Mikrobielle Prozesskontrolle in Biogasanlagen durch Monitoring der Kohlenstoff-Isotopenverhältnisse im Gasbereich

Der zunehmende Anteil von Strom aus erneuerbaren Energiequellen erfordert ein dynamisches Konzept, um Spitzenlastzeiten und Versorgungslücken aus der Wind- und Solarenergie ausgleichen zu können. Biogasanlagen können aufgrund ihrer hohen energetischen Verfügbarkeit und der Speicherbarkeit von Biogas eine flexible Energiebereitstellung ermöglichen und darüber hinaus über ein „Power-to-Gas“-Verfahren bei einem kurzzeitigen Überschuss von Strom eine Überlastung des Stromnetzes verhindern. Ein nachfrageorientierter Betrieb von Biogasanlagen stellt jedoch hohe Anforderungen an die Mikrobiologie im Reaktor, die sich an die häufig wechselnden Prozessbedingungen wie der Raumbelastung im Reaktor anpassen muss. Eine Überwachung des Fermentationsprozesses in Echtzeit ist daher unabdingbar, um Störungen in den mikrobiellen Gärungswegen frühzeitig erkennen und adäquat entgegenwirken zu können. rnBisherige mikrobielle Populationsanalysen beschränken sich auf aufwendige, molekularbiologische Untersuchungen des Gärsubstrates, deren Ergebnisse dem Betreiber daher nur zeitversetzt zur Verfügung stehen. Im Rahmen dieser Arbeit wurde erstmalig ein Laser-Absorptionsspektrometer zur kontinuierlichen Messung der Kohlenstoff-Isotopenverhältnisse des Methans an einer Forschungsbiogasanlage erprobt. Dabei konnten, in Abhängigkeit der Raumbelastung und Prozessbedingungen variierende Isotopenverhältnisse gemessen werden. Anhand von Isolaten aus dem untersuchten Reaktor konnte zunächst gezeigt werden, dass für jeden Methanogenesepfad (hydrogeno-troph, aceto¬klastisch sowie methylotroph) eine charakteristische, natürliche Isotopensignatur im Biogas nachgewiesen werden kann, sodass eine Identifizierung der aktuell dominierenden methanogenen Reaktionen anhand der Isotopen-verhältnisse im Biogas möglich ist. rnDurch den Einsatz von 13C- und 2H-isotopen¬markierten Substraten in Rein- und Mischkulturen und Batchreaktoren, sowie HPLC- und GC-Unter¬suchungen der Stoffwechselprodukte konnten einige bislang unbekannte C-Flüsse in Bioreaktoren festgestellt werden, die sich wiederum auf die gemessenen Isotopenverhältnisse im Biogas auswirken können. So konnte die Entstehung von Methanol sowie dessen mikrobieller Abbauprodukte bis zur finalen CH4-Bildung anhand von fünf Isolaten erstmalig in einer landwirtschaftlichen Biogasanlage rekonstruiert und das Vorkommen methylotropher Methanogenesewege nachgewiesen werden. Mithilfe molekularbiologischer Methoden wurden darüber hinaus methanoxidierende Bakterien zahlreicher, unbekannter Arten im Reaktor detektiert, deren Vorkommen aufgrund des geringen O2-Gehaltes in Biogasanlagen bislang nicht erwartet wurde. rnDurch die Konstruktion eines synthetischen DNA-Stranges mit den Bindesequenzen für elf spezifische Primerpaare konnte eine neue Methode etabliert werden, anhand derer eine Vielzahl mikrobieller Zielorganismen durch die Verwendung eines einheitlichen Kopienstandards in einer real-time PCR quantifiziert werden können. Eine über 70 Tage durchgeführte, wöchentliche qPCR-Analyse von Fermenterproben zeigte, dass die Isotopenverhältnisse im Biogas signifikant von der Zusammensetzung der Reaktormikrobiota beeinflusst sind. Neben den aktuell dominierenden Methanogenesewegen war es auch möglich, einige bakterielle Reaktionen wie eine syntrophe Acetatoxidation, Acetogenese oder Sulfatreduktion anhand der δ13C (CH4)-Werte zu identifizieren, sodass das hohe Potential einer kontinuierlichen Isotopenmessung zur Prozessanalytik in Biogasanlagen aufgezeigt werden konnte.rn

CAN CHINA USE ALTERNATIVE ENERGIES INSTEAD OF COAL TO PROVIDE MORE ELECTRICITY BY 2030?

