Failure mode prediction and energy forecasting of PV plants to assist dynamic maintenance tasks by ANN based models

In the field of renewable energy, reliability analysis techniques combining the operating time of the system with the observation of operational and environmental conditions, are gaining importance over time. In this paper, reliability models are adapted to incorporate monitoring data on operating assets, as well as information on their environmental conditions, in their calculations. To that end, a logical decision tool based on two artificial neural networks models is presented. This tool allows updating assets reliability analysis according to changes in operational and/or environmental conditions. The proposed tool could easily be automated within a supervisory control and data acquisition system, where reference values and corresponding warnings and alarms could be now dynamically generated using the tool. Thanks to this capability, on-line diagnosis and/or potential asset degradation prediction can be certainly improved. Reliability models in the tool presented are developed according to the available amount of failure data and are used for early detection of degradation in energy production due to power inverter and solar trackers functional failures. Another capability of the tool presented in the paper is to assess the economic risk associated with the system under existing conditions and for a certain period of time. This information can then also be used to trigger preventive maintenance activities

Optimization of the long-term planning of supply chains with decaying performance

This master's thesis addresses the optimization of supply and distribution chains considering the effect that equipment aging may cause over the performance of facilities involved in the process. The decaying performance of the facilities is modeled as an exponential equation and can be either physical or economic, thus giving rise to a novel mixed integer non-linear programming (MINLP) formulation. The optimization model has been developed based on a typical chemical supply chain. Thus, the best long-term investment plan has to be determined given production nodes, their production capacity and expected evolution; aggregated consumption nodes (urban or industrial districts) and their lumped demand (and expected evolution); actual and potential distribution nodes; distances between the nodes of the network; and a time horizon. The model includes the balances in each node, a general decaying performance function, and a cost function, as well as constraints to be satisfied. Hence, the investment plan (decision variables) consists not only on the start-up and shutdown of alternative distribution facilities, but also on the sizing of the lines satisfying the flows. The model has been implemented using GAMS optimization software. Results considering a variety of scenarios have been discussed. In addition, different approaches to the starting point for the model have been compared, showing the importance of initializing the optimization algorithm. The capabilities of the proposed approach have been tested through its application to two case studies: a natural gas network with physical decaying performance and an electricity distribution network with economic decaying performance. Each case study is solved with a different procedure to obtain results. Results demonstrate that overlooking the effect of equipment aging can lead to infeasible (for physical decaying performance) or unrealistic (for economic decaying performance) solutions in practice and show how the proposed model allows overcoming such limitations thus becoming a practical tool to support the decision-making process in the distribution secto

High-Performance Integrated Window and Façade Solutions for California

The researchers developed a new generation of high-performance façade systems and supporting design and management tools to support industry in meeting California’s greenhouse gas reduction targets, reduce energy consumption, and enable an adaptable response to minimize real-time demands on the electricity grid. The project resulted in five outcomes: (1) The research team developed an R-5, 1-inch thick, triplepane, insulating glass unit with a novel low-conductance aluminum frame. This technology can help significantly reduce residential cooling and heating loads, particularly during the evening. (2) The team developed a prototype of a windowintegrated local ventilation and energy recovery device that provides clean, dry fresh air through the façade with minimal energy requirements. (3) A daylight-redirecting louver system was prototyped to redirect sunlight 15–40 feet from the window. Simulations estimated that lighting energy use could be reduced by 35–54 percent without glare. (4) A control system incorporating physics-based equations and a mathematical solver was prototyped and field tested to demonstrate feasibility. Simulations estimated that total electricity costs could be reduced by 9-28 percent on sunny summer days through adaptive control of operable shading and daylighting components and the thermostat compared to state-of-the-art automatic façade controls in commercial building perimeter zones. (5) Supporting models and tools needed by industry for technology R&D and market transformation activities were validated. Attaining California’s clean energy goals require making a fundamental shift from today’s ad-hoc assemblages of static components to turnkey, intelligent, responsive, integrated building façade systems. These systems offered significant reductions in energy use, peak demand, and operating cost in California

Numerical propulsion system simulation: An interdisciplinary approach

The tremendous progress being made in computational engineering and the rapid growth in computing power that is resulting from parallel processing now make it feasible to consider the use of computer simulations to gain insights into the complex interactions in aerospace propulsion systems and to evaluate new concepts early in the design process before a commitment to hardware is made. Described here is a NASA initiative to develop a Numerical Propulsion System Simulation (NPSS) capability

