Contributions to uncertainty reduction in the estimation of PV plants performance

Esta tesis doctoral presenta un procedimiento integral de control de calidad en centrales fotovoltaicas, que comprende desde la fase inicial de estimación de las expectativas de producción hasta la vigilancia del funcionamiento de la instalación una vez en operación, y que permite reducir la incertidumbre asociada su comportamiento y aumentar su fiabilidad a largo plazo, optimizando su funcionamiento. La coyuntura de la tecnología fotovoltaica ha evolucionado enormemente en los últimos años, haciendo que las centrales fotovoltaicas sean capaces de producir energía a unos precios totalmente competitivos en relación con otras fuentes de energía. Esto hace que aumente la exigencia sobre el funcionamiento y la fiabilidad de estas instalaciones. Para cumplir con dicha exigencia, es necesaria la adecuación de los procedimientos de control de calidad aplicados, así como el desarrollo de nuevos métodos que deriven en un conocimiento más completo del estado de las centrales, y que permitan mantener la vigilancia sobre las mismas a lo largo del tiempo. Además, los ajustados márgenes de explotación actuales requieren que durante la fase de diseño se disponga de métodos de estimación de la producción que comporten la menor incertidumbre posible. La propuesta de control de calidad presentada en este trabajo parte de protocolos anteriores orientados a la fase de puesta en marcha de una instalación fotovoltaica, y las complementa con métodos aplicables a la fase de operación, prestando especial atención a los principales problemas que aparecen en las centrales a lo largo de su vida útil (puntos calientes, impacto de la suciedad, envejecimiento…). Además, incorpora un protocolo de vigilancia y análisis del funcionamiento de las instalaciones a partir de sus datos de monitorización, que incluye desde la comprobación de la validez de los propios datos registrados hasta la detección y el diagnóstico de fallos, y que permite un conocimiento automatizado y detallado de las plantas. Dicho procedimiento está orientado a facilitar las tareas de operación y mantenimiento, de manera que se garantice una alta disponibilidad de funcionamiento de la instalación. De vuelta a la fase inicial de cálculo de las expectativas de producción, se utilizan los datos registrados en las centrales para llevar a cabo una mejora de los métodos de estimación de la radiación, que es la componente que más incertidumbre añade al proceso de modelado. El desarrollo y la aplicación de este procedimiento de control de calidad se han llevado a cabo en 39 grandes centrales fotovoltaicas, que totalizan una potencia de 250 MW, distribuidas por varios países de Europa y América Latina. ABSTRACT This thesis presents a comprehensive quality control procedure to be applied in photovoltaic plants, which covers from the initial phase of energy production estimation to the monitoring of the installation performance, once it is in operation. This protocol allows reducing the uncertainty associated to the photovoltaic plants behaviour and increases their long term reliability, therefore optimizing their performance. The situation of photovoltaic technology has drastically evolved in recent years, making photovoltaic plants capable of producing energy at fully competitive prices, in relation to other energy sources. This fact increases the requirements on the performance and reliability of these facilities. To meet this demand, it is necessary to adapt the quality control procedures and to develop new methods able to provide a more complete knowledge of the state of health of the plants, and able to maintain surveillance on them over time. In addition, the current meagre margins in which these installations operate require procedures capable of estimating energy production with the lower possible uncertainty during the design phase. The quality control procedure presented in this work starts from previous protocols oriented to the commissioning phase of a photovoltaic system, and complete them with procedures for the operation phase, paying particular attention to the major problems that arise in photovoltaic plants during their lifetime (hot spots, dust impact, ageing...). It also incorporates a protocol to control and analyse the installation performance directly from its monitoring data, which comprises from checking the validity of the recorded data itself to the detection and diagnosis of failures, and which allows an automated and detailed knowledge of the PV plant performance that can be oriented to facilitate the operation and maintenance of the installation, so as to ensure a high operation availability of the system. Back to the initial stage of calculating production expectations, the data recorded in the photovoltaic plants is used to improved methods for estimating the incident irradiation, which is the component that adds more uncertainty to the modelling process. The development and implementation of the presented quality control procedure has been carried out in 39 large photovoltaic plants, with a total power of 250 MW, located in different European and Latin-American countries.

