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.

Fresnel-based modular solar fields for performance/cost optimization in solar thermal power plants: A comparison with parabolic trough collectors.

Linear Fresnel collectors are identified as a technology that should play a main role in order to reduce cost of Concentrating Solar Power. An optical and thermal analysis of the different blocks of the solar power plant is carried out, where Fresnel arrays are compared with the most extended linear technology: parabolic trough collectors. It is demonstrated that the optical performance of Fresnel array is very close to that of PTC, with similar values of maximum flux intensities. In addition, if the heat carrier fluid flows in series by the tubes of the receiver, relatively high thermal efficiencies are achieved. Thus, an annual solar to electricity efficiency of 19% is expected, which is similar to the state of the art in PTCs; this is done with a reduction of costs, thanks to lighter structures, that drives to an estimation of LCOE of around 6.5 c€/kWh.

Laser-fired contact optimization in c-Si solar cells

In this work we study the optimization of laser-fired contact (LFC) processing parameters, namely laser power and number of pulses, based on the electrical resistance measurement of an aluminum single LFC point. LFC process has been made through four passivation layers that are typically used in c-Si and mc-Si solar cell fabrication: thermally grown silicon oxide (SiO2), deposited phosphorus-doped amorphous silicon carbide (a-SiCx/H(n)), aluminum oxide (Al2O3) and silicon nitride (SiNx/H) films. Values for the LFC resistance normalized by the laser spot area in the range of 0.65–3 mΩ cm2 have been obtained

A low power routing algorithm for localization in IEEE 802.15.4 networks

Many context-aware applications rely on the knowledge of the position of the user and the surrounding objects to provide advanced, personalized and real-time services. In wide-area deployments, a routing protocol is needed to collect the location information from distant nodes. In this paper, we propose a new source-initiated (on demand) routing protocol for location-aware applications in IEEE 802.15.4 wireless sensor networks. This protocol uses a low power MAC layer to maximize the lifetime of the network while maintaining the communication delay to a low value. Its performance is assessed through experimental tests that show a good trade-off between power consumption and time delay in the localization of a mobile device.

Power Measurement Methodology for FPGA Devices

The efficiency of power optimization tools depends on information on design power provided by the power estimation models. Power models targeting different power groups can enable fast identification of the most power consuming parts of design and their properties. The accuracy of these estimation models is highly dependent on the accuracy of the method used for their characterization. The highest precision is achieved by using physical onboard measurements. In this paper, we present a measurement methodology that is primarily aimed at calibrating and validating high-level dynamic power estimation models. The measurements have been carefully designed to enable the separation of the interconnect power from the logic power and the power of the clock circuitry, so that each of these power groups can be used for the corresponding model validation. The standard measurement uncertainty is lower than 2% of the measured value even with a very small number of repeated measurements. Additionally, the accuracy of a commercial low-level power estimation tool has been also assessed for comparison purposes. The results indicate that the tool is not suitable for power estimation of data path-oriented designs.

Sputter optimization of AlN on diamond substrates for high frequency SAW resonators

The AlN/diamond structure is an attractive combination for SAW devices and its application at high frequencies. In this work, the synthesis of AlN thin films by reactive sputtering has been optimized on diamond substrates in order to process high frequency devices. Polished microcrystalline and as-grown nanocrystalline diamond substrates have been used to deposit AlN of different thickness under equal sputtering conditions. For the smoother substrates, the FWHM of the rocking curve of the (002) AlN peak varies from 3.8° to 2.7° with increasing power. SAW one port resonators have been fabricated on these films, whose electrical characterization (in terms of S11 parameters) is reported.

Ultra Low Power FPGA-Based Architecture for Wake-up Radio in Wireless Sensor Networks

In this paper the capabilities of ultra low power FPGAs to implement Wake-up Radios (WuR) for ultra low energy Wireless Sensor Networks (WSNs) are analyzed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the more common approaches based on ASICs or microcontrollers. In this context, energy efficiency is a key aspect, considering that usually the instant power consumption is considered a figure of merit, more than the total energy consumed by the application.

Wake up Radio Architecture for Wireless Sensor Networks Using an Ultra Low Power FPGA

In this paper an implementation of a Wake up Radio(WuR) with addressing capabilities based on an ultra low power FPGA for ultra low energy Wireless Sensor Networks (WSNs) is proposed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the traditional approaches based on ASICs or microcontrollers, for communication frame decoding and communication data control.

