Towards a dynamic model for the Urban Heat Island of Madrid

Present research is framed within the project MODIFICA (MODelo predictivo - edIFIcios - Isla de Calor urbanA) aimed at developing a predictive model for dwelling energy performance under the urban heat island effect in order to implement it in the evaluation of real energy demand and consumption of dwellings as well as in the selection of energy retrofitting strategies. It is funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. Despite great advances on building energy performance have been achieved during the last years, available climate data is derived from weather stations placed in the outskirts of the city. Hence, urban heat island effect is not considered in energy simulations, which implies an important lack of accuracy. Since 1980's several international studies have been conducted on the urban heat island (UHI) phenomena, which modifies the atmospheric conditions of the urban centres due to urban agglomeration [1][2][3][4]. In the particular case of Madrid, multiple maps haven been generated using different methodologies during the last two decades [5][6][7]. These maps allow us to study the UHI phenomena from a wide perspective, offering however an static representation of it. Consequently a dynamic model for Madrid UHI is proposed, in order to evaluate it in a continuous way, and to be able to integrate it in building energy simulations.

Hybrid wind-diesel power plant valuation and optimization using real option theory and dynamic programming

El sistema de energía eólica-diesel híbrido tiene un gran potencial en la prestación de suministro de energía a comunidades remotas. En comparación con los sistemas tradicionales de diesel, las plantas de energía híbridas ofrecen grandes ventajas tales como el suministro de capacidad de energía extra para "microgrids", reducción de los contaminantes y emisiones de gases de efecto invernadero, y la cobertura del riesgo de aumento inesperado del precio del combustible. El principal objetivo de la presente tesis es proporcionar nuevos conocimientos para la evaluación y optimización de los sistemas de energía híbrido eólico-diesel considerando las incertidumbres. Dado que la energía eólica es una variable estocástica, ésta no puede ser controlada ni predecirse con exactitud. La naturaleza incierta del viento como fuente de energía produce serios problemas tanto para la operación como para la evaluación del valor del sistema de energía eólica-diesel híbrido. Por un lado, la regulación de la potencia inyectada desde las turbinas de viento es una difícil tarea cuando opera el sistema híbrido. Por otro lado, el bene.cio económico de un sistema eólico-diesel híbrido se logra directamente a través de la energía entregada a la red de alimentación de la energía eólica. Consecuentemente, la incertidumbre de los recursos eólicos incrementa la dificultad de estimar los beneficios globales en la etapa de planificación. La principal preocupación del modelo tradicional determinista es no tener en cuenta la incertidumbre futura a la hora de tomar la decisión de operación. Con lo cual, no se prevé las acciones operativas flexibles en respuesta a los escenarios futuros. El análisis del rendimiento y simulación por ordenador en el Proyecto Eólico San Cristóbal demuestra que la incertidumbre sobre la energía eólica, las estrategias de control, almacenamiento de energía, y la curva de potencia de aerogeneradores tienen un impacto significativo sobre el rendimiento del sistema. En la presente tesis, se analiza la relación entre la teoría de valoración de opciones y el proceso de toma de decisiones. La opción real se desarrolla con un modelo y se presenta a través de ejemplos prácticos para evaluar el valor de los sistemas de energía eólica-diesel híbridos. Los resultados muestran que las opciones operacionales pueden aportar un valor adicional para el sistema de energía híbrida, cuando esta flexibilidad operativa se utiliza correctamente. Este marco se puede aplicar en la optimización de la operación a corto plazo teniendo en cuenta la naturaleza dependiente de la trayectoria de la política óptima de despacho, dadas las plausibles futuras realizaciones de la producción de energía eólica. En comparación con los métodos de valoración y optimización existentes, el resultado del caso de estudio numérico muestra que la política de operación resultante del modelo de optimización propuesto presenta una notable actuación en la reducción del con- sumo total de combustible del sistema eólico-diesel. Con el .n de tomar decisiones óptimas, los operadores de plantas de energía y los gestores de éstas no deben centrarse sólo en el resultado directo de cada acción operativa, tampoco deberían tomar decisiones deterministas. La forma correcta es gestionar dinámicamente el sistema de energía teniendo en cuenta el valor futuro condicionado en cada opción frente a la incertidumbre. ABSTRACT Hybrid wind-diesel power systems have a great potential in providing energy supply to remote communities. Compared with the traditional diesel systems, hybrid power plants are providing many advantages such as providing extra energy capacity to the micro-grid, reducing pollution and greenhouse-gas emissions, and hedging the risk of unexpected fuel price increases. This dissertation aims at providing novel insights for assessing and optimizing hybrid wind-diesel power systems considering the related uncertainties. Since wind power can neither be controlled nor accurately predicted, the energy harvested from a wind turbine may be considered a stochastic variable. This uncertain nature of wind energy source results in serious problems for both the operation and value assessment of the hybrid wind-diesel power system. On the one hand, regulating the uncertain power injected from wind turbines is a difficult task when operating the hybrid system. On the other hand, the economic profit of a hybrid wind-diesel system is achieved directly through the energy delivered to the power grid from the wind energy. Therefore, the uncertainty of wind resources has increased the difficulty in estimating the total benefits in the planning stage. The main concern of the traditional deterministic model is that it does not consider the future uncertainty when making the dispatch decision. Thus, it does not provide flexible operational actions in response to the uncertain future scenarios. Performance analysis and computer simulation on the San Cristobal Wind Project demonstrate that the wind power uncertainty, control strategies, energy storage, and the wind turbine power curve have a significant impact on the performance of the system. In this dissertation, the relationship between option pricing theory and decision making process is discussed. A real option model is developed and presented through practical examples for assessing the value of hybrid wind-diesel power systems. Results show that operational options can provide additional value to the hybrid power system when this operational flexibility is correctly utilized. This framework can be applied in optimizing short term dispatch decisions considering the path-dependent nature of the optimal dispatch policy, given the plausible future realizations of the wind power production. Comparing with the existing valuation and optimization methods, result from numerical example shows that the dispatch policy resulting from the proposed optimization model exhibits a remarkable performance in minimizing the total fuel consumption of the wind-diesel system. In order to make optimal decisions, power plant operators and managers should not just focus on the direct outcome of each operational action; neither should they make deterministic decisions. The correct way is to dynamically manage the power system by taking into consideration the conditional future value in each option in response to the uncertainty.