A methodology to estimate uncertainty for emission projections through sensitivity analysis

Air pollution abatement policies must be based on quantitative information on current and future emissions of pollutants. As emission projections uncertainties are inevitable and traditional statistical treatments of uncertainty are highly time/resources consuming, a simplified methodology for nonstatistical uncertainty estimation based on sensitivity analysis is presented in this work. The methodology was applied to the “with measures” scenario for Spain, concretely over the 12 highest emitting sectors regarding greenhouse gas and air pollutants emissions. Examples of methodology application for two important sectors (power plants, and agriculture and livestock) are shown and explained in depth. Uncertainty bands were obtained up to 2020 by modifying the driving factors of the 12 selected sectors and the methodology was tested against a recomputed emission trend in a low economic-growth perspective and official figures for 2010, showing a very good performance. Implications: A solid understanding and quantification of uncertainties related to atmospheric emission inventories and projections provide useful information for policy negotiations. However, as many of those uncertainties are irreducible, there is an interest on how they could be managed in order to derive robust policy conclusions. Taking this into account, a method developed to use sensitivity analysis as a source of information to derive nonstatistical uncertainty bands for emission projections is presented and applied to Spain. This method simplifies uncertainty assessment and allows other countries to take advantage of their sensitivity analyses.

Aprendizaje integrado en arquitectura con modelos virtuales : implementación de metodología BIM en la docencia universitaria

