Analytical study and evaluation results of power optimizers for distributed power conditioning in PV arrays

The use of modular or ‘micro’ maximum power point tracking (MPPT) converters at module level in series association, commercially known as “power optimizers”, allows the individual adaptation of each panel to the load, solving part of the problems related to partial shadows and different tilt and/or orientation angles of the photovoltaic (PV) modules. This is particularly relevant in building integrated PV systems. This paper presents useful behavioural analytical studies of cascade MPPT converters and evaluation test results of a prototype developed under a Spanish national research project. On the one hand, this work focuses on the development of new useful expressions which can be used to identify the behaviour of individual MPPT converters applied to each module and connected in series, in a typical grid-connected PV system. On the other hand, a novel characterization method of MPPT converters is developed, and experimental results of the prototype are obtained: when individual partial shading is applied, and they are connected in a typical grid connected PV array

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.

Surface velocity and mass balance of Livingston Island ice cap, Antarctica

The mass budget of the ice caps surrounding the Antarctica Peninsula and, in particular, the partitioning of its main components are poorly known. Here we approximate frontal ablation (i.e. the sum of mass losses by calving and submarine melt) and surface mass balance of the ice cap of Livingston Island, the second largest island in the South Shetland Islands archipelago, and analyse variations in surface velocity for the period 2007–2011. Velocities are obtained from feature tracking using 25 PALSAR-1 images, and used in conjunction with estimates of glacier ice thicknesses inferred from principles of glacier dynamics and ground-penetrating radar observations to estimate frontal ablation rates by a flux-gate approach. Glacier-wide surface mass-balance rates are approximated from in situ observations on two glaciers of the ice cap. Within the limitations of the large uncertainties mostly due to unknown ice thicknesses at the flux gates, we find that frontal ablation (−509 ± 263 Mt yr−1, equivalent to −0.73 ± 0.38 m w.e. yr−1 over the ice cap area of 697 km2) and surface ablation (−0.73 ± 0.10 m w.e. yr−1) contribute similar shares to total ablation (−1.46 ± 0.39 m w.e. yr−1). Total mass change (δM = −0.67 ± 0.40 m w.e. yr−1) is negative despite a slightly positive surface mass balance (0.06 ± 0.14 m w.e. yr−1). We find large interannual and, for some basins, pronounced seasonal variations in surface velocities at the flux gates, with higher velocities in summer than in winter. Associated variations in frontal ablation (of ~237 Mt yr−1; −0.34 m w.e. yr−1) highlight the importance of taking into account the seasonality in ice velocities when computing frontal ablation with a flux-gate approach.

Wind intermittency and CO2 reductions: the case of the spanish power system

Renewable energy sources are believed to reduce drastically greenhouse gas emissions that would otherwise be generated from fossil fuels used to generate electricity. This implies that a unit of renewable energy will replace a unit of fossil-fuel, with its CO2 emissions, on an equivalent basis (with no other effects on the grid). But, the fuel economy and emissions in the existing power systems are not proportional with the electricity production of intermittent sources due to cycling of the fossil fuel plants that make up the balance of the grid (i.e. changing the power output makes thermal units to operate less efficiently). This study focuses in the interactions between wind generation and thermal plants cycling, by establishing the levels of extra fuel use caused by decreased efficiencies of fossil back-up for wind electricity in Spain. We analyze the production of all thermal plants in 2011, studying different scenarios where wind penetration causes major deviations in programming, while we define a procedure for quantifying the carbon reductions by using emission factors and efficiency curves from the existing installations. The objectives are to discuss the real contributions of renewable energies to the environmental targets as well as suggest alternatives that would improve the reliability of future power systems.