Hacia un modelo dinámico para la isla de calor urbana de Madrid = Towards a Dynamic Model for the Urban Heat Island of Madrid

Esta investigación se enmarca dentro del proyecto MODIFICA (modelo predictivo - Edificios - Isla de Calor Urbano), financiado por el Programa de I + D + i Orientada a los Retos de la sociedad 'Retos Investigación' de 2013. Está dirigido a desarrollar un modelo predictivo de eficiencia energética para viviendas, bajo el efecto de isla de calor urbano (AUS) con el fin de ponerla en práctica en la evaluación de la demanda de energía real y el consumo en las viviendas. A pesar de los grandes avances que se han logrado durante los últimos años en el rendimiento energético de edificios, los archivos de tiempo utilizados en la construcción de simulaciones de energía se derivan generalmente de estaciones meteorológicas situadas en las afueras de la ciudad. Por lo tanto, el efecto de la Isla de Calor Urbano (ICU) no se considera en estos cálculos, lo que implica una importante falta de precisión. Centrado en explorar cómo incluir los fenómenos ICU, el presente trabajo recopila y analiza la dinámica por hora de la temperatura en diferentes lugares dentro de la ciudad de Madrid. Abstract This research is framed within the project MODIFICA (Predictive model - Buildings - Urban Heat Island), funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. It is aimed at developing a predictive model for dwelling energy performance under the Urban Heat Island (UHI) effect in order to implement it in the evaluation of real energy demand and consumption in dwellings. Despite great advances on building energy performance have been achieved during the last years, weather files used in building energy simulations are usually derived from weather stations placed in the outskirts of the city. Hence, Urban Heat Island (UHI) effect is not considered in this calculations, which implies an important lack of accuracy. Focused on exploring how to include the UHI phenomena, the present paper compiles and analyses the hourly dynamics of temperature in different locations within the city of Madrid.

