comprises research on polysilicon production for photovoltaic (PV) applications through the chemical route: chemical vapor deposition (CVD) process. PV polysilicon is named solar grade silicon (SoG Si). On the one hand, the besetting CVD process for SoG Si production is based on the synthesis, distillation, and decomposition of thriclorosilane (TCS) in the so called Siemens reactor; high purity silicon is obtained at the expense of high energy consumption. Thus, lowering the energy consumption of the Siemens process is essential to achieve the two wider objectives for silicon-based PV technology: low production cost and low energy payback time. On the other hand, a valuable variation of this process considers the use of monosilane (MS) in a fluidized bed reactor (FBR); lower output material quality is obtained but it may fulfil the requirements for the PV industry. FBRs demand lower energy consumption than Siemens reactors but further research is necessary to address the actual challenges of these reactors. In short, this work is centered in polysilicon CVD process from TCS -Siemens reactor-; but it also offers insights on the strengths and weaknesses of the FBR for SoG Si production. In order to aid further development in polysilicon CVD is key the understanding of the fundamental reactions and how they influence the product quality, at the same time as to comprehend the phenomena responsible for the energy consumption. Experiments conducted in a laboratory Siemens reactor prove the satisfactory operation of the prototype reactor, and allow to acquire the knowledge that has been described. Complexity of the CVD reactors is stated and the heat loss problem associated with polysilicon CVD is addressed. All contributions to the energy consumption of Siemens reactors and FBRs are put forward; these phenomena are radiation and, conduction and convection via gases heat loss. In a Siemens reactor the major contributor to the energy consumption is radiation heat loss; in case of FBRs radiation and heat transfer due to mass transport are both important contributors. Theoretical models for radiation, conduction and convection heat loss in a Siemens reactor are developed; shaping a comprehensive theoretical model for heat loss in Siemens reactors. Limitations of the radiation heat loss model are put forward, and a novel contribution to the existing model is developed. The comprehensive model for heat loss is validated through a laboratory Siemens reactor, and results are scaled to industrial reactors. The process of conversion of TCS and MS gases to solid polysilicon is investigated by means of computational fluid-dynamics models. CFD models for a laboratory Siemens reactor and a FBR prototype are developed. Simulated results for both CVD prototypes are compared with experimental data. The developed models are used as a tool to investigate the parameters that more strongly influence both processes. For the Siemens reactors, both, the comprehensive theoretical model and the CFD model allow to identify the parameters responsible for the great power consumption, and thus, suggest some modifications that could decrease the ratio kilowatts-hour per kilogram of silicon produced. For the FBR, the CFD model allows to explore the effect of a number of parameters on the thermal distribution of the fluidized bed; that is the main actual challenge of these type of reactors. Finally, there exist new deposition surface concepts that take advantage of higher volume deposited per time unit -when higher deposition area is available- trying to reduce the high energy consumption of the Siemens reactors. These novel concepts are explored by means of theoretical calculations and tests in the laboratory Siemens prototype.

Effect of level of fiber of the rearing phase diets on egg production, digestive tract traits, and body measurements of brown egg-laying hens fed diets differing in energy concentration

This research studied the effects of additional fiber in the rearing phase diets on egg production, gastrointestinal tract (GIT) traits, and body measurements of brown egg-laying hens fed diets varying in energy concentration from 17 to 46 wk of age. The experiment was completely randomized with 10 treatments arranged as a 5 × 2 factorial with 5 rearing phase diets and 2 laying phase diets. During the rearing phase, treatments consisted of a control diet based on cereals and soybean meal and 4 additional diets with a combination of 2 fiber sources (cereal straw and sugar beet pulp, SBP) at 2 levels (2 and 4%). During the laying phase, diets differed in energy content (2,650 vs. 2,750 kcal AMEn/kg) but had the same amino acid content per unit of energy. The rearing diet did not affect any production trait except egg production that was lower in birds fed SBP than in birds fed straw (91.6 and 94.1%, respectively; P < 0.05). Laying hens fed the high energy diet had lower feed intake (P < 0.001), better feed conversion (P < 0.01), and greater BW gain (P < 0.05) than hens fed the low energy diet but egg production and egg weight were not affected. At 46 wk of age, none of the GIT traits was affected by previous dietary treatment. At this age, hen BW was positively related with body length (r = 0.500; P < 0.01), tarsus length (r = 0.758; P < 0.001), and body mass index (r = 0.762; P < 0.001) but no effects of type of diet on these traits were detected. In summary, the inclusion of up to 4% of a fiber source in the rearing diets did not affect GIT development of the hens but SBP reduced egg production. An increase in the energy content of the laying phase diet reduced ADFI and improved feed efficiency but did not affect any of the other traits studied.

Renewable Energy Generation at Copper Mountain Resort

Copper Mountain, a Colorado ski area, evaluated onsite renewable energy generation to save on energy costs and reduce carbon emissions. Multiple resort locations were analyzed to determine suitable sites for implementation of solar electricity generation, wind electricity generation and biomass heat production. Potential project sites were assessed based on four criteria: costs and financial returns, environmental impacts, implementation and maintenance, and public relations/marketing opportunities. Solar projects had the lowest capital cost of the three types of renewable energy, and wind projects had high capital costs and low financial returns. Biomass projects had high capital costs, solid financial projections and good marketing value compared to wind and solar technologies. Project implementation recommendations were given based upon the evaluation.

Retrofit of heat exchanger networks with pressure recovery of process streams at sub-ambient conditions

This paper presents a new mathematical programming model for the retrofit of heat exchanger networks (HENs), wherein the pressure recovery of process streams is conducted to enhance heat integration. Particularly applied to cryogenic processes, HENs retrofit with combined heat and work integration is mainly aimed at reducing the use of expensive cold services. The proposed multi-stage superstructure allows the increment of the existing heat transfer area, as well as the use of new equipment for both heat exchange and pressure manipulation. The pressure recovery of streams is carried out simultaneously with the HEN design, such that the process conditions (streams pressure and temperature) are variables of optimization. The mathematical model is formulated using generalized disjunctive programming (GDP) and is optimized via mixed-integer nonlinear programming (MINLP), through the minimization of the retrofit total annualized cost, considering the turbine and compressor coupling with a helper motor. Three case studies are performed to assess the accuracy of the developed approach, including a real industrial example related to liquefied natural gas (LNG) production. The results show that the pressure recovery of streams is efficient for energy savings and, consequently, for decreasing the HEN retrofit total cost especially in sub-ambient processes.