Desarrollo de un sistema de optimización económica para instalaciones de régimen especial

. Este proyecto tiene por objeto el desarrollo y la implantación de un sistema de optimización económica de instalaciones de producción de Régimen Especial, en una compañía eléctrica que representa a este tipo de instalaciones para su participación en los distintos mercados de electricidad. Inicialmente, se analizarán las opciones de participación en los distintos mercados de cada tecnología, en función de la legislación a la que pudieran estar acogidas las instalaciones del Régimen Especial; según tamaño y tipología de instalaciones, características o combustibles utilizados. En segundo lugar, se estudiará la relación entre dichas instalaciones y los distintos organismos reguladores del mercado; la Comisión Nacional de la Energía, el Ministerio de Industria y Turismo, Red Eléctrica de España y el Operador del mercado eléctrico. Posteriormente, se realizará un modelo de análisis estático de la situación actual de los mercados eléctricos, su estructura y funcionamiento, obteniendo para cada tipo de instalación el escenario de optimización de base, a partir del cual se podrá desarrollar el modelo dinámico que permitirá conocer en cualquier momento cuál será la mejor opción técnico-económica para cada tipo de instalación, optimizando así el presupuesto de las instalaciones objeto del estudio. Finalmente, este modelo se implementará en los sistemas de la compañía eléctrica, como una herramienta que permitirá asegurar la optimización en tiempo real a las instalaciones a las que representa en el mercado, optimizando sus propios costes a través de la implementación de este sistema automático y logrando así maximizar los ingresos de la compañía eléctrica. ABSTRACT DEVELOPMENT OF A SYSTEM OF ECONOMIC OPTIMIZATION FOR PLANTS OF SPECIAL REGIME. This project takes as an object the development and the implantation of a system of economic optimization of facilities of production of Special Regime, in an electrical company that it represents to this type of facilities for his participation in the different markets of electricity. Initially, there will be analyzed the options of participation in the different markets of every technology, depending on the legislation to which there could be received the facilities of the Special Regime; according to size and typology of facilities, characteristics or used fuels. Secondly, the relation will be studied between the above mentioned facilities and the different regulatory organisms of the market; the National Commission of the Energy, the Department of Industry and Tourism, Electrical Network of Spain and the Operator of the electrical market. Later, there will carry out a model of static analysis of the current situation of the electrical markets, his structure and functioning, obtaining for every type of installation the scene of base optimization, from which there will be able to develop the dynamic model who will allow to know at any time which will be the best technical - economic option for every type of installation, optimizing this way the budget of the facilities I object of the study. Finally, this model will be implemented in the systems of the electrical company, as a tool that will allow to assure the real time optimization to the facilities to which it represents on the market, optimizing his own costs across the implementation of this automatic system and managing this way to maximize the income of the electrical company.

Optimization of the irrigation time and irrigation frequency by using Hydrus-2D and a capacitance FDR sensor

