A Column-Generation Approach for a Short-Term Production Planning Problem in Closed-Loop Supply Chains

We present a new model formulation for a multi-product lot-sizing problem with product returns and remanufacturing subject to a capacity constraint. The given external demand of the products has to be satisfied by remanufactured or newly produced goods. The objective is to determine a feasible production plan, which minimizes production, holding, and setup costs. As the LP relaxation of a model formulation based on the well-known CLSP leads to very poor lower bounds, we propose a column-generation approach to determine tighter bounds. The lower bound obtained by column generation can be easily transferred into a feasible solution by a truncated branch-and-bound approach using CPLEX. The results of an extensive numerical study show the high solution quality of the proposed solution approach.

The nitrogen costs of photosynthesis in a diatom under current and future pCO2

With each cellular generation, oxygenic photoautotrophs must accumulate abundant protein complexes that mediate light capture, photosynthetic electron transport and carbon fixation. In addition to this net synthesis, oxygenic photoautotrophs must counter the light-dependent photoinactivation of Photosystem II (PSII), using metabolically expensive proteolysis, disassembly, resynthesis and re-assembly of protein subunits. We used growth rates, elemental analyses and protein quantitations to estimate the nitrogen (N) metabolism costs to both accumulate the photosynthetic system and to maintain PSII function in the diatom Thalassiosira pseudonana, growing at two pCO2 levels across a range of light levels. The photosynthetic system contains c. 15-25% of total cellular N. Under low growth light, N (re)cycling through PSII repair is only c. 1% of the cellular N assimilation rate. As growth light increases to inhibitory levels, N metabolite cycling through PSII repair increases to c. 14% of the cellular N assimilation rate. Cells growing under the assumed future 750 ppmv pCO2 show higher growth rates under optimal light, coinciding with a lowered N metabolic cost to maintain photosynthesis, but then suffer greater photoinhibition of growth under excess light, coincident with rising costs to maintain photosynthesis. We predict this quantitative trait response to light will vary across taxa.

Power system stability of a small sized isolated network supplied by a combined wind-pumped storage generation system: a case study in the Canary Islands

Massive integration of renewable energy sources in electrical power systems of remote islands is a subject of current interest. The increasing cost of fossil fuels, transport costs to isolated sites and environmental concerns constitute a serious drawback to the use of conventional fossil fuel plants. In a weak electrical grid, as it is typical on an island, if a large amount of conventional generation is substituted by renewable energy sources, power system safety and stability can be compromised, in the case of large grid disturbances. In this work, a model for transient stability analysis of an isolated electrical grid exclusively fed from a combination of renewable energy sources has been studied. This new generation model will be installed in El Hierro Island, in Spain. Additionally, an operation strategy to coordinate the generation units (wind, hydro) is also established. Attention is given to the assessment of inertial energy and reactive current to guarantee power system stability against large disturbances. The effectiveness of the proposed strategy is shown by means of simulation results.

Generación de Casos de Prueba en Programación Orientada a Objetos = Test Case Generation in Object-Oriented Programming