Ultrasonic transducer design: Feasibility as parametric echosounder in shallow water

In recent decades, acoustic techniques have become the most appropriate tools for biomass estimation in the fishing industry. This is because acoustic waves are the only waves that can be used for remote sensing in the aquatic environment due to their low attenuation compared to electromagnetic waves, which are usually used in long-distance communications in the atmosphere. Ultrasonic echo sounders allow sampling of water columns and cover large areas of ocean by means of sampling campaigns conducted by oceanographic vessels, providing information on fish stocks of commercial interest. Furthermore, as a result of the overexploitation of fishery resources and to cover increasing demand, fish production has been developed as an alternative to capture. Although several species are bred in captivity, in Spain we can highlight three in particular, due to the high economic impact and degree of implantation: Gilt-head bream (Sparus aurata), sea bass (Dicentrarchus labrax) and Bluefin tuna (Thunnus thynnus). There is demand in the aquaculture industry for techniques developed in the field of fishery acoustics to control and estimate biomass. However, various problems related to the geometry of the application and high fish densities in intensive aquaculture have made these techniques difficult to apply directly. The study of biomass and species classification has progressed in parallel with the development of sonar and echo sounder systems used for this type of applications, and particularly with the evolution of ultrasonic transducers. Operation frequency, transmission power, bandwidth and directivity are key factors in the acoustic methods applied to fishing. In addition, other aspects of research are becoming more relevant in this sector, such as the study of nonlinear parametric sound generation. This generation or parametric effect, produced in the medium, has focused so far especially on bathymetry or classification of the oceanic subsoil, by offering much lower operation frequencies with the same directivity as the beam generated at high frequency. Nowadays, their feasibility is studied for application to fisheries or aquaculture, due to the possibility of working at several frequencies with the same transducer, given the same radiation characteristics, which is not possible in the linear regime. This thesis presents the design of an ultrasound transducer for biomass estimation with specific characteristics and demonstrates its capacity to work in a non-linear regime with optimum apertures for use in shallow water or in aquaculture cages. Chapter 2 presents general information on ultrasound waves, the medium through which they are propagated and an introduction to non-linear generation. General concepts in ultrasound generation and design are presented in Chapter 3. Chapter 4 shows the numerical models used to reinforce the experimental results presented during this thesis. Chapter 5 covers the design of the transducer, encompassing all the processes, from characterization of the materials, to assembly, operation and simulation of designed prototypes. To conclude, Chapter 6 presents the behavior of prototypes in a nonlinear regime and their feasibility for estimating biomass of different species in shallow water.Las técnicas acústicas se han convertido en las últimas décadas en las herramientas más apropiadas para la estimación de biomasa en el sector pesquero. Esto es debido a que las ondas acústicas son las únicas que pueden utilizarse para teledetección en el medio acuático, por su baja atenuación, comparadas con las ondas electromagnéticas, que son las usadas habitualmente en comunicaciones a larga distancia en la atmósfera. Las ecosondas ultrasónicas permiten muestrear la columna de agua y cubrir grandes extensiones de océano mediante campañas de muestreo realizadas por buques oceanográficos, ofreciendo información de las poblaciones de peces de interés comercial. Por otro lado, como consecuencia de la sobreexplotación de los recursos pesqueros y para cubrir la demanda creciente para su consumo, se ha desarrollado como alternativa a la captura, la producción piscícola. Aunque hay diversas especies que se crían en cautividad, en España podemos destacar tres en particular, por el alto impacto económico y grado de implantación: Dorada (Sparus aurata), lubina (Dicentrarchus labrax) y atún rojo (Thunnus thynnus). La aplicación de las técnicas desarrolladas en el campo de la acústica de pesquerías para el control y estimación de la biomasa en jaulas flotantes, es una demanda del sector acuicultor. Sin embargo, diferentes problemas relacionados con la geometría de la aplicación y las altas densidades de peces con las que se trabaja en acuicultura intensiva, han dificultado la aplicación directa de las mismas. Los avances en el estudio de la biomasa o en la clasificación de especies han ido en paralelo con el desarrollo de los sistemas sonar y ecosondas usados para este tipo de aplicaciones, y particularmente con la evolución de los transductores ultrasónicos empleados. La frecuencia de trabajo, la potencia de emisión, el ancho de banda, así como la directividad son factores clave en los métodos acústicos aplicados a la pesca. Además, otras vertientes de investigación están adquiriendo mayor relevancia en este sector, como por ejemplo, el estudio de la generación no lineal paramétrica de sonido. Esta generación