Following the rapid growth of China's economy, energy consumption, especially electricity consumption of China, has made a huge increase in the past 30 years. Since China has been using coal as the major energy source to produce electricity during these years, environmental problems have become more and more serious. The research question for this paper is: "Can China use alternative energies instead of coal to produce more electricity in 2030?" Hydro power, nuclear power, natural gas, wind power and solar power are considered as the possible and most popular alternative energies for the current situation of China. To answer the research question above, there are two things to know: How much is the total electricity consumption in China by 2030? And how much electricity can the alternative energies provide in China by 2030? For a more reliable forecast, an econometric model using the Ordinary Least Squares Method is established on this paper to predict the total electricity consumption by 2030. The predicted electricity coming from alternative energy sources by 2030 in China can be calculated from the existing literature. The research results of this paper are analyzed under a reference scenario and a max tech scenario. In the reference scenario, the combination of the alternative energies can provide 47.71% of the total electricity consumption by 2030. In the max tech scenario, it provides 57.96% of the total electricity consumption by 2030. These results are important not only because they indicate the government's long term goal is reachable, but also implies that the natural environment of China could have an inspiring future.

MultiPARTES: Multicore Virtualization for Mixed-Criticality Systems

Modern embedded applications typically integrate a multitude of functionalities with potentially different criticality levels into a single system. Without appropriate preconditions, the integration of mixed-criticality subsystems can lead to a significant and potentially unacceptable increase of engineering and certification costs. A promising solution is to incorporate mechanisms that establish multiple partitions with strict temporal and spatial separation between the individual partitions. In this approach, subsystems with different levels of criticality can be placed in different partitions and can be verified and validated in isolation. The MultiPARTES FP7 project aims at supporting mixed- criticality integration for embedded systems based on virtualization techniques for heterogeneous multicore processors. A major outcome of the project is the MultiPARTES XtratuM, an open source hypervisor designed as a generic virtualization layer for heterogeneous multicore. MultiPARTES evaluates the developed technology through selected use cases from the offshore wind power, space, visual surveillance, and automotive domains. The impact of MultiPARTES on the targeted domains will be also discussed. In a number of ongoing research initiatives (e.g., RECOMP, ARAMIS, MultiPARTES, CERTAINTY) mixed-criticality integration is considered in multicore processors. Key challenges are the combination of software virtualization and hardware segregation and the extension of partitioning mechanisms to jointly address significant non-functional requirements (e.g., time, energy and power budgets, adaptivity, reliability, safety, security, volume, weight, etc.) along with development and certification methodology.

Deviation of Cup and Propeller Anemometer Calibration Results with Air Density

The effect of air density variations on the calibration constants of several models of anemometers has been analyzed. The analysis was based on a series of calibrations between March 2003 and February 2011. Results indicate a linear behavior of both calibration constants with the air density. The effect of changes in air density on the measured wind speed by an anemometer was also studied. The results suggest that there can be an important deviation of the measured wind speed with changes in air density from the one at which the anemometer was calibrated, and therefore the need to take this effect into account when calculating wind power estimations.