Clean Coal Technologies Scenario and Evaluation of Present CO2 Dwindling Initiatives to Approach Zero Emission Power Stations By Coal Combustion. Deployment Situation and Evaluation Study

In the present uncertain global context of reaching an equal social stability and steady thriving economy, power demand expected to grow and global electricity generation could nearly double from 2005 to 2030. Fossil fuels will remain a significant contribution on this energy mix up to 2050, with an expected part of around 70% of global and ca. 60% of European electricity generation. Coal will remain a key player. Hence, a direct effect on the considered CO2 emissions business-as-usual scenario is expected, forecasting three times the present CO2 concentration values up to 1,200ppm by the end of this century. Kyoto protocol was the first approach to take global responsibility onto CO2 emissions monitoring and cap targets by 2012 with reference to 1990. Some of principal CO2emitters did not ratify the reduction targets. Although USA and China spur are taking its own actions and parallel reduction measures. More efficient combustion processes comprising less fuel consuming, a significant contribution from the electricity generation sector to a CO2 dwindling concentration levels, might not be sufficient. Carbon Capture and Storage (CCS) technologies have started to gain more importance from the beginning of the decade, with research and funds coming out to drive its come in useful. After first researching projects and initial scale testing, three principal capture processes came out available today with first figures showing up to 90% CO2 removal by its standard applications in coal fired power stations. Regarding last part of CO2 reduction chain, two options could be considered worthy, reusing (EOR & EGR) and storage. The study evaluates the state of the CO2 capture technology development, availability and investment cost of the different technologies, with few operation cost analysis possible at the time. Main findings and the abatement potential for coal applications are presented. DOE, NETL, MIT, European universities and research institutions, key technology enterprises and utilities, and key technology suppliers are the main sources of this study. A vision of the technology deployment is presented.

Modulation-mode Assignment for SVD-assisted Multiuser MIMO Systems with Correlation.

Multiuser multiple-input multiple-output (MIMO) downlink (DL) transmission schemes experience both multiuser interference as well as inter-antenna interference. The singular value decomposition provides an appropriate mean to process channel information and allows us to take the individual user’s channel characteristics into account rather than treating all users channels jointly as in zero-forcing (ZF) multiuser transmission techniques. However, uncorrelated MIMO channels has attracted a lot of attention and reached a state of maturity. By contrast, the performance analysis in the presence of antenna fading correlation, which decreases the channel capacity, requires substantial further research. The joint optimization of the number of activated MIMO layers and the number of bits per symbol along with the appropriate allocation of the transmit power shows that not necessarily all user-specific MIMO layers has to be activated in order to minimize the overall BER under the constraint of a given fixed data throughput.

Performance optimization in switched reluctance motor drives

In this paper, switched reluctance motors (SRM) are proposed as an alternative for electric power assisted steering (EPAS) applications. A prototype machine has been developed as very attractive design for a steering electric motor, both from a cost and size perspective. A fourphase 8/6 SRM drive is designed for a rack type EPAS which should provide a maximum force of 10 kN. Two-dimension finite element analysis is used to validate the design.

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.

Energy and power aware scheduling algorithm modeling for battery powered embedded systems