Design and implementation of an adaptive dashboard and visualization interface for the dynamic optimization and control of Data Centers

Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.

Particle swarm optimization with sequential niche technique for dynamic finite element model updating

Peer reviewed

Dynamic weighting in Monte Carlo and optimization

Dynamic importance weighting is proposed as a Monte Carlo method that has the capability to sample relevant parts of the configuration space even in the presence of many steep energy minima. The method relies on an additional dynamic variable (the importance weight) to help the system overcome steep barriers. A non-Metropolis theory is developed for the construction of such weighted samplers. Algorithms based on this method are designed for simulation and global optimization tasks arising from multimodal sampling, neural network training, and the traveling salesman problem. Numerical tests on these problems confirm the effectiveness of the method.

Dynamics and folding of single two-stranded coiled-coil peptides studied by fluorescent energy transfer confocal microscopy

We report single-molecule measurements on the folding and unfolding conformational equilibrium distributions and dynamics of a disulfide crosslinked version of the two-stranded coiled coil from GCN4. The peptide has a fluorescent donor and acceptor at the N termini of its two chains and a Cys disulfide near its C terminus. Thus, folding brings the two N termini of the two chains close together, resulting in an enhancement of fluorescent resonant energy transfer. End-to-end distance distributions have thus been characterized under conditions where the peptide is nearly fully folded (0 M urea), unfolded (7.4 M urea), and in dynamic exchange between folded and unfolded states (3.0 M urea). The distributions have been compared for the peptide freely diffusing in solution and deposited onto aminopropyl silanized glass. As the urea concentration is increased, the mean end-to-end distance shifts to longer distances both in free solution and on the modified surface. The widths of these distributions indicate that the molecules are undergoing millisecond conformational fluctuations. Under all three conditions, these fluctuations gave nonexponential correlations on 1- to 100-ms time scale. A component of the correlation decay that was sensitive to the concentration of urea corresponded to that measured by bulk relaxation kinetics. The trajectories provided effective intramolecular diffusion coefficients as a function of the end-to-end distances for the folded and unfolded states. Single-molecule folding studies provide information concerning the distributions of conformational states in the folded, unfolded, and dynamically interconverting states.

Solvent dependence of dynamic transitions in protein solutions

A transition as a function of increasing temperature from harmonic to anharmonic dynamics has been observed in globular proteins by using spectroscopic, scattering, and computer simulation techniques. We present here results of a dynamic neutron scattering analysis of the solvent dependence of the picosecond-time scale dynamic transition behavior of solutions of a simple single-subunit enzyme, xylanase. The protein is examined in powder form, in D2O, and in four two-component perdeuterated single-phase cryosolvents in which it is active and stable. The scattering profiles of the mixed solvent systems in the absence of protein are also determined. The general features of the dynamic transition behavior of the protein solutions follow those of the solvents. The dynamic transition in all of the mixed cryosolvent–protein systems is much more gradual than in pure D2O, consistent with a distribution of energy barriers. The differences between the dynamic behaviors of the various cryosolvent protein solutions themselves are remarkably small. The results are consistent with a picture in which the picosecond-time scale atomic dynamics respond strongly to melting of pure water solvent but are relatively invariant in cryosolvents of differing compositions and melting points.

Probing the interaction between two single molecules: fluorescence resonance energy transfer between a single donor and a single acceptor.

We extend the sensitivity of fluorescence resonance energy transfer (FRET) to the single molecule level by measuring energy transfer between a single donor fluorophore and a single acceptor fluorophore. Near-field scanning optical microscopy (NSOM) is used to obtain simultaneous dual color images and emission spectra from donor and acceptor fluorophores linked by a short DNA molecule. Photodestruction dynamics of the donor or acceptor are used to determine the presence and efficiency of energy transfer. The classical equations used to measure energy transfer on ensembles of fluorophores are modified for single-molecule measurements. In contrast to ensemble measurements, dynamic events on a molecular scale are observable in single pair FRET measurements because they are not canceled out by random averaging. Monitoring conformational changes, such as rotations and distance changes on a nanometer scale, within single biological macromolecules, may be possible with single pair FRET.