Electricity price forecasting accounting for renewable energies: optimal combined forecasts

Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as Spain, Germany and Denmark, renewable energy is having a deep impact on the local power markets. In this paper, we propose an optimal model from the perspective of forecasting accuracy, and it consists of a combination of several univariate and multivariate time series methods that account for the amount of energy produced with clean energies, particularly wind and hydro, which are the most relevant renewable energy sources in the Iberian Market. This market is used to illustrate the proposed methodology, as it is one of those markets in which wind power production is more relevant in terms of its percentage of the total demand, but of course our method can be applied to any other liberalised power market. As far as our contribution is concerned, first, the methodology proposed by García-Martos et al(2007 and 2012) is generalised twofold: we allow the incorporation of wind power production and hydro reservoirs, and we do not impose the restriction of using the same model for 24h. A computational experiment and a Design of Experiments (DOE) are performed for this purpose. Then, for those hours in which there are two or more models without statistically significant differences in terms of their forecasting accuracy, a combination of forecasts is proposed by weighting the best models(according to the DOE) and minimising the Mean Absolute Percentage Error (MAPE). The MAPE is the most popular accuracy metric for comparing electricity price forecasting models. We construct the combi nation of forecasts by solving several nonlinear optimisation problems that allow computation of the optimal weights for building the combination of forecasts. The results are obtained by a large computational experiment that entails calculating out-of-sample forecasts for every hour in every day in the period from January 2007 to Decem ber 2009. In addition, to reinforce the value of our methodology, we compare our results with those that appear in recent published works in the field. This comparison shows the superiority of our methodology in terms of forecasting accuracy.

Optimal Combined Forecasts for Electricity Prices: Influence of Clean Energies

In this work, an electricity price forecasting model is developed. The performance of the proposed approach is improved by considering renewable energies (wind power and hydro generation) as explanatory variables. Additionally, the resulting forecasts are obtained as an optimal combination of a set of several univariate and multivariate time series models. The large computational experiment carried out using out-of-sample forecasts for every hour and day allows withdrawing statistically sound conclusions