Energy management has always been recognized as a challenge in mobile systems, especially in modern OS-based mobile systems where multi-functioning are widely supported. Nowadays, it is common for a mobile system user to run multiple applications simultaneously while having a target battery lifetime in mind for a specific application. Traditional OS-level power management (PM) policies make their best effort to save energy under performance constraint, but fail to guarantee a target lifetime, leaving the painful trading off between the total performance of applications and the target lifetime to the user itself. This thesis provides a new way to deal with the problem. It is advocated that a strong energy-aware PM scheme should first guarantee a user-specified battery lifetime to a target application by restricting the average power of those less important applications, and in addition to that, maximize the total performance of applications without harming the lifetime guarantee. As a support, energy, instead of CPU or transmission bandwidth, should be globally managed as the first-class resource by the OS. As the first-stage work of a complete PM scheme, this thesis presents the energy-based fair queuing scheduling, a novel class of energy-aware scheduling algorithms which, in combination with a mechanism of battery discharge rate restricting, systematically manage energy as the first-class resource with the objective of guaranteeing a user-specified battery lifetime for a target application in OS-based mobile systems. Energy-based fair queuing is a cross-application of the traditional fair queuing in the energy management domain. It assigns a power share to each task, and manages energy by proportionally serving energy to tasks according to their assigned power shares. The proportional energy use establishes proportional share of the system power among tasks, which guarantees a minimum power for each task and thus, avoids energy starvation on any task. Energy-based fair queuing treats all tasks equally as one type and supports periodical time-sensitive tasks by allocating each of them a share of system power that is adequate to meet the highest energy demand in all periods. However, an overly conservative power share is usually required to guarantee the meeting of all time constraints. To provide more effective and flexible support for various types of time-sensitive tasks in general purpose operating systems, an extra real-time friendly mechanism is introduced to combine priority-based scheduling into the energy-based fair queuing. Since a method is available to control the maximum time one time-sensitive task can run with priority, the power control and time-constraint meeting can be flexibly traded off. A SystemC-based test-bench is designed to assess the algorithms. Simulation results show the success of the energy-based fair queuing in achieving proportional energy use, time-constraint meeting, and a proper trading off between them. La gestión de energía en los sistema móviles está considerada hoy en día como un reto fundamental, notándose, especialmente, en aquellos terminales que utilizando un sistema operativo implementan múltiples funciones. Es común en los sistemas móviles actuales ejecutar simultaneamente diferentes aplicaciones y tener, para una de ellas, un objetivo de tiempo de uso de la batería. Tradicionalmente, las políticas de gestión de consumo de potencia de los sistemas operativos hacen lo que está en sus manos para ahorrar energía y satisfacer sus requisitos de prestaciones, pero no son capaces de proporcionar un objetivo de tiempo de utilización del sistema, dejando al usuario la difícil tarea de buscar un compromiso entre prestaciones y tiempo de utilización del sistema. Esta tesis, como contribución, proporciona una nueva manera de afrontar el problema. En ella se establece que un esquema de gestión de consumo de energía debería, en primer lugar, garantizar, para una aplicación dada, un tiempo mínimo de utilización de la batería que estuviera especificado por el usuario, restringiendo la potencia media consumida por las aplicaciones que se puedan considerar menos importantes y, en segundo lugar, maximizar las prestaciones globales sin comprometer la garantía de utilización de la batería. Como soporte de lo anterior, la energía, en lugar del tiempo de CPU o el ancho de banda, debería gestionarse globalmente por el sistema operativo como recurso de primera clase. Como primera fase en el desarrollo completo de un esquema de gestión de consumo, esta tesis presenta un algoritmo de planificación de encolado equitativo (fair queueing) basado en el consumo de energía, es decir, una nueva clase de algoritmos de planificación que, en combinación con mecanismos que restrinjan la tasa de descarga de una batería, gestionen de forma sistemática la energía como recurso de primera clase, con el objetivo de garantizar, para una aplicación dada, un tiempo de uso de la batería, definido por el usuario, en sistemas móviles empotrados. El encolado equitativo de energía es una extensión al dominio de la energía del encolado equitativo tradicional. Esta clase de algoritmos asigna una reserva de potencia a cada tarea y gestiona la energía sirviéndola de manera proporcional a su reserva. Este uso proporcional de la energía garantiza que cada tarea reciba una porción de potencia y evita que haya tareas que se vean privadas de recibir energía por otras con un comportamiento más ambicioso. Esta clase de algoritmos trata a todas las tareas por igual y puede planificar tareas periódicas en tiempo real asignando a cada una de ellas una reserva de potencia que es adecuada para proporcionar la mayor de las cantidades de energía demandadas por período. Sin embargo, es posible demostrar que sólo se consigue cumplir con los requisitos impuestos por todos los plazos temporales con reservas de potencia extremadamente conservadoras. En esta tesis, para proporcionar un soporte más flexible y eficiente para diferentes tipos de tareas de tiempo real junto con el resto de tareas, se combina un mecanismo de planificación basado en prioridades con el encolado equitativo basado en energía. En esta clase de algoritmos, gracias al método introducido, que controla el tiempo que se ejecuta con prioridad una tarea de tiempo real, se puede establecer un compromiso entre el cumplimiento de los requisitos de tiempo real y el consumo de potencia. Para evaluar los algoritmos, se ha diseñado en SystemC un banco de pruebas. Los resultados muestran que el algoritmo de encolado equitativo basado en el consumo de energía consigue el balance entre el uso proporcional a la energía reservada y el cumplimiento de los requisitos de tiempo real.

Optimization of logic programs with dynamic scheduling

Dynamic scheduling increases the expressive power of logic programming languages, but also introduces some overhead. In this paper we present two classes of program transformations designed to reduce this additional overhead, while preserving the operational semantics of the original programs, modulo ordering of literals woken at the same time. The first class of transformations simplifies the delay conditions while the second class moves delayed literals later in the rule body. Application of the program transformations can be automated using information provided by compile-time analysis. We provide experimental results obtained from an implementation of the proposed techniques using the CIAO prototype compiler. Our results show that the techniques can lead to substantial performance improvement.

Specialization and optimization of constraint programs with dynamic scheduling

In this report we discuss some of the issues involved in the specialization and optimization of constraint logic programs with dynamic scheduling. Dynamic scheduling, as any other form of concurrency, increases the expressive power of constraint logic programs, but also introduces run-time overhead. The objective of the specialization and optimization is to reduce as much as possible such overhead automatically, while preserving the semantics of the original programs. This is done by program transformation based on global analysis. We present implementation techniques for this purpose and report on experimental results obtained from an implementation of the techniques in the context of the CIAO compiler.