Las pruebas de software (Testing) son en la actualidad la técnica más utilizada para la validación y la evaluación de la calidad de un programa. El testing está integrado en todas las metodologías prácticas de desarrollo de software y juega un papel crucial en el éxito de cualquier proyecto de software. Desde las unidades de código más pequeñas a los componentes más complejos, su integración en un sistema de software y su despliegue a producción, todas las piezas de un producto de software deben ser probadas a fondo antes de que el producto de software pueda ser liberado a un entorno de producción. La mayor limitación del testing de software es que continúa siendo un conjunto de tareas manuales, representando una buena parte del coste total de desarrollo. En este escenario, la automatización resulta fundamental para aliviar estos altos costes. La generación automática de casos de pruebas (TCG, del inglés test case generation) es el proceso de generar automáticamente casos de prueba que logren un alto recubrimiento del programa. Entre la gran variedad de enfoques hacia la TCG, esta tesis se centra en un enfoque estructural de caja blanca, y más concretamente en una de las técnicas más utilizadas actualmente, la ejecución simbólica. En ejecución simbólica, el programa bajo pruebas es ejecutado con expresiones simbólicas como argumentos de entrada en lugar de valores concretos. Esta tesis se basa en un marco general para la generación automática de casos de prueba dirigido a programas imperativos orientados a objetos (Java, por ejemplo) y basado en programación lógica con restricciones (CLP, del inglés constraint logic programming). En este marco general, el programa imperativo bajo pruebas es primeramente traducido a un programa CLP equivalente, y luego dicho programa CLP es ejecutado simbólicamente utilizando los mecanismos de evaluación estándar de CLP, extendidos con operaciones especiales para el tratamiento de estructuras de datos dinámicas. Mejorar la escalabilidad y la eficiencia de la ejecución simbólica constituye un reto muy importante. Es bien sabido que la ejecución simbólica resulta impracticable debido al gran número de caminos de ejecución que deben ser explorados y a tamaño de las restricciones que se deben manipular. Además, la generación de casos de prueba mediante ejecución simbólica tiende a producir un número innecesariamente grande de casos de prueba cuando es aplicada a programas de tamaño medio o grande. Las contribuciones de esta tesis pueden ser resumidas como sigue. (1) Se desarrolla un enfoque composicional basado en CLP para la generación de casos de prueba, el cual busca aliviar el problema de la explosión de caminos interprocedimiento analizando de forma separada cada componente (p.ej. método) del programa bajo pruebas, almacenando los resultados y reutilizándolos incrementalmente hasta obtener resultados para el programa completo. También se ha desarrollado un enfoque composicional basado en especialización de programas (evaluación parcial) para la herramienta de ejecución simbólica Symbolic PathFinder (SPF). (2) Se propone una metodología para usar información del consumo de recursos del programa bajo pruebas para guiar la ejecución simbólica hacia aquellas partes del programa que satisfacen una determinada política de recursos, evitando la exploración de aquellas partes del programa que violan dicha política. (3) Se propone una metodología genérica para guiar la ejecución simbólica hacia las partes más interesantes del programa, la cual utiliza abstracciones como generadores de trazas para guiar la ejecución de acuerdo a criterios de selección estructurales. (4) Se propone un nuevo resolutor de restricciones, el cual maneja eficientemente restricciones sobre el uso de la memoria dinámica global (heap) durante ejecución simbólica, el cual mejora considerablemente el rendimiento de la técnica estándar utilizada para este propósito, la \lazy initialization". (5) Todas las técnicas propuestas han sido implementadas en el sistema PET (el enfoque composicional ha sido también implementado en la herramienta SPF). Mediante evaluación experimental se ha confirmado que todas ellas mejoran considerablemente la escalabilidad y eficiencia de la ejecución simbólica y la generación de casos de prueba. ABSTRACT Testing is nowadays the most used technique to validate software and assess its quality. It is integrated into all practical software development methodologies and plays a crucial role towards the success of any software project. From the smallest units of code to the most complex components and their integration into a software system and later deployment; all pieces of a software product must be tested thoroughly before a software product can be released. The main limitation of software testing is that it remains a mostly manual task, representing a large fraction of the total development cost. In this scenario, test automation is paramount to alleviate such high costs. Test case generation (TCG) is the process of automatically generating test inputs that achieve high coverage of the system under test. Among a wide variety of approaches to TCG, this thesis focuses on structural (white-box) TCG, where one of the most successful enabling techniques is symbolic execution. In symbolic execution, the program under test is executed with its input arguments being symbolic expressions rather than concrete values. This thesis relies on a previously developed constraint-based TCG framework for imperative object-oriented programs (e.g., Java), in which the imperative program under test is first translated into an equivalent constraint logic program, and then such translated program is symbolically executed by relying on standard evaluation mechanisms of Constraint Logic Programming (CLP), extended with special treatment for dynamically allocated data structures. Improving the scalability and efficiency of symbolic execution constitutes a major challenge. It is well known that symbolic execution quickly becomes impractical due to the large number of paths that must be explored and the size of the constraints that must be handled. Moreover, symbolic execution-based TCG tends to produce an unnecessarily large number of test cases when applied to medium or large programs. The contributions of this dissertation can be summarized as follows. (1) A compositional approach to CLP-based TCG is developed which overcomes the inter-procedural path explosion by separately analyzing each component (method) in a program under test, stowing the results as method summaries and incrementally reusing them to obtain whole-program results. A similar compositional strategy that relies on program specialization is also developed for the state-of-the-art symbolic execution tool Symbolic PathFinder (SPF). (2) Resource-driven TCG is proposed as a methodology to use resource consumption information to drive symbolic execution towards those parts of the program under test that comply with a user-provided resource policy, avoiding the exploration of those parts of the program that violate such policy. (3) A generic methodology to guide symbolic execution towards the most interesting parts of a program is proposed, which uses abstractions as oracles to steer symbolic execution through those parts of the program under test that interest the programmer/tester most. (4) A new heap-constraint solver is proposed, which efficiently handles heap-related constraints and aliasing of references during symbolic execution and greatly outperforms the state-of-the-art standard technique known as lazy initialization. (5) All techniques above have been implemented in the PET system (and some of them in the SPF tool). Experimental evaluation has confirmed that they considerably help towards a more scalable and efficient symbolic execution and TCG.