A framework for mixed-criticality partitioned real-time embedded systems

Los sistemas empotrados son cada día más comunes y complejos, de modo que encontrar procesos seguros, eficaces y baratos de desarrollo software dirigidos específicamente a esta clase de sistemas es más necesario que nunca. A diferencia de lo que ocurría hasta hace poco, en la actualidad los avances tecnológicos en el campo de los microprocesadores de los últimos tiempos permiten el desarrollo de equipos con prestaciones más que suficientes para ejecutar varios sistemas software en una única máquina. Además, hay sistemas empotrados con requisitos de seguridad (safety) de cuyo correcto funcionamiento depende la vida de muchas personas y/o grandes inversiones económicas. Estos sistemas software se diseñan e implementan de acuerdo con unos estándares de desarrollo software muy estrictos y exigentes. En algunos casos puede ser necesaria también la certificación del software. Para estos casos, los sistemas con criticidades mixtas pueden ser una alternativa muy valiosa. En esta clase de sistemas, aplicaciones con diferentes niveles de criticidad se ejecutan en el mismo computador. Sin embargo, a menudo es necesario certificar el sistema entero con el nivel de criticidad de la aplicación más crítica, lo que hace que los costes se disparen. La virtualización se ha postulado como una tecnología muy interesante para contener esos costes. Esta tecnología permite que un conjunto de máquinas virtuales o particiones ejecuten las aplicaciones con unos niveles de aislamiento tanto temporal como espacial muy altos. Esto, a su vez, permite que cada partición pueda ser certificada independientemente. Para el desarrollo de sistemas particionados con criticidades mixtas se necesita actualizar los modelos de desarrollo software tradicionales, pues estos no cubren ni las nuevas actividades ni los nuevos roles que se requieren en el desarrollo de estos sistemas. Por ejemplo, el integrador del sistema debe definir las particiones o el desarrollador de aplicaciones debe tener en cuenta las características de la partición donde su aplicación va a ejecutar. Tradicionalmente, en el desarrollo de sistemas empotrados, el modelo en V ha tenido una especial relevancia. Por ello, este modelo ha sido adaptado para tener en cuenta escenarios tales como el desarrollo en paralelo de aplicaciones o la incorporación de una nueva partición a un sistema ya existente. El objetivo de esta tesis doctoral es mejorar la tecnología actual de desarrollo de sistemas particionados con criticidades mixtas. Para ello, se ha diseñado e implementado un entorno dirigido específicamente a facilitar y mejorar los procesos de desarrollo de esta clase de sistemas. En concreto, se ha creado un algoritmo que genera el particionado del sistema automáticamente. En el entorno de desarrollo propuesto, se han integrado todas las actividades necesarias para desarrollo de un sistema particionado, incluidos los nuevos roles y actividades mencionados anteriormente. Además, el diseño del entorno de desarrollo se ha basado en la ingeniería guiada por modelos (Model-Driven Engineering), la cual promueve el uso de los modelos como elementos fundamentales en el proceso de desarrollo. Así pues, se proporcionan las herramientas necesarias para modelar y particionar el sistema, así como para validar los resultados y generar los artefactos necesarios para el compilado, construcción y despliegue del mismo. Además, en el diseño del entorno de desarrollo, la extensión e integración del mismo con herramientas de validación ha sido un factor clave. En concreto, se pueden incorporar al entorno de desarrollo nuevos requisitos no-funcionales, la generación de nuevos artefactos tales como documentación o diferentes lenguajes de programación, etc. Una parte clave del entorno de desarrollo es el algoritmo de particionado. Este algoritmo se ha diseñado para ser independiente de los requisitos de las aplicaciones así como para permitir al integrador del sistema implementar nuevos requisitos del sistema. Para lograr esta independencia, se han definido las restricciones al particionado. El algoritmo garantiza que dichas restricciones se cumplirán en el sistema particionado que resulte de su ejecución. Las restricciones al particionado se han diseñado con una capacidad expresiva suficiente para que, con un pequeño grupo de ellas, se puedan expresar la mayor parte de los requisitos no-funcionales más comunes. Las restricciones pueden ser definidas manualmente por el integrador del sistema o bien pueden ser generadas automáticamente por una herramienta a partir de los requisitos funcionales y no-funcionales de una aplicación. El algoritmo de particionado toma como entradas los modelos y las restricciones al particionado del sistema. Tras la ejecución y como resultado, se genera un modelo de despliegue en el que se definen las particiones que son necesarias para el particionado del sistema. A su vez, cada partición define qué aplicaciones deben ejecutar en ella así como los recursos que necesita la partición para ejecutar correctamente. El problema del particionado y las restricciones al particionado se modelan matemáticamente a través de grafos coloreados. En dichos grafos, un coloreado propio de los vértices representa un particionado del sistema correcto. El algoritmo se ha diseñado también para que, si es necesario, sea posible obtener particionados alternativos al inicialmente propuesto. El entorno de desarrollo, incluyendo el algoritmo de particionado, se ha probado con éxito en dos casos de uso industriales: el satélite UPMSat-2 y un demostrador del sistema de control de una turbina eólica. Además, el algoritmo se ha validado mediante la ejecución de numerosos escenarios sintéticos, incluyendo algunos muy complejos, de más de 500 aplicaciones. ABSTRACT The importance of embedded software is growing as it is required for a large number of systems. Devising cheap, efficient and reliable development processes for embedded systems is thus a notable challenge nowadays. Computer processing power is continuously increasing, and as a result, it is currently possible to integrate complex systems in a single processor, which was not feasible a few years ago.Embedded systems may have safety critical requirements. Its failure may result in personal or substantial economical loss. The development of these systems requires stringent development processes that are usually defined by suitable standards. In some cases their certification is also necessary. This scenario fosters the use of mixed-criticality systems in which applications of different criticality levels must coexist in a single system. In these cases, it is usually necessary to certify the whole system, including non-critical applications, which is costly. Virtualization emerges as an enabling technology used for dealing with this problem. The system is structured as a set of partitions, or virtual machines, that can be executed with temporal and spatial isolation. In this way, applications can be developed and certified independently. The development of MCPS (Mixed-Criticality Partitioned Systems) requires additional roles and activities that traditional systems do not require. The system integrator has to define system partitions. Application development has to consider the characteristics of the partition to which it is allocated. In addition, traditional software process models have to be adapted to this scenario. The V-model is commonly used in embedded systems development. It can be adapted to the development of MCPS by enabling the parallel development of applications or adding an additional partition to an existing system. The objective of this PhD is to improve the available technology for MCPS development by providing a framework tailored to the development of this type of system and by defining a flexible and efficient algorithm for automatically generating system partitionings. The goal of the framework is to integrate all the activities required for developing MCPS and to support the different roles involved in this process. The framework is based on MDE (Model-Driven Engineering), which emphasizes the use of models in the development process. The framework provides basic means for modeling the system, generating system partitions, validating the system and generating final artifacts. The framework has been designed to facilitate its extension and the integration of external validation tools. In particular, it can be extended by adding support for additional non-functional requirements and support for final artifacts, such as new programming languages or additional documentation. The framework includes a novel partitioning algorithm. It has been designed to be independent of the types of applications requirements and also to enable the system integrator to tailor the partitioning to the specific requirements of a system. This independence is achieved by defining partitioning constraints that must be met by the resulting partitioning. They have sufficient expressive capacity to state the most common constraints and can be defined manually by the system integrator or generated automatically based on functional and non-functional requirements of the applications. The partitioning algorithm uses system models and partitioning constraints as its inputs. It generates a deployment model that is composed by a set of partitions. Each partition is in turn composed of a set of allocated applications and assigned resources. The partitioning problem, including applications and constraints, is modeled as a colored graph. A valid partitioning is a proper vertex coloring. A specially designed algorithm generates this coloring and is able to provide alternative partitions if required. The framework, including the partitioning algorithm, has been successfully used in the development of two industrial use cases: the UPMSat-2 satellite and the control system of a wind-power turbine. The partitioning algorithm has been successfully validated by using a large number of synthetic loads, including complex scenarios with more that 500 applications.