Los procesos de diseño y construcción en Arquitectura han mostrado un desarrollo de optimización históricamente muy deficiente cuando se compara con las restantes actividades típicamente industriales. La aspiración constante a una industrialización efectiva, tanto en aras de alcanzar mayores cotas de calidad así como de ahorro de recursos, recibe hoy una oportunidad inmejorable desde el ámbito informático: el Building Information Modelling o BIM. Lo que en un inicio puede parecer meramente un determinado tipo de programa informático, en realidad supone un concepto de “proceso” que subvierte muchas rutinas hoy habituales en el desarrollo de proyectos y construcciones arquitectónicas. La inclusión y desarrollo de datos ligados al proyecto, desde su inicio hasta el fin de su ciclo de vida, conlleva la oportunidad de crear una realidad virtual dinámica y actualizable, que por añadidura posibilita su ensayo y optimización en todos sus aspectos: antes y durante su ejecución, así como vida útil. A ello se suma la oportunidad de transmitir eficientemente los datos completos de proyecto, sin apenas pérdidas o reelaboración, a la cadena de fabricación, lo que facilita el paso a una industrialización verdaderamente significativa en edificación. Ante una llamada mundial a la optimización de recursos y el interés indudable de aumentar beneficios económicos por medio de la reducción del factor de incertidumbre de los procesos, BIM supone un opción de mejora indudable, y así ha sido reconocido a través de la inminente implantación obligatoria por parte de los gobiernos (p. ej. Gran Bretaña en 2016 y España en 2018). La modificación de procesos y roles profesionales que conlleva la incorporación de BIM resulta muy significativa y marcará el ejercicio profesional de los futuros graduados en las disciplinas de Arquitectura, Ingeniería y Construcción (AEC por sus siglas en inglés). La universidad debe responder ágilmente a estas nuevas necesidades incorporando esta metodología en la enseñanza reglada y aportando una visión sinérgica que permita extraer los beneficios formativos subyacentes en el propio marco BIM. En este sentido BIM, al aglutinar el conjunto de datos sobre un único modelo virtual, ofrece un potencial singularmente interesante. La realidad tridimensional del modelo, desarrollada y actualizada continuamente, ofrece al estudiante una gestión radicalmente distinta de la representación gráfica, en la que las vistas parciales de secciones y plantas, tan complejas de asimilar en los inicios de la formación universitaria, resultan en una mera petición a posteriori, para ser extraída según necesidad del modelo virtual. El diseño se realiza siempre sobre el propio modelo único, independientemente de la vista de trabajo elegida en cada momento, permaneciendo los datos y sus relaciones constructivas siempre actualizados y plenamente coherentes. Esta descripción condensada de características de BIM preconfiguran gran parte de las beneficios formativos que ofrecen los procesos BIM, en especial, en referencia al desarrollo del diseño integrado y la gestión de la información (incluyendo TIC). Destacan a su vez las facilidades en comprensión visual de elementos arquitectónicos, sistemas técnicos, sus relaciones intrínsecas así como procesos constructivos. A ello se une el desarrollo experimental que la plataforma BIM ofrece a través de sus software colaborativos: la simulación del comportamiento estructural, energético, económico, entre otros muchos, del modelo virtual en base a los datos inherentes del proyecto. En la presente tesis se describe un estudio de conjunto para explicitar tanto las cualidades como posibles reservas en el uso de procesos BIM, en el marco de una disciplina concreta: la docencia de la Arquitectura. Para ello se ha realizado una revisión bibliográfica general sobre BIM y específica sobre docencia en Arquitectura, así como analizado las experiencias de distintos grupos de interés en el marco concreto de la enseñanza de la en Arquitectura en la Universidad Europea de Madrid. El análisis de beneficios o reservas respecto al uso de BIM se ha enfocado a través de la encuesta a estudiantes y la entrevista a profesionales AEC relacionados o no con BIM. Las conclusiones del estudio permiten sintetizar una implantación de metodología BIM que para mayor claridad y facilidad de comunicación y manejo, se ha volcado en un Marco de Implantación eminentemente gráfico. En él se orienta sobre las acciones docentes para el desarrollo de competencias concretas, valiéndose de la flexibilidad conceptual de los Planes de Estudio en el contexto del Espacio Europeo de Educación Superior (Declaración de Bolonia) para incorporar con naturalidad la nueva herramienta docente al servicio de los objetivos formativo legalmente establecidos. El enfoque global del Marco de Implementación propuesto facilita la planificación de acciones formativas con perspectiva de conjunto: combinar los formatos puntuales o vehiculares BIM, establecer sinergias transversales y armonizar recursos, de modo que la metodología pueda beneficiar tanto la asimilación de conocimientos y habilidades establecidas para el título, como el propio flujo de aprendizaje o learn flow BIM. Del mismo modo reserva, incluso visualmente, aquellas áreas de conocimiento en las que, al menos en la planificación actual, la inclusión de procesos BIM no se considera ventajosa respecto a otras metodologías, o incluso inadecuadas para los objetivos docentes establecidos. Y es esta última categorización la que caracteriza el conjunto de conclusiones de esta investigación, centrada en: 1. la incuestionable necesidad de formar en conceptos y procesos BIM desde etapas muy iniciales de la formación universitaria en Arquitectura, 2. los beneficios formativos adicionales que aporta BIM en el desarrollo de competencias muy diversas contempladas en el currículum académico y 3. la especificidad del rol profesional del arquitecto que exigirá una implantación cuidadosa y ponderada de BIM que respete las metodologías de desarrollo creativo tradicionalmente efectivas, y aporte valor en una reorientación simbiótica con el diseño paramétrico y fabricación digital que permita un diseño finalmente generativo. ABSTRACT The traditional architectural design and construction procedures