Impact of N2 plasma power and duration on AlGaN/GaN HEMT

urface treatments have been recently shown to play an active role in electrical characteristics in AlGaN/GaN HEMTs, in particular during the passivation processing [1-4]. However, the responsible mechanisms are partially unknown and further studies are demanding. The effects of power and time N2 plasma pre-treatment prior to SiN deposition using PE-CVD (plasma enhanced chemical vapour deposition) on GaN and AlGaN/GaN HEMT have been investigated. The low power (60 W) plasma pre-treatment was found to improve the electronic characteristics in GaN based HEMT devices, independently of the time duration up to 20 min. In contrast, high power (150 and 210 W) plasma pretreatment showed detrimental effects in the electronic properties (Fig. 1), increasing the sheet resistance of the 2DEG, decreasing the 2DEG charge density in AlGaN/GaN HEMTs, transconductance reduction and decreasing the fT and fmax values up to 40% respect to the case using 60 W N2 plasma power. Although AFM (atomic force microscopy) results showed AlGaN and GaN surface roughness is not strongly affected by the N2-plasma, KFM (Kelvin force microscopy) surface analysis shows significant changes in the surface potential, trending to increase its values as the plasma power is higher. The whole results point at energetic ions inducing polarization-charge changes that affect dramatically to the 2-DEG charge density and the final characteristics of the HEMT devices. Therefore, we conclude that AlGaN surface is strongly sensitive to N2 plasma power conditions, which turn to be a key factor to achieve a good surface preparation prior to SiN passivation.

Teaching digital control of switch mode power supplier

This paper explains the methodology followed to teach the subject `Digital control of power converters'. This subject belongs to the research master on `Industrial Electronics' of the Universidad Politécnica de Madrid. The subject is composed of several theoretical lessons plus the development of an actual digital control. For that purpose an ad hoc dc-dc converter has been designed and built. The use of this board together with some software tools seems a very powerful way for the students to learn the concepts from the design to the real world

The use of wind pumps for greenhouse microirrigation: a case study for tomato in Cuba.

Crop irrigation is a major consumer of energy. Only a few countries are self-sufficient in conventional non-renewable energy sources. Fortunately, there are renewable ones, such as wind, which has experienced recent developments in the area of power generation. Wind pumps can play a vital role in irrigation projects in remote farms. A methodology based on daily estimation balance between water needs and water availability was used to evaluate the feasibility of the most economic windmill irrigation system. For this purpose, several factors were included: three-hourly wind velocity (W3 h, m/s), flow supplied by the wind pump as a function of the elevation height (H, m) and daily greenhouse evapotranspiration as a function of crop planting date. Monthly volumes of water required for irrigation (Dr, m3/ha) and in the water tank (Vd, m3), as well as the monthly irrigable area (Ar, ha), were estimated by cumulative deficit water budgeting taking in account these factors. An example is given illustrating the use of this methodology on tomato crop (Lycopersicon esculentum Mill.) under greenhouse at Ciego de Ávila, Cuba. In this case two different W3 h series (average and low wind year), three different H values and five tomato crop planting dates were considered. The results show that the optimum period of wind-pump driven irrigation is with crop plating in November, recommending a 5 m3 volume tank for cultivated areas around 0.2 ha when using wind pumps operating at 15 m of height elevation.

Use of calculus of variations to determine the shape of hovering rotors of minimum power and its application to micro air vehicles

In this paper, calculus of variations and combined blade element and momentum theory (BEMT) are used to demonstrate that, in hover, when neither root nor tip losses are considered; the rotor, which minimizes the total power (MPR), generates an induced velocity that varies linearly along the blade span. The angle of attack of every blade element is constant and equal to its optimum value. The traditional ideal twist (ITR) and optimum (OR) rotors are revisited in the context of this variational framework. Two more optimum rotors are obtained considering root and tip losses, the ORL, and the MPRL. A comparison between these five rotors is presented and discussed. The MPR and MPRL present a remarkable saving of power for low values of both thrust coefficient and maximum aerodynamic efficiency. The result obtained can be exploited to improve the aerodynamic behaviour of rotary wing micro air vehicles (MAV). A comparison with experimental results obtained from the literature is presented.