Integración técnica y económica de energías renovables, en un sistema eléctrico liberalizado, a partir de vectores energéticos

El objetivo de la tesis es estudiar la bondad del almacenamiento de energía en hidrógeno para minorar los desvíos de energía respecto a su previsión de parques eólicos y huertas solares. Para ello se ha partido de datos de energías horarias previstas con 24 h de antelación y la energía real generada. Se ha procedido a dimensionar la planta de hidrógeno, a partir de una modelización de la operación de la misma, teniendo siempre como objetivo la limitación de los desvíos. Posteriormente, se ha procedido a simular la operación de la planta con dos objetivos en mente, uno limitar los desvíos y por otro lado operar la planta como una central de bombeo, generando hidrógeno en horas valle y generando electricidad en horas punta. Las dos simulaciones se han aplicado a tres parques eólicos de diferentes potencias, y a una huerta solar fotovoltaica. Se ha realizado un estudio económico para determinar la viabilidad de las plantas dimensionadas, obteniendo como resultado que no son viables a día de hoy y con la estimación de precios considerada, necesitando disminuir considerablemente los costes, dependiendo fuertemente de la bondad de los métodos de previsión de viento. Por último se ha estudiado la influencia de la disminución de los desvíos generados sobre una red tipo de 30 nudos, obteniendo como resultado, que si bien no disminuyen sensiblemente los extra costes generados en regulación, sí que mejora la penetración de las energías renovables no despachables en la red. Se observa disminuyen los vertidos eólicos cuando se usa la planta de hidrógeno. ABSTRACT The aim of this thesis is to study the benefit of hydrogen energy storage to minimize energy deviations of Wind Power and Solar Photovoltaic (PV) Power Plants compared to its forecast. To achieve this goal, first of all we have started with hourly energy data provided 24 h in advance (scheduled energy), and real generation (measured energy). Secondly, It has been sized the hydrogen plant, from a modeling of its working mode, always keeping the goal in mind of limiting energy imbalances. Subsequently, It have been simulated the plant working mode following two goals, one, to limit energy imbalances and secondly to operate the plant as a pumping power plant, generating hydrogen-in valley hours and generating electricity at peak hours. The two simulations have been applied to three wind power plants with different installed power capacities, and a photovoltaic solar power plant. It has been done an economic analysis in order to determine the viability of this sized plants, turning out not viable plants today with the estimated prices considered, requiring significantly lower costs, depending heavily on the reliability of the Wind Power forecast methods. Finally, It has been studied the influence of decreasing measured imbalances (of energy) in a 30 grid node, resulting that, while it not reduces significantly the extra costs generated by reserve power, it does improve the penetration of non-manageable renewable energy on the grid, by reducing the curtailments of power of these plants.