About the origin of low wafer performance and crystal defect generation on seed-cast growth of industrial mono-like silicon ingots

The era of the seed-cast grown monocrystalline-based silicon ingots is coming. Mono-like, pseudomono or quasimono wafers are product labels that can be nowadays found in the market, as a critical innovation for the photovoltaic industry. They integrate some of the most favorable features of the conventional silicon substrates for solar cells, so far, such as the high solar cell efficiency offered by the monocrystalline Czochralski-Si (Cz-Si) wafers and the lower cost, high productivity and full square-shape that characterize the well-known multicrystalline casting growth method. Nevertheless, this innovative crystal growth approach still faces a number of mass scale problems that need to be resolved, in order to gain a deep, 100% reliable and worldwide market: (i) extended defects formation during the growth process; (ii) optimization of the seed recycling; and (iii) parts of the ingots giving low solar cells performance, which directly affect the production costs and yield of this approach. Therefore, this paper presents a series of casting crystal growth experiments and characterization studies from ingots, wafers and cells manufactured in an industrial approach, showing the main sources of crystal defect formation, impurity enrichment and potential consequences at solar cell level. The previously mentioned technological drawbacks are directly addressed, proposing industrial actions to pave the way of this new wafer technology to high efficiency solar cells.

Generation of human computational models with machine learning

Services in smart environments pursue to increase the quality of people?s lives. The most important issues when developing this kind of environments is testing and validating such services. These tasks usually imply high costs and annoying or unfeasible real-world testing. In such cases, artificial societies may be used to simulate the smart environment (i.e. physical environment, equipment and humans). With this aim, the CHROMUBE methodology guides test engineers when modeling human beings. Such models reproduce behaviors which are highly similar to the real ones. Originally, these models are based on automata whose transitions are governed by random variables. Automaton?s structure and the probability distribution functions of each random variable are determined by a manual test and error process. In this paper, it is presented an alternative extension of this methodology which avoids the said manual process. It is based on learning human behavior patterns automatically from sensor data by using machine learning techniques. The presented approach has been tested on a real scenario, where this extension has given highly accurate human behavior models,

Impact assessment of an integrated approach for thermal power generation plants asset management in the current energy market