Smoothing of PV power fluctuations by geographical dispersion

The quality and the reliability of the power generated by large grid-connected photovoltaic (PV) plants are negatively affected by the source characteristic variability. This paper deals with the smoothing of power fluctuations because of geographical dispersion of PV systems. The fluctuation frequency and the maximum fluctuation registered at a PV plant ensemble are analyzed to study these effects. We propose an empirical expression to compare the fluctuation attenuation because of both the size and the number of PV plants grouped. The convolution of single PV plants frequency distribution functions has turned out to be a successful tool to statistically describe the behavior of an ensemble of PV plants and determine their maximum output fluctuation. Our work is based on experimental 1-s data collected throughout 2009 from seven PV plants, 20 MWp in total, separated between 6 and 360 km.

Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

Power density of a bare electrodynamic tether generator

The maximum performance of bare electrodynamic tethers as power generating systems under OML-theory is analyzed. Results show that best performance in terms of power density is achieved by designing the tether in such a way to increase ohmic impedance with respect to plasma contact impedance, hence favoring longer and thinner tethers. In such condition the corresponding optimal value of the load impedance is seen to approach the ohmic impedance of the conducting tether. At the other extreme, when plasma contact impedance dominates (which is not optimal but can be relevant for some applications) optimum power generation is found by matching the load impedance with an effective tether-plasma contact impedance whose expression is derived.

Impact of N2 plasma power discharge on AlGaN/GaN HEMT performance

The effects of power and time conditions of in situ N2 plasma treatment, prior to silicon nitride (SiN) passivation, were investigated on an AlGaN/GaN high-electron mobility transistor (HEMT). These studies reveal that N2 plasma power is a critical parameter to control the SiN/AlGaN interface quality, which directly affects the 2-D electron gas density. Significant enhancement in the HEMT characteristics was observed by using a low power N2 plasma pretreatment. In contrast, a marked gradual reduction in the maximum drain-source current density (IDS max) and maximum transconductance (gm max), as well as in fT and fmax, was observed as the N2 plasma power increases (up to 40% decrease for 210 W). Different mechanisms were proposed to be dominant as a function of the discharge power range. A good correlation was observed between the device electrical characteristics and the surface assessment by atomic force microscopy and Kelvin force microscopy techniques.

Supercritical Steam power cycle for Line-Focus Solar Power Plants

The supercritical Rankine power cycle offers a net improvement in plant efficiency compared with a subcritical Rankine cycle. For fossil power plants the minimum supercritical steam turbine size is about 450MW. A recent study between Sandia National Laboratories and Siemens Energy, Inc., published on March 2013, confirmed the feasibility of adapting the Siemens turbine SST-900 for supercritical steam in concentrated solar power plants, with a live steam conditions 230-260 bar and output range between 140-200 MWe. In this context, this analysis is focused on integrating a line-focus solar field with a supercritical Rankine power cycle. For this purpose two heat transfer fluids were assessed: direct steam generation and molten salt Hitec XL. To isolate solar field from high pressure supercritical water power cycle, an intermediate heat exchanger was installed between linear solar collectors and balance of plant. Due to receiver selective coating temperature limitations, turbine inlet temperature was fixed 550ºC. The design-point conditions were 550ºC and 260 bar at turbine inlet, and 165 MWe Gross power output. Plant performance was assessed at design-point in the supercritical power plant (between 43-45% net plant efficiency depending on balance of plantconfiguration), and in the subcritical plant configuration (~40% net plant efficiency). Regarding the balance of plant configuration, direct reheating was adopted as the optimum solution to avoid any intermediate heat exchanger. One direct reheating stage between high pressure turbine and intermediate pressure turbine is the common practice; however, General Electric ultrasupercritical(350 bar) fossil power plants also considered doubled-reheat applications. In this study were analyzed heat balances with single-reheat, double-reheat and even three reheating stages. In all cases were adopted the proper reheating solar field configurations to limit solar collectors pressure drops. As main conclusion, it was confirmed net plant efficiency improvements in supercritical Rankine line-focus (parabolic or linear Fresnel) solar plant configurations are mainly due to the following two reasons: higher number of feed-water preheaters (up to seven)delivering hotter water at solar field inlet, and two or even three direct reheating stages (550ºC reheating temperature) in high or intermediate pressure turbines. However, the turbine manufacturer should confirm the equipment constrains regarding reheating stages and number of steam extractions to feed-water heaters.

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.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.