Developing Autonomous Microgrids: A Theoretical Case Study

Microgrids are autonomously operated, geographically clustered electricity generation and distribution systems that supply power in closed system settings; they are highly compatible with renewable energy sources and distributed generation technologies. Mocrogrids are currently a serially underutilized and underappreciated commodity in the energy infrastructure portfolio worldwide. To demonstrate feasibility under poor conditions (little renewable energy potential and high demand) this capstone project develops a theoretical case study in which a renewable microgrid is employed to power rural communities of southern Montgomery County, Arkansas. Utilizing commercially manufactured 1.5-megawatt wind turbines and a 1-megawatt solar panel generation system, 4-megawatts of lithium ion battery storage, and demand response technology, a microgrid is designed that supplies 235 households with reliable electricity supply.

Sustainable Energy Plan for a Small Island Economy: St. Vincent & the Grenadines

This paper defines a sustainable energy plan to provide the basis for renewable energy initiatives that will increase energy security, reduce negative economic impacts and provide a cleaner environment. The hotel, agriculture, transportation, construction, utility, government and private sectors will play pivotal roles in achieving targets and will see significant gains. Government policies, educational campaigns and financial incentives will be required to facilitate and encourage renewable energy development and entrepreneurship. Utilization of solar energy, energy conservation measures and the use of efficient and alternative fuel vehicles by the commercial/industrial and private sectors will be crucial in meeting targets. The utility company will be charged with developing large scale renewable energy applications and with improving efficiency of the electrical system.

Photovoltaics information user study /

"October 1980."

A competitive assessment of the renewable energy equipment industry /

Item 231-B-1

Illinois solar weather program /

"March 1983."

A multi-modular second life hybrid battery energy storage system for utility grid applications