El sector energético, en España en particular, y de forma similar en los principales países de Europa, cuenta con una significativa sobrecapacidad de generación, debido al rápido y significativo crecimiento de las energías renovables en los últimos diez años y la reducción de la demanda energética, como consecuencia de la crisis económica. Esta situación ha hecho que las centrales térmicas de generación de electricidad, y en concreto los ciclos combinados de gas, operen con un factor de utilización extremadamente bajo, del orden del 10%. Además de la reducción de ingresos, esto supone para las plantas trabajar continuamente fuera del punto de diseño, provocando una significativa pérdida de rendimiento y mayores costes de explotación. En este escenario, cualquier contribución que ayude a mejorar la eficiencia y la condición de los equipos, es positivamente considerada. La gestión de activos está ganando relevancia como un proceso multidisciplinar e integrado, tal y como refleja la reciente publicación de las normas ISO 55000:2014. Como proceso global e integrado, la gestión de activos requiere el manejo de diversos procesos y grandes volúmenes de información, incluso en tiempo real. Para ello es necesario utilizar tecnologías de la información y aplicaciones de software. Esta tesis desarrolla un concepto integrado de gestión de activos (Integrated Plant Management – IPM) aplicado a centrales de ciclo combinado y una metodología para estimar el beneficio aportado por el mismo. Debido a las incertidumbres asociadas a la estimación del beneficio, se ha optado por un análisis probabilístico coste-beneficio. Así mismo, el análisis cuantitativo se ha completado con una validación cualitativa del beneficio aportado por las tecnologías incorporadas al concepto de gestión integrada de activos, mediante una entrevista realizada a expertos del sector de generación de energía. Los resultados del análisis coste-beneficio son positivos, incluso en el desfavorable escenario con un factor de utilización de sólo el 10% y muy prometedores para factores de utilización por encima del 30%. ABSTRACT The energy sector particularly in Spain, and in a similar way in Europe, has a significant overcapacity due to the big growth of the renewable energies in the last ten years, and it is seriously affected by the demand decrease due to the economic crisis. That situation has forced the thermal plants and in particular, the combined cycles to operate with extremely low annual average capacity factors, very close to 10%. Apart from the incomes reduction, working in out-of-design conditions, means getting a worse performance and higher costs than expected. In this scenario, anything that can be done to improve the efficiency and the equipment condition is positively received. Asset Management, as a multidisciplinary and integrated process, is gaining prominence, reflected in the recent publication of the ISO 55000 series in 2014. Dealing Asset Management as a global, integrated process needs to manage several processes and significant volumes of information, also in real time, that requires information technologies and software applications to support it. This thesis proposes an integrated asset management concept (Integrated Plant Management-IPM) applied to combined cycle power plants and develops a methodology to assess the benefit that it can provide. Due to the difficulties in getting deterministic benefit estimation, a statistical approach has been adopted for the cot-benefit analysis. As well, the quantitative analysis has been completed with a qualitative validation of the technologies included in the IPM and their contribution to key power plant challenges by power generation sector experts. The cost- benefit analysis provides positive results even in the negative scenario of annual average capacity factor close to 10% and is promising for capacity factors over 30%.

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.

Geothermal Electricity Generation in Colorado: Actual and Perceived Obstacles to Greater Implementation

The objective of this paper is to provide an analysis of the potential and obstacles to the development of geothermal energy resources in Colorado. Geothermal energy is the only renewable resource that can provide base-load electricity. While Colorado has significant geothermal energy potential, there are no such power plants. Layers of federal and state laws and regulations represent one barrier to further geothermal development. Transmission constraints represent another major barrier. High exploration and construction costs along with high-risk profiles for geothermal projects form another major barrier. Perceived barriers such as misunderstanding the impacts, risks, and benefits of geothermal energy hinder further development. Recommendations are provided to help overcome these obstacles.

System Costs of Variable Renewable Energy in the European Union. Bruges European Economic Policy (BEEP) Briefings 37/2015

To shift to a low-carbon economy, the EU has been encouraging the deployment of variable renewable energy sources (VRE). However, VRE lack of competitiveness and their technical specificities have substantially raised the cost of the transition. Economic evaluations show that VRE life-cycle costs of electricity generation are still today higher than those of conventional thermal power plants. Member States have consequently adopted dedicated policies to support them. In addition, Ueckerdt et al. (2013) show that when integrated to the power system, VRE induce supplementary not-accounted-for costs. This paper first exposes the rationale of EU renewables goals, the EU targets and current deployment. It then explains why the LCOE metric is not appropriate to compute VRE costs by describing integration costs, their magnitude and their implications. Finally, it analyses the consequences for the power system and policy options. The paper shows that the EU has greatly underestimated VRE direct and indirect costs and that policymakers have failed to take into account the burden caused by renewable energy and the return of State support policies. Indeed, induced market distortions have been shattering the whole power system and have undermined competition in the Internal Energy Market. EU policymakers can nonetheless take full account of this negative trend and reverse it by relying on competition rules, setting-up a framework to collect robust EU-wide data, redesigning the architecture of the electricity system and relying on EU regulators.

Combined desalination and power generation using coal energy.

Phase I report. Site selection and estimated water costs based on current technology. Phase II report. Investigation of emerging technology, by-product recovery, and very large capacities. Period of performance: June 1965-Oct. 1966.