The evolution of water content on a sandy soil during the sprinkler irrigation campaign, in the summer of 2010, of a field of sugar beet crop located at Valladolid (Spain) is assessed by a capacitive FDR (Frequency Domain Reflectometry) EnviroScan. This field is one of the experimental sites of the Spanish research center for the sugar beet development (AIMCRA). The objective of the work focus on monitoring the soil water content evolution of consecutive irrigations during the second two weeks of July (from the 12th to the 28th). These measurements will be used to simulate water movement by means of Hydrus-2D. The water probe logged water content readings (m3/m3) at 10, 20, 40 and 60 cm depth every 30 minutes. The probe was placed between two rows in one of the typical 12 x 15 m sprinkler irrigation framework. Furthermore, a texture analysis at the soil profile was also conducted. The irrigation frequency in this farm was set by the own personal farmer 0 s criteria that aiming to minimizing electricity pumping costs, used to irrigate at night and during the weekend i.e. longer irrigation frequency than expected. However, the high evapotranspiration rates and the weekly sugar beet water consumption—up to 50mm/week—clearly determined the need for lower this frequency. Moreover, farmer used to irrigate for six or five hours whilst results from the EnviroScan probe showed the soil profile reaching saturation point after the first three hours. It must be noted that AIMCRA provides to his members with a SMS service regarding weekly sugar beet water requirement; from the use of different meteorological stations and evapotranspiration pans, farmers have an idea of the weekly irrigation needs. Nevertheless, it is the farmer 0 s decision to decide how to irrigate. Thus, in order to minimize water stress and pumping costs, a suitable irrigation time and irrigation frequency was modeled with Hydrus-2D. Results for the period above mentioned showed values of water content ranging from 35 and 30 (m3/m3) for the first 10 and 20cm profile depth (two hours after irrigation) to the minimum 14 and 13 (m3/m3) ( two hours before irrigation). For the 40 and 60 cm profile depth, water content moves steadily across the dates: The greater the root activity the greater the water content variation. According to the results in the EnviroScan probe and the modeling in Hydrus-2D, shorter frequencies and irrigation times are suggested.

Server power modeling for run-time energy optimization of cloud computing facilities

As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simul- taneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.

Space-time Reconstruction of Oceanic Sea States via Variational Stereo Methods

We present a remote sensing observational method for the measurement of the spatio-temporal dynamics of ocean waves. Variational techniques are used to recover a coherent space-time reconstruction of oceanic sea states given stereo video imagery. The stereoscopic reconstruction problem is expressed in a variational optimization framework. There, we design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal regularizers. A nested iterative scheme is devised to numerically solve, via 3-D multigrid methods, the system of partial differential equations resulting from the optimality condition of the energy functional. The output of our method is the coherent, simultaneous estimation of the wave surface height and radiance at multiple snapshots. We demonstrate our algorithm on real data collected off-shore. Statistical and spectral analysis are performed. Comparison with respect to an existing sequential method is analyzed.

Design and Optimization of Power Delivery and Distribution Systems Using Evolutionary Computation Techniques

Nowadays computing platforms consist of a very large number of components that require to be supplied with diferent voltage levels and power requirements. Even a very small platform, like a handheld computer, may contain more than twenty diferent loads and voltage regulators. The power delivery designers of these systems are required to provide, in a very short time, the right power architecture that optimizes the performance, meets electrical specifications plus cost and size targets. The appropriate selection of the architecture and converters directly defines the performance of a given solution. Therefore, the designer needs to be able to evaluate a significant number of options in order to know with good certainty whether the selected solutions meet the size, energy eficiency and cost targets. The design dificulties of selecting the right solution arise due to the wide range of power conversion products provided by diferent manufacturers. These products range from discrete components (to build converters) to complete power conversion modules that employ diferent manufacturing technologies. Consequently, in most cases it is not possible to analyze all the alternatives (combinations of power architectures and converters) that can be built. The designer has to select a limited number of converters in order to simplify the analysis. In this thesis, in order to overcome the mentioned dificulties, a new design methodology for power supply systems is proposed. This methodology integrates evolutionary computation techniques in order to make possible analyzing a large number of possibilities. This exhaustive analysis helps the designer to quickly define a set of feasible solutions and select the best trade-off in performance according to each application. The proposed approach consists of two key steps, one for the automatic generation of architectures and other for the optimized selection of components. In this thesis are detailed the implementation of these two steps. The usefulness of the methodology is corroborated by contrasting the results using real problems and experiments designed to test the limits of the algorithms.

Integrated program debugging, verification, and optimization using abstract interpretation (and the Ciao system preprocessor)

The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, nonfailure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas.