have proven to be deficient where process optimization is concerned, particularly when compared to other common industrial activities. The ever‐growing strife to achieve effective industrialization, both in favor of reaching greater quality levels as well as sustainable management of resources, has a better chance today than ever through a mean out of the realm of information technology, the Building Information Modelling o BIM. What may initially seem to be merely another computer program, in reality turns out to be a “process” concept that subverts many of today’s routines in architectural design and construction. Including and working with project data from the very beginning to the end of its full life cycle allows for creating a dynamic and updatable virtual reality, enabling data testing and optimizing throughout: before and during execution, all the way to the end of its lifespan. In addition, there is an opportunity to transmit complete project data efficiently, with hardly any loss or redeveloping of the manufacture chain required, which facilitates attaining a truly significant industrialization within the construction industry. In the presence of a world‐wide call for optimizing resources, along with an undeniable interest in increasing economic benefits through reducing uncertainty factors in its processes, BIM undoubtedly offers a chance for improvement as acknowledged by its imminent and mandatory implementation on the part of governments (for example United Kingdom in 2016 and Spain in 2018). The changes involved in professional roles and procedures upon incorporating BIM are highly significant and will set the course for future graduates of Architecture, Engineering and Construction disciplines (AEC) within their professions. Higher Education must respond to such needs with swiftness by incorporating this methodology into their educational standards and providing a synergetic vision that focuses on the underlying educational benefits inherent in the BIM framework. In this respect, BIM, in gathering data set under one single virtual model, offers a uniquely interesting potential. The three‐dimensional reality of the model, under continuous development and updating, provides students with a radically different graphic environment, in which partial views of elevation, section or plan that tend characteristically to be difficult to assimilate at the beginning of their studies, become mere post hoc requests to be ordered when needed directly out the virtual model. The design is always carried out on the sole model itself, independently of the working view chosen at any particular moment, with all data and data relations within construction permanently updated and fully coherent. This condensed description of the features of BIM begin to shape an important part of the educational benefits posed by BIM processes, particularly in reference to integrated design development and information management (including ITC). At the same time, it highlights the ease with which visual understanding is achieved regarding architectural elements, technology systems, their intrinsic relationships, and construction processes. In addition to this, there is the experimental development the BIM platform grants through its collaborative software: simulation of structural, energetic, and economic behavior, among others, of the virtual model according to the data inherent to the project. This doctoral dissertation presents a broad study including a wide array of research methods and issues in order to specify both the virtues and possible reservations in the use of BIM processes within the framework of a specific discipline: teaching Architecture. To do so, a literature review on BIM has been carried out, specifically concerning teaching in the discipline of Architecture, as well as an analysis of the experience of different groups of interest delimited to Universidad Europea de Madrid. The analysis of the benefits and/or limitations of using BIM has been approached through student surveys and interviews with professionals from the AEC sector, associated or not, with BIM. Various diverse educational experiences are described and academic management for experimental implementation has been analyzed. The conclusions of this study offer a synthesis for a Framework of Implementation of BIM methodology, which in order to reach greater clarity, communication ease and user‐friendliness, have been posed in an eminently graphic manner. The proposed framework proffers guidance on teaching methods conducive to the development of specific skills, taking advantage of the conceptual flexibility of the European Higher Education Area guidelines based on competencies, which naturally facilitate for the incorporation of this new teaching tool to achieve the educational objectives established by law. The global approach of the Implementation Framework put forth in this study facilitates the planning of educational actions within a common perspective: combining exceptional or vehicular BIM formats, establishing cross‐disciplinary synergies, and sharing resources, so as to purport a methodology that contributes to the assimilation of knowledge and pre‐defined competencies within the degree program, and to the flow of learning itself. At the same time, it reserves, even visually, those areas of knowledge in which the use of BIM processes is not considered necessarily an advantage over other methodologies, or even inadequate for the learning outcomes established, at least where current planning is concerned. It is this last category which characterizes the research conclusions as a whole, centering on: 1. The unquestionable need for teaching BIM concepts and processes in Architecture very early on, in the initial stages of higher education; 2. The additional educational benefits that BIM offers in a varied array of competency development within the academic curriculum; and 3. The specific nature of the professional role of the Architect, which demands a careful and balanced implementation of BIM that respects the traditional teaching methodologies that have proven effective and creative, and adds value by a symbiotic reorientation merged with parametric design and digital manufacturing so to enable for a finally generative design.