Analysis of transport costs for energy crops for use in biomass pyrolysis plant networks

Fast pyrolysis of biomass produces a liquid bio-oil that can be used for electricity generation. Bio-oil can be stored and transported so it is possible to decouple the pyrolysis process from the generation process. This allows each process to be separately optimised. It is necessary to have an understanding of the transport costs involved in order to carry out techno-economic assessments of combinations of remote pyrolysis plants and generation plants. Published fixed and variable costs for freight haulage have been used to calculate the transport cost for trucks running between field stores and a pyrolysis plant. It was found that the key parameter for estimating these costs was the number of round trips a day a truck could make rather than the distance covered. This zone costing approach was used to estimate the transport costs for a range of pyrolysis plants size for willow woodchips and baled miscanthus. The possibility of saving transport costs by producing bio-oil near to the field stores and transporting the bio-oil to a central plant was investigated and it was found that this would only be cost effective for large generation plants.

Decentralised off-grid electricity generation in India using intermediate pyrolysis of residue straws

Use of agricultural residues, like wheat or rice straw for energy generation, is the most effective measure in terms of costs and availability. The present paper focuses the need of such measure, its impact on the environment as practiced today (open burning). The application of intermediate pyrolysis technology for straw conversion in India is discussed herein. A 20 kg/h Pyroformer has been coupled to a direct quenching system without filtration. The process temperature was around 360 ?C and the yields for the product fractions, char pyrolysis oil, and non-condensable gas fractions were, 32%, 35%, and 33% respectively. The pyrolysis oil was condensed in a quenching unit using bio-diesel or diesel. The blend produced was 30 % pyrolysis liquid and 70 % bio-diesel. The engine has been tested with the pyro-oil/biooil mixture over a long term (75 hours). An overall economic analysis of the process has been carried out.

Techno-economic assessment and uncertainty analysis of thermochemical processes for second generation biofuels

Biomass-To-Liquid (BTL) is one of the most promising low carbon processes available to support the expanding transportation sector. This multi-step process produces hydrocarbon fuels from biomass, the so-called “second generation biofuels” that, unlike first generation biofuels, have the ability to make use of a wider range of biomass feedstock than just plant oils and sugar/starch components. A BTL process based on gasification has yet to be commercialized. This work focuses on the techno-economic feasibility of nine BTL plants. The scope was limited to hydrocarbon products as these can be readily incorporated and integrated into conventional markets and supply chains. The evaluated BTL systems were based on pressurised oxygen gasification of wood biomass or bio-oil and they were characterised by different fuel synthesis processes including: Fischer-Tropsch synthesis, the Methanol to Gasoline (MTG) process and the Topsoe Integrated Gasoline (TIGAS) synthesis. This was the first time that these three fuel synthesis technologies were compared in a single, consistent evaluation. The selected process concepts were modelled using the process simulation software IPSEpro to determine mass balances, energy balances and product distributions. For each BTL concept, a cost model was developed in MS Excel to estimate capital, operating and production costs. An uncertainty analysis based on the Monte Carlo statistical method, was also carried out to examine how the uncertainty in the input parameters of the cost model could affect the output (i.e. production cost) of the model. This was the first time that an uncertainty analysis was included in a published techno-economic assessment study of BTL systems. It was found that bio-oil gasification cannot currently compete with solid biomass gasification due to the lower efficiencies and higher costs associated with the additional thermal conversion step of fast pyrolysis. Fischer-Tropsch synthesis was the most promising fuel synthesis technology for commercial production of liquid hydrocarbon fuels since it achieved higher efficiencies and lower costs than TIGAS and MTG. None of the BTL systems were competitive with conventional fossil fuel plants. However, if government tax take was reduced by approximately 33% or a subsidy of £55/t dry biomass was available, transport biofuels could be competitive with conventional fuels. Large scale biofuel production may be possible in the long term through subsidies, fuels price rises and legislation.

A bidding strategy for minimizing the imbalances costs for renewable generators in Spanish power markets

The aim of this paper is to suggest a simple methodology to be used by renewable power generators to bid in Spanish markets in order to minimize the cost of their imbalances. As it is known, the optimal bid depends on the probability distribution function of the energy to produce, of the probability distribution function of the future system imbalance and of its expected cost. We assume simple methods for estimating any of these parameters and, using actual data of 2014, we test the potential economic benefit for a wind generator from using our optimal bid instead of just the expected power generation. We find evidence that Spanish wind generators savings would be from 7% to 26%.