Optimization of a label-free biosensor vertically characterized based on a periodic lattice of high aspect ratio SU-8 nano-pillars with a simplified 2D theoretical model

We have recently demonstrated a biosensor based on a lattice of SU8 pillars on a 1 μm SiO2/Si wafer by measuring vertically reflectivity as a function of wavelength. The biodetection has been proven with the combination of Bovine Serum Albumin (BSA) protein and its antibody (antiBSA). A BSA layer is attached to the pillars; the biorecognition of antiBSA involves a shift in the reflectivity curve, related with the concentration of antiBSA. A detection limit in the order of 2 ng/ml is achieved for a rhombic lattice of pillars with a lattice parameter (a) of 800 nm, a height (h) of 420 nm and a diameter(d) of 200 nm. These results correlate with calculations using 3D-finite difference time domain method. A 2D simplified model is proposed, consisting of a multilayer model where the pillars are turned into a 420 nm layer with an effective refractive index obtained by using Beam Propagation Method (BPM) algorithm. Results provided by this model are in good correlation with experimental data, reaching a reduction in time from one day to 15 minutes, giving a fast but accurate tool to optimize the design and maximizing sensitivity, and allows analyzing the influence of different variables (diameter, height and lattice parameter). Sensitivity is obtained for a variety of configurations, reaching a limit of detection under 1 ng/ml. Optimum design is not only chosen because of its sensitivity but also its feasibility, both from fabrication (limited by aspect ratio and proximity of the pillars) and fluidic point of view. (© 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

PV self-consumption optimization with storage and Active DSM for the residential sector

With the rising prices of the retail electricity and the decreasing cost of the PV technology, grid parity with commercial electricity will soon become a reality in Europe. This fact, together with less attractive PV feed-in-tariffs in the near future and incentives to promote self-consumption suggest, that new operation modes for the PV Distributed Generation should be explored; differently from the traditional approach which is only based on maximizing the exported electricity to the grid. The smart metering is experiencing a growth in Europe and the United States but the possibilities of its use are still uncertain, in our system we propose their use to manage the storage and to allow the user to know their electrical power and energy balances. The ADSM has many benefits studied previously but also it has important challenges, in this paper we can observe and ADSM implementation example where we propose a solution to these challenges. In this paper we study the effects of the Active Demand-Side Management (ADSM) and storage systems in the amount of consumed local electrical energy. It has been developed on a prototype of a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead–acid batteries, controllable appliances and smart metering. We carried out simulations for long-time experiments (yearly studies) and real measures for short and mid-time experiments (daily and weekly studies). Results show the relationship between the electricity flows and the storage capacity, which is not linear and becomes an important design criterion.

Score optimization and template updating in a biometric technique for authentication in mobiles based on gestures

This article focuses on the evaluation of a biometric technique based on the performance of an identifying gesture by holding a telephone with an embedded accelerometer in his/her hand. The acceleration signals obtained when users perform gestures are analyzed following a mathematical method based on global sequence alignment. In this article, eight different scores are proposed and evaluated in order to quantify the differences between gestures, obtaining an optimal EER result of 3.42% when analyzing a random set of 40 users of a database made up of 80 users with real attempts of falsification. Moreover, a temporal study of the technique is presented leeding to the need to update the template to adapt the manner in which users modify how they perform their identifying gesture over time. Six updating schemes have been assessed within a database of 22 users repeating their identifying gesture in 20 sessions over 4 months, concluding that the more often the template is updated the better and more stable performance the technique presents.

Analysis and optimization of propagation losses in LiNbO3 optical waveguides produced by swift heavy-ion irradiation

The propagation losses (PL) of lithium niobate optical planar waveguides fabricated by swift heavy-ion irradiation (SHI), an alternative to conventional ion implantation, have been investigated and optimized. For waveguide fabrication, congruently melting LiNbO3 substrates were irradiated with F ions at 20 MeV or 30 MeV and fluences in the range 1013–1014 cm−2. The influence of the temperature and time of post-irradiation annealing treatments has been systematically studied. Optimum propagation losses lower than 0.5 dB/cm have been obtained for both TE and TM modes, after a two-stage annealing treatment at 350 and 375∘C. Possible loss mechanisms are discussed.