Piezoelectric sensing and non-parametric statistical signal processing for health monitoring of hysteretic dampers used in seismic-resistant structures

The paper proposes a new application of non-parametric statistical processing of signals recorded from vibration tests for damage detection and evaluation on I-section steel segments. The steel segments investigated constitute the energy dissipating part of a new type of hysteretic damper that is used for passive control of buildings and civil engineering structures subjected to earthquake-type dynamic loadings. Two I-section steel segments with different levels of damage were instrumented with piezoceramic sensors and subjected to controlled white noise random vibrations. The signals recorded during the tests were processed using two non-parametric methods (the power spectral density method and the frequency response function method) that had never previously been applied to hysteretic dampers. The appropriateness of these methods for quantifying the level of damage on the I-shape steel segments is validated experimentally. Based on the results of the random vibrations, the paper proposes a new index that predicts the level of damage and the proximity of failure of the hysteretic damper

What role does climate change play in agricultural market uncertainty? An integrated assessment taking into account market-driven adjustments

Recent studies point to climate change being one of the long-term drivers of agricultural market uncertainty. To advance in the understanding of the influence of climate change on future agricultural market developments, we compare a reference scenario for 2030 with alternative simulation scenarios that differ regarding: (1) emission scenarios; (2) climate projections; and (3) the consideration of carbon fertilization effects. For each simulation scenario, the CAPRI model provides global and EU-wide impacts of climate change on agricultural markets. Results show that climate change would considerably affect agrifood markets up to 2030. Nevertheless, market-driven adaptation strategies (production intensification, trade adjustments) would soften the impact of yield shocks on supply and demand. As a result, regional changes in production would be lower than foreseen by other studies focused on supply effects.

Uncertainty in Structural Interpretation : Lessons to be learnt

Peer reviewed

Resolving taxonomic uncertainty in vulnerable elasmobranchs : are the Madeira skate (Raja maderensis) and the thornback ray (Raja clavata) distinct species?

We are grateful to all those who helped with sample collection. This includes the MEDITS survey programme (IEO Mallorca) for Mediterranean samples. Portugal mainland samples were collected under the EU Data Collection Framework (DCF, PNAB). Azores specimens from the Department of Oceanography and Fisheries (DOP) of the University of the Azores (UAc) were collected under the project DEMERSAIS “Monitorização das espécies demersais dos Açores” financed by the Azorean government, and the project DEECON “Unravelling population connectivity for sustainable fisheries in the Deep Sea” project approved by the European Science Foundation (ESF) under the EUROCORES programme (proposal No 06-EuroDEEP-FP-008 & SFRH-EuroDEEP/0002/2007). This study was funded by the UK Natural Environment Research Council (NERC) Oceans 2025 Strategic Research Programme Theme 6 (Science for Sustainable Marine Resources). REB was supported by the Fisheries Society of the British Isles (FSBI), BSP was funded by the Fundação para a Ciência e a Tecnologia, SFRH/BPD/72351/2010 and JL was supported by The Alasdair Downes Marine Conservation Fund.

Comparison of parametric and nonparametric methods to map oligogenes by linkage

A sample of 95 sib pairs affected with insulin-dependent diabetes and typed with their normal parents for 28 markers on chromosome 6 has been analyzed by several methods. When appropriate parameters are efficiently estimated, a parametric model is equivalent to the β model, which is superior to nonparametric alternatives both in single point tests (as found previously) and in multipoint tests. Theory is given for meta-analysis combined with allelic association, and problems that may be associated with errors of map location and/or marker typing are identified. Reducing by multipoint analysis the number of association tests in a dense map can give a 3-fold reduction in the critical lod, and therefore in the cost of positional cloning.

ϕ-Divergence Based Procedure for Parametric Change-Point Problems

This paper studies the change-point problem for a general parametric, univariate or multivariate family of distributions. An information theoretic procedure is developed which is based on general divergence measures for testing the hypothesis of the existence of a change. For comparing the exact sizes of the new test-statistic using the criterion proposed in Dale (J R Stat Soc B 48–59, 1986), a simulation study is performed for the special case of exponentially distributed random variables. A complete study of powers of the test-statistics and their corresponding relative local efficiencies, is also considered.