The modern grid system or the smart grid is likely to be populated with multiple distributed energy sources, e.g. wind power, PV power, Plug-in Electric Vehicle (PEV). It will also include a variety of linear and nonlinear loads. The intermittent nature of renewable energies like PV, wind turbine and increased penetration of Electric Vehicle (EV) makes the stable operation of utility grid system challenging. In order to ensure a stable operation of the utility grid system and to support smart grid functionalities such as, fault ride-through, frequency response, reactive power support, and mitigation of power quality issues, an energy storage system (ESS) could play an important role. A fast acting bidirectional energy storage system which can rapidly provide and absorb power and/or VARs for a sufficient time is a potentially valuable tool to support this functionality. Battery energy storage systems (BESS) are one of a range suitable energy storage system because it can provide and absorb power for sufficient time as well as able to respond reasonably fast. Conventional BESS already exist on the grid system are made up primarily of new batteries. The cost of these batteries can be high which makes most BESS an expensive solution. In order to assist moving towards a low carbon economy and to reduce battery cost this work aims to research the opportunities for the re-use of batteries after their primary use in low and ultra-low carbon vehicles (EV/HEV) on the electricity grid system. This research aims to develop a new generation of second life battery energy storage systems (SLBESS) which could interface to the low/medium voltage network to provide necessary grid support in a reliable and in cost-effective manner. The reliability/performance of these batteries is not clear, but is almost certainly worse than a new battery. Manufacturers indicate that a mixture of gradual degradation and sudden failure are both possible and failure mechanisms are likely to be related to how hard the batteries were driven inside the vehicle. There are several figures from a number of sources including the DECC (Department of Energy and Climate Control) and Arup and Cenex reports indicate anything from 70,000 to 2.6 million electric and hybrid vehicles on the road by 2020. Once the vehicle battery has degraded to around 70-80% of its capacity it is considered to be at the end of its first life application. This leaves capacity available for a second life at a much cheaper cost than a new BESS Assuming a battery capability of around 5-18kWhr (MHEV 5kWh - BEV 18kWh battery) and approximate 10 year life span, this equates to a projection of battery storage capability available for second life of >1GWhrs by 2025. Moreover, each vehicle manufacturer has different specifications for battery chemistry, number and arrangement of battery cells, capacity, voltage, size etc. To enable research and investment in this area and to maximize the remaining life of these batteries, one of the design challenges is to combine these hybrid batteries into a grid-tie converter where their different performance characteristics, and parameter variation can be catered for and a hot swapping mechanism is available so that as a battery ends it second life, it can be replaced without affecting the overall system operation. This integration of either single types of batteries with vastly different performance capability or a hybrid battery system to a grid-tie 3 energy storage system is different to currently existing work on battery energy storage systems (BESS) which deals with a single type of battery with common characteristics. This thesis addresses and solves the power electronic design challenges in integrating second life hybrid batteries into a grid-tie energy storage unit for the first time. This study details a suitable multi-modular power electronic converter and its various switching strategies which can integrate widely different batteries to a grid-tie inverter irrespective of their characteristics, voltage levels and reliability. The proposed converter provides a high efficiency, enhanced control flexibility and has the capability to operate in different operational modes from the input to output. Designing an appropriate control system for this kind of hybrid battery storage system is also important because of the variation of battery types, differences in characteristics and different levels of degradations. This thesis proposes a generalised distributed power sharing strategy based on weighting function aims to optimally use a set of hybrid batteries according to their relative characteristics while providing the necessary grid support by distributing the power between the batteries. The strategy is adaptive in nature and varies as the individual battery characteristics change in real time as a result of degradation for example. A suitable bidirectional distributed control strategy or a module independent control technique has been developed corresponding to each mode of operation of the proposed modular converter. Stability is an important consideration in control of all power converters and as such this thesis investigates the control stability of the multi-modular converter in detailed. Many controllers use PI/PID based techniques with fixed control parameters. However, this is not found to be suitable from a stability point-of-view. Issues of control stability using this controller type under one of the operating modes has led to the development of an alternative adaptive and nonlinear Lyapunov based control for the modular power converter. Finally, a detailed simulation and experimental validation of the proposed power converter operation, power sharing strategy, proposed control structures and control stability issue have been undertaken using a grid connected laboratory based multi-modular hybrid battery energy storage system prototype. The experimental validation has demonstrated the feasibility of this new energy storage system operation for use in future grid applications.

A new sensorless speed control scheme for doubly-fed reluctance generators

This paper presents the development and experimental validation of a novel angular velocity observer-based field-oriented control algorithm for a promising low-cost brushless doubly fed reluctance generator (BDFRG) in wind power applications. The BDFRG has been receiving increasing attention because of the use of partially rated power electronics, the high reliability of brushless design, and competitive performance to its popular slip-ring counterpart, the doubly fed induction generator. The controller viability has been demonstrated on a BDFRG laboratory test facility for emulation of variable speed and loading conditions of wind turbines or pump drives.