Profiling for run-time checking of computational properties and performance debugging in logic programs

Although several profiling techniques for identifying performance bottlenecks in logic programs have been developed, they are generally not automatic and in most cases they do not provide enough information for identifying the root causes of such bottlenecks. This complicates using their results for guiding performance improvement. We present a profiling method and tool that provides such explanations. Our profiler associates cost centers to certain program elements and can measure different types of resource-related properties that affect performance, preserving the precedence of cost centers in the cali graph. It includes an automatic method for detecting procedures that are performance bottlenecks. The profiling tool has been integrated in a previously developed run-time checking framework to allow verification of certain properties when they cannot be verified statically. The approach allows checking global computational properties which require complex instrumentation tracking information about previous execution states, such as, e.g., that the execution time accumulated by a given procedure is not greater than a given bound. We have built a prototype implementation, integrated it in the Ciao/CiaoPP system and successfully applied it to performance improvement, automatic optimization (e.g., resource-aware specialization of programs), run-time checking, and debugging of global computational properties (e.g., resource usage) in Prolog programs.

Optimization of urban mobility measures to achieve win-win strategies

European cities are essential in the development of Europe as they constitute the living environment of more than 60% of the population in the European Union and are drivers of the European economy – just under 85% of the EU’s gross domestic product is produced in urban areas (EC, 2007a). The car has been one of the main factors of development during the 20th century, but it is at the same time the origin of the key problems cities have to face: traffic increase. This has resulted in chronic congestion with many adverse consequences such as air pollution and noise. This loss of environmental quality is one of the reasons for urban sprawl in European cities during recent decades. But this urban sprawl at the same time worsens the environmental conditions. We must return to the dense city, but clean and competitive, and this implies reducing car use yet provides quality transport alternatives sufficient to recover and maintain the competitiveness of cities (EC, 2007a). Consequently, European cities need to establish an urban transport strategy which helps reduce their environmental problems –mainly emissions and noise – but without decreasing their trip attraction. This aspect is very important because a loss of trip attraction would result in an increase of people moving to more disperse areas, contributing towards worsening the current situation. This thesis is an attempt to contribute solutions to this problem in two ways: 1) The first is to analyze the complementarity and possible synergies of several urban transport measures aimed at improving a modal split to a more sustainable means of transport. This analysis will focus on the three aspects already mentioned: emissions, noise and attractiveness or competitiveness. 2) Once possible synergies and complementarities have been analyzed, the second objective is to propose the best combination of these measures, in terms of level of implementation, to achieve the maximum benefit with respect to the three aspects previously established: emissions, noise and attractiveness or competitiveness. Therefore, within the wide range of measures enhancing sustainable urban transport, three of them have been be selected in this thesis to establish a methodology for achieving these objectives. The analysis will be based on the region of Madrid, which is also the case study selected for this research. Las ciudades europeas son piezas fundamentales para el desarrollo europeo, ya que son el lugar de residencia de más del 60% de la población de la unión europea así como los motores de su economía – casi el 85% del PIB europeo se produce en áreas urbanas (EC, 2007a). El coche ha sido uno de los principales motores de desarrollo de las ciudades durante el siglo XX, pero se ha terminado por convertir a su vez en uno de los principales problemas con los que tiene que lidiar las ciudades: el aumento del tráfico. Esto ha derivado en unos niveles crónicos de congestión, con multitud de efectos adversos, entre los que cabe destacar la contaminación del aire y el ruido. Esta pérdida de calidad ambiental es una de las razones que ha propiciado la dispersión urbana que han experimentado las ciudades europeas en las últimas décadas. Pero esta dispersión urbana a su vez contribuye a empeorar las condiciones ambientales de las ciudades. Debemos retornar a la ciudad densa, pero limpia y competitiva, y esto implica reducir el uso del coche, pero proporcionando alternativas de transporte que permitan recuperar y mantener la competitividad de las ciudades (EC, 2007a). Por lo tanto, las ciudades europeas necesitan encontrar una estrategia de transporte urbano que ayude a reducir sus problemas medio ambientales – principalmente ruido y emisiones – pero sin hacerlas perder atractividad o competitividad. Este aspecto tiene gran importancia porque una pérdida de la misma se traduciría en un aumento de dispersión de la población hacia áreas periféricas, contribuyendo a empeorar la situación actual. Esta tesis contribuye a solucionar este problema de dos maneras: 1) La primera, analizando la complementariedad y posibles sinergias de diferentes medidas de transporte urbano orientadas a promover un reparto modal hacia modos más sostenibles. Este análisis se centrará en los tres aspectos anteriormente citados: emisiones, ruido y atractividad o competitividad. 2) Una vez las posibles sinergias y complementariedades se han analizado, el segundo objetivo es proponer la mejor combinación de estas medidas – en términos de grado de aplicación - para lograr el máximo beneficio en lo que respecta a los tres objetivos previamente establecidos. Para ello, en esta tesis se han seleccionado una serie de medidas que permitan establecer una metodología para alcanzar estos objetivos previamente definidos. El análisis se centra en la ciudad de Madrid y su área metropolitana, la cual se ha escogido como caso de estudio para realizar esta investigación.