Governance and Uncertainty

Government actors create law against a backdrop of uncertainty. Limited information, unpredictable events, and lack of understanding interfere with accurately predicting a legal regime’s costs, benefits, and effects on other legal and social programs and institutions. Does the availability of no-fault divorce increase the number of terminated marriages? Will bulk-collection of telecommunications information about American citizens reveal terrorist plots? Can a sensitive species breed in the presence of oil and gas wells? The answers to these questions are far from clear, but lawmakers must act nonetheless. The problems posed by uncertainty cut across legal fields. Scholars and regulators in a variety of contexts recognize the importance of uncertainty, but no systematic, generally-applicable framework exists for determining how law should account for gaps in information. This Article suggests such a framework and develops a novel typology of strategies for accounting for uncertainty in governance. This typology includes “static law,” as well as three varieties of “dynamic law.” “Static law” is a legal rule initially intended to last in perpetuity. “Dynamic law” is intended to change, and includes: (1) durational regulation, or fixed legal rules with periodic opportunities for amendment or repeal; (2) adaptive regulation, or malleable legal rules with procedural mechanisms allowing rules to change; and (3) contingent regulation, or malleable legal rules with triggering mechanisms to substantively change to the rules. Each of these strategies, alone or in combination, may best address the uncertainty inherent in a particular lawmaking effort. This Article provides a diagnostic framework that lawmakers can use to identify optimal strategies. Ultimately, this approach to uncertainty yields immediate practical benefits by enabling lawmakers to better structure governance.

Parametric & nonparametric approaches to event studies: an application to a hotel’s market value

The main objective of this paper is twofold: on the one hand, to analyse the impact that the announcement of the opening of a new hotel has on the performance of its chain by carrying out an event study, and on the other hand, to compare the results of two different approaches to this method: a parametric specification based on the autoregressive conditional heteroskedasticity models to estimate the market model, and a nonparametric approach, which implies employing Theil’s nonparametric regression technique, which in turn, leads to the so-called complete nonparametric approach to event studies. The results that the empirical application arrives at are noteworthy as, on average, the reaction to such news releases is highly positive, both approaches reaching the same level of significance. However, a word of caution must be said when one is not only interested in detecting whether the market reacts, but also in obtaining an exhaustive calculation of the abnormal returns to further examine its determining factors.

Robust linear semi-infinite programming duality under uncertainty

In this paper, we propose a duality theory for semi-infinite linear programming problems under uncertainty in the constraint functions, the objective function, or both, within the framework of robust optimization. We present robust duality by establishing strong duality between the robust counterpart of an uncertain semi-infinite linear program and the optimistic counterpart of its uncertain Lagrangian dual. We show that robust duality holds whenever a robust moment cone is closed and convex. We then establish that the closed-convex robust moment cone condition in the case of constraint-wise uncertainty is in fact necessary and sufficient for robust duality. In other words, the robust moment cone is closed and convex if and only if robust duality holds for every linear objective function of the program. In the case of uncertain problems with affinely parameterized data uncertainty, we establish that robust duality is easily satisfied under a Slater type constraint qualification. Consequently, we derive robust forms of the Farkas lemma for systems of uncertain semi-infinite linear inequalities.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Robust Solutions of MultiObjective Linear Semi-Infinite Programs under Constraint Data Uncertainty

The multiobjective optimization model studied in this paper deals with simultaneous minimization of finitely many linear functions subject to an arbitrary number of uncertain linear constraints. We first provide a radius of robust feasibility guaranteeing the feasibility of the robust counterpart under affine data parametrization. We then establish dual characterizations of robust solutions of our model that are immunized against data uncertainty by way of characterizing corresponding solutions of robust counterpart of the model. Consequently, we present robust duality theorems relating the value of the robust model with the corresponding value of its dual problem.