Testing co-volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances

There is substantial empirical evidence that energy and financial markets are closely connected. As one of the most widely-used energy resources worldwide, natural gas has a large daily trading volume. In order to hedge the risk of natural gas spot markets, a large number of hedging strategies can be used, especially with the rapid development of natural gas derivatives markets. These hedging instruments include natural gas futures and options, as well as Exchange Traded Fund (ETF) prices that are related to natural gas stock prices. The volatility spillover effect is the delayed effect of a returns shock in one physical, biological or financial asset on the subsequent volatility or co-volatility of another physical, biological or financial asset. Investigating volatility spillovers within and across energy and financial markets is a crucial aspect of constructing optimal dynamic hedging strategies. The paper tests and calculates spillover effects among natural gas spot, futures and ETF markets using the multivariate conditional volatility diagonal BEKK model. The data used include natural gas spot and futures returns data from two major international natural gas derivatives markets, namely NYMEX (USA) and ICE (UK), as well as ETF data of natural gas companies from the stock markets in the USA and UK. The empirical results show that there are significant spillover effects in natural gas spot, futures and ETF markets for both USA and UK. Such a result suggests that both natural gas futures and ETF products within and beyond the country might be considered when constructing optimal dynamic hedging strategies for natural gas spot prices.

Volatility spillovers for spot, futures, and ETF prices in energy and agriculture

The agricultural and energy industries are closely related, both biologically and financially. The paper discusses the relationship and the interactions on price and volatility, with special focus on the covolatility spillover effects for these two industries. The interaction and covolatility spillovers or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper. Although there has already been significant research on biofuel and biofuel-related crops, much of the previous research has sought to find a relationship among commodity prices. Only a few published papers have been concerned with volatility spillovers. However, it must be emphasized that there have been numerous technical errors in the theoretical and empirical research, which needs to be corrected. The paper not only considers futures prices as a widely-used hedging instrument, but also takes an interesting new hedging instrument, ETF, into account. ETF is regarded as index futures when investors manage their portfolios, so it is possible to calculate an optimal dynamic hedging ratio. This is a very useful and interesting application for the estimation and testing of volatility spillovers. In the empirical analysis, multivariate conditional volatility diagonal BEKK models are estimated for comparing patterns of covolatility spillovers. The paper provides a new way of analyzing and describing the patterns of covolatility spillovers, which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects.

An econometric analysis of ETF and ETF futures in financial and energy markets using generated regressors

It is well known that that there is an intrinsic link between the financial and energy sectors, which can be analyzed through their spillover effects, which are measures of how the shocks to returns in different assets affect each other’s subsequent volatility in both spot and futures markets. Financial derivatives, which are not only highly representative of the underlying indices but can also be traded on both the spot and futures markets, include Exchange Traded Funds (ETFs), which is a tradable spot index whose aim is to replicate the return of an underlying benchmark index. When ETF futures are not available to examine spillover effects, “generated regressors” may be used to construct both Financial ETF futures and Energy ETF futures. The purpose of the paper is to investigate the covolatility spillovers within and across the US energy and financial sectors in both spot and futures markets, by using “generated regressors” and a multivariate conditional volatility model, namely Diagonal BEKK. The daily data used are from 1998/12/23 to 2016/4/22. The data set is analyzed in its entirety, and also subdivided into three subset time periods. The empirical results show there is a significant relationship between the Financial ETF and Energy ETF in the spot and futures markets. Therefore, financial and energy ETFs are suitable for constructing a financial portfolio from an optimal risk management perspective, and also for dynamic hedging purposes.