Program analysis, debugging and optimization using the ciao system preprocessor

We present a tutorial overview of Ciaopp, the Ciao system preprocessor. Ciao is a public-domain, next-generation logic programming system, which subsumes ISO-Prolog and is specifically designed to a) be highly extensible via librarles and b) support modular program analysis, debugging, and optimization. The latter tasks are performed in an integrated fashion by Ciaopp. Ciaopp uses modular, incremental abstract interpretation to infer properties of program predicates and literals, including types, variable instantiation properties (including modes), non-failure, determinacy, bounds on computational cost, bounds on sizes of terms in the program, etc. Using such analysis information, Ciaopp can find errors at compile-time in programs and/or perform partial verification. Ciaopp checks how programs cali system librarles and also any assertions present in the program or in other modules used by the program. These assertions are also used to genérate documentation automatically. Ciaopp also uses analysis information to perform program transformations and optimizations such as múltiple abstract specialization, parallelization (including granularity control), and optimization of run-time tests for properties which cannot be checked completely at compile-time. We illustrate "hands-on" the use of Ciaopp in all these tasks. By design, Ciaopp is a generic tool, which can be easily tailored to perform these and other tasks for different LP and CLP dialects.

An approach to profiling for run-time checking of computational properties and performance debugging in logic programs.

Although several profiling techniques for identifying performance bottlenecks in logic programs have been developed, they are generally not automatic and in most cases they do not provide enough information for identifying the root causes of such bottlenecks. This complicates using their results for guiding performance improvement. We present a profiling method and tool that provides such explanations. Our profiler associates cost centers to certain program elements and can measure different types of resource-related properties that affect performance, preserving the precedence of cost centers in the call graph. It includes an automatic method for detecting procedures that are performance bottlenecks. The profiling tool has been integrated in a previously developed run-time checking framework to allow verification of certain properties when they cannot be verified statically. The approach allows checking global computational properties which require complex instrumentation tracking information about previous execution states, such as, e.g., that the execution time accumulated by a given procedure is not greater than a given bound. We have built a prototype implementation, integrated it in the Ciao/CiaoPP system and successfully applied it to performance improvement, automatic optimization (e.g., resource-aware specialization of programs), run-time checking, and debugging of global computational properties (e.g., resource usage) in Prolog programs.

A tutorial on program development and optimization using the Ciao preprocessor

We present in a tutorial fashion CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, non-failure, and bounds on resource consumption (time or space cost).