o efecto paramétrico, producido en el medio, se ha enfocado hasta ahora especialmente en batimetrías o en la clasificación del subsuelo oceánico, por ofrecer frecuencias de trabajo mucho más bajas con la misma directividad que el haz generado a alta frecuencia. Actualmente, se estudia su viabilidad para ser aplicado a pesquerías o a acuicultura, debido a la posibilidad de trabajar a varias frecuencias con un mismo transductor, presentado éstas las mismas características de radiación, lo que no es posible en el régimen lineal. Esta tesis presenta el diseño de un transductor de ultrasonidos para la estimación de biomasa con unas características específicas. Demostrando, además, la capacidad de éste para poder trabajar en régimen no lineal con aperturas adecuadas para su uso en aguas poco profundas o en jaulas de acuicultura. En el capítulo 2 se presenta información general sobre las ondas de ultrasonidos y el medio por donde se propagan, así como una introducción a la generación no-lineal. Conceptos generales sobre la generación de los ultrasonidos y el diseño se presentan en el capítulo 3. En el capítulo 4, se muestran los modelos numéricos utilizados para afianzar los resultados experimentales presentados durante la tesis. El capítulo 5 recoge el diseño del transductor, que englobará todos los procesos, desde la caracterización de los materiales, hasta el montaje, puesta en marcha y simulación de los prototipos creados. Para finalizar el capítulo 6 presenta el comportamiento de los prototipos en régimen no lineal y su viabilidad para estimar biomasa de diferentes especies en aguas poco profundasLes tècniques acústiques s'han convertit en les últimes dècades en les ferramentes més apropiades per a l'estimació de biomassa en el sector pesquer. Això és degut a que les ones acústiques són les úniques que poden utilitzar-se per teledetecció en el medi aquàtic, per la seva baixa atenuació, comparades amb les ones electromagnètiques, que són les usades habitualment en comunicacions a llarga distància en l'atmosfera. Les ecosondes ultrasòniques permeten mostrejar la columna d'aigua i cobrir grans extensions d'oceà mitjançant campanyes de mostreig realitzades per vaixells oceanogràfics, oferint informació de les poblacions de peixos d'interès comercial. Per altre costat, com a conseqüència de la sobreexplotació dels recursos pesquers i per cobrir la demanda creixent per al seu consum, s'ha desenvolupat com a alternativa a la captura, la producció piscícola. Encara que hi ha diverses espècies que es crien en captivitat, a Espanya podem destacar tres en particular, per l'alt impacte econòmic i grau d'implantació: Daurada (Sparus aurata), llobarro (Dicentrarchus labrax) i tonyina vermella (Thunnus thynnus). L'aplicació de les tècniques desenvolupades en el camp de l'acústica de pesqueres pel control i estimació de la biomassa en gàbies flotants, és una demanda del sector aqüicultor. No obstant això, diferents problemes relacionats amb la geometria de l'aplicació i les altes densitats de peixos amb les que es treballa en aqüicultura intensiva, han dificultat l'aplicació directa de les mateixes. Els avanços en l'estudi de la biomassa o en la classificació d'espècies han anat en paral·lel amb el desenvolupament dels sistemes sonar i ecosondes usats per a aquest tipus d'aplicacions, i particularment amb l'evolució dels transductors ultrasònics empleats. La freqüència de treball, la potència d'emissió, l'ample de banda, així com la directivitat són factors clau en els mètodes acústics aplicats a la pesca. A més, altres vessants d'investigació estan adquirint major rellevància en aquest sector, com per exemple, l'estudi de la generació no lineal paramètrica de so. Aquesta generació o efecte paramètric, produït en el medi, s'ha enfocat fins ara especialment en batimetries o en la classificació del subsòl oceànic, per oferir freqüències de treball molt més baixes amb la mateixa directivitat que el feix generat a alta freqüència. Actualment, s'estudia la seva viabilitat per a ser aplicat a pesqueries o a aqüicultura, a causa de la possibilitat de treballar a diverses freqüències amb un mateix transductor, presentat aquestes les mateixes característiques de radiació, el que no és possible en el règim lineal. Esta tesi presenta el disseny d'un transductor d'ultrasons per a l'estimació de biomassa amb unes característiques específiques. Demostrant, a més, la capacitat d'aquest per poder treballar en règim no lineal amb obertures adequades per al seu ús en aigües poc profundes o en gàbies d'aqüicultura. En el capítol 2 es presenta informació general sobre els ultrasons i el mitjà pel qual es propaguen, així com una introducció a la generació no-lineal. Conceptes generals sobre la generació dels ultrasons i el disseny es presenten en el capítol 3. En el capítol 4, es mostren també els models numèrics utilitzats per a refermar els resultats experimentals presentats durant la tesi. El capítol 5 recull el disseny del transductor, que englobarà tots els processos, des de la caracterització dels materials fins al muntatge, posada en marxa i simulació dels prototips creats. Finalment, el capítol 6 presenta el comportament dels prototips en règim no lineal i la seua viabilitat per a estimar biomassa de diferents espècies en aigües poc profundes.Ordoñez Cebrián, P. (2017). Ultrasonic transducer design: Feasibility as parametric echosounder in shallow water [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86192TESI