Dynamic bonding of metallic nanocontacts: Insights from experiments and atomistic simulations

The conductance across an atomically narrow metallic contact can be measured by using scanning tunneling microscopy. In certain situations, a jump in the conductance is observed right at the point of contact between the tip and the surface, which is known as “jump to contact” (JC). Such behavior provides a way to explore, at a fundamental level, how bonding between metallic atoms occurs dynamically. This phenomenon depends not only on the type of metal but also on the geometry of the two electrodes. For example, while some authors always find JC when approaching two atomically sharp tips of Cu, others find that a smooth transition occurs when approaching a Cu tip to an adatom on a flat surface of Cu. In an attempt to show that all these results are consistent, we make use of atomistic simulations; in particular, classical molecular dynamics together with density functional theory transport calculations to explore a number of possible scenarios. Simulations are performed for two different materials: Cu and Au in a [100] crystal orientation and at a temperature of 4.2 K. These simulations allow us to study the contribution of short- and long-range interactions to the process of bonding between metallic atoms, as well as to compare directly with experimental measurements of conductance, giving a plausible explanation for the different experimental observations. Moreover, we show a correlation between the cohesive energy of the metal, its Young's modulus, and the frequency of occurrence of a jump to contact.

Smart Monitoring Embedded Service for Energy-Efficient and Sustainable Management in Data Centers

Information technologies (IT) currently represent 2% of CO2 emissions. In recent years, a wide variety of IT solutions have been proposed, focused on increasing the energy efficiency of network data centers. Monitoring is one of the fundamental pillars of these systems, providing the information necessary for adequate decision making. However, today’s monitoring systems (MSs) are partial, specific and highly coupled solutions. This study proposes a model for monitoring data centers that serves as a basis for energy saving systems, offered as a value-added service embedded in a device with low cost and power consumption. The proposal is general in nature, comprehensive, scalable and focused on heterogeneous environments, and it allows quick adaptation to the needs of changing and dynamic environments. Further, a prototype of the system has been implemented in several devices, which has allowed validation of the proposal in addition to identification of the minimum hardware profile required to support the model.

Consensus, contradiction, and conciliation of interests: the geo-economics of the Energy Union. EPC Policy Brief, 8 July 2015

European Union energy policy calls for nothing less than a profound transformation of the EU's energy system: by 2050 decarbonised electricity generation with 80-95% fewer greenhouse gas emissions, increased use of renewables, more energy efficiency, a functioning energy market and increased security of supply are to be achieved. Different EU policies (e.g., EU climate and energy package for 2020) are intended to create the political and regulatory framework for this transformation. The sectorial dynamics resulting from these EU policies already affect the systems of electricity generation, transportation and storage in Europe, and the more effective the implementation of new measures the more the structure of Europe's power system will change in the years to come. Recent initiatives such as the 2030 climate/energy package and the Energy Union are supposed to keep this dynamic up. Setting new EU targets, however, is not necessarily the same as meeting them. The impact of EU energy policy is likely to have considerable geo-economic implications for individual member states: with increasing market integration come new competitors; coal and gas power plants face new renewable challengers domestically and abroad; and diversification towards new suppliers will result in new trade routes, entry points and infrastructure. Where these implications are at odds with powerful national interests, any member state may point to Article 194, 2 of the Lisbon Treaty and argue that the EU's energy policy agenda interferes with its given right to determine the conditions for exploiting its energy resources, the choice between different energy sources and the general structure of its energy supply. The implementation of new policy initiatives therefore involves intense negotiations to conciliate contradicting interests, something that traditionally has been far from easy to achieve. In areas where this process runs into difficulties, the transfer of sovereignty to the European level is usually to be found amongst the suggested solutions. Pooling sovereignty on a new level, however, does not automatically result in a consensus, i.e., conciliate contradicting interests. Rather than focussing on the right level of decision making, European policy makers need to face the (inconvenient truth of) geo-economical frictions within the Union that make it difficult to come to an arrangement. The reminder of this text explains these latter, more structural and sector-related challenges for European energy policy in more detail, and develops some concrete steps towards a political and regulatory framework necessary to overcome them.