Evaluating three proposals for testing independence in non linear spatial processes

[ENG]This paper evaluates the behaviour of different families of tests when checking for spatial independence in the presence of nonlinearities. To reach this goal, we select three representative proposals. The usual parametric tests of I-Moran, the nonparametric proposal of Brett and Pinkse (1997), and the semiparametric Scan test. In order to study how they perform, we simulate different nonlinear spatial structures by Monte Carlo methods, hence conducting empirical tests on the matter. Main results show failures of traditional tests in this framework, and the need to build on new proposals in the presence of nonlinearities. An empirical application to an economic-theory-of-production scenario illustrates the performance of the three tests.[SPA]Este artículo evalúa el comportamiento de tres estadísticos utilizados para contrastar la hipótesis de independencia de procesos espaciales cuando subyace una estructura no lineal en los datos: el clásico test paramétrico de Moran, la propuesta no paramétrica de Brett y Pinkse y el test semiparamétrico Scan. Para comparar el comportamiento de estos contrastes se realiza un extenso ejercicio de Montecarlo en el que se proponen diversas estructuras de dependencia espacial no lineal. Los resultados obtenidos señalan la necesidad de aplicar los nuevos contrastes en entornos no lineales, dado que los tradicionales suelen fallar en su detección. Una aplicación a la función de producción empresarial permite ilustrar esta cuestión

Two new feature selection algorithms with rough sets theory

Rough Sets Theory has opened new trends for the development of the Incomplete Information Theory. Inside this one, the notion of reduct is a very significant one, but to obtain a reduct in a decision system is an expensive computing process although very important in data analysis and knowledge discovery. Because of this, it has been necessary the development of different variants to calculate reducts. The present work look into the utility that offers Rough Sets Model and Information Theory in feature selection and a new method is presented with the purpose of calculate a good reduct. This new method consists of a greedy algorithm that uses heuristics to work out a good reduct in acceptable times. In this paper we propose other method to find good reducts, this method combines elements of Genetic Algorithm with Estimation of Distribution Algorithms. The new methods are compared with others which are implemented inside Pattern Recognition and Ant Colony Optimization Algorithms and the results of the statistical tests are shown.IFIP International Conference on Artificial Intelligence in Theory and Practice - Knowledge Acquisition and Data MiningRed de Universidades con Carreras en Informática (RedUNCI

A Process to Implement an Artificial Neural Network and Association Rules Techniques to Improve Asset Performance and Energy Efficiency

In this paper, we address the problem of asset performance monitoring, with the intention of both detecting any potential reliability problem and predicting any loss of energy consumption e ciency. This is an important concern for many industries and utilities with very intensive capitalization in very long-lasting assets. To overcome this problem, in this paper we propose an approach to combine an Artificial Neural Network (ANN) with Data Mining (DM) tools, specifically with Association Rule (AR) Mining. The combination of these two techniques can now be done using software which can handle large volumes of data (big data), but the process still needs to ensure that the required amount of data will be available during the assets’ life cycle and that its quality is acceptable. The combination of these two techniques in the proposed sequence di ers from previous works found in the literature, giving researchers new options to face the problem. Practical implementation of the proposed approach may lead to novel predictive maintenance models (emerging predictive analytics) that may detect with unprecedented precision any asset’s lack of performance and help manage assets’ O&M accordingly. The approach is illustrated using specific examples where asset performance monitoring is rather complex under normal operational conditions.Ministerio de Economía y Competitividad DPI2015-70842-