Effect of market-driven minigrids on the frequency stabilization process of isolated middle-sized power grids

Neueste Entwicklungen in Technologien für dezentrale Energieversorgungsstrukturen, erneuerbare Energien, Großhandelsenergiemarkt, Mini- und Mikronetze, verteilte Intelligenz, sowie Informations- und Datenübertragungstechnologien werden die zukünftige Energiewelt maßgeblich bestimmen. Die derzeitigen Forschungsbemühungen zur Vernutzung aller dieser Technologien bilden die Voraussetzungen für ein zukünftiges, intelligentes Stromnetz. Dieses neue Konzept gründet sich auf die folgenden Säulen: Die Versorgung erfolgt durch dezentrale Erzeugungsanlagen und nicht mehr durch große zentrale Erzeuger; die Steuerung beeinflusst nicht mehr allein die Versorgung sondern ermöglich eine auch aktive Führung des Bedarf; die Eingabeparameter des Systems sind nicht mehr nur mechanische oder elektrische Kenngrößen sondern auch Preissignale; die erneuerbaren Energieträger sind nicht mehr nur angeschlossen, sondern voll ins Energienetz integriert. Die vorgelegte Arbeit fügt sich in dieses neue Konzept des intelligenten Stromnetz ein. Da das zukünftige Stromnetz dezentral konfiguriert sein wird, ist eine Übergangsphase notwendig. Dieser Übergang benötigt Technologien, die alle diese neue Konzepte in die derzeitigen Stromnetze integrieren können. Diese Arbeit beweist, dass ein Mininetz in einem Netzabschnitt mittlerer Größe als netzschützende Element wirken kann. Hierfür wurde ein neues Energiemanagementsystem für Mininetze – das CMS (englisch: Cluster Management System) – entwickelt. Diese CMS funktioniert als eine von ökonomischorientierte Betriebsoptimierung und wirkt wie eine intelligente Last auf das System ein, reagierend auf Preissignale. Sobald wird durch eine Frequenzsenkung eine Überlastung des Systems bemerkt, ändert das Mininetz sein Verhalten und regelt seine Belastung, um die Stabilisierung des Hauptnetzes zu unterstützen. Die Wirksamkeit und die Realisierbarkeit des einwickelten Konzept wurde mit Hilfe von Simulationen und erfolgreichen Laborversuchen bewiesen.

Genetic Programming meets Model-Driven Development

Genetic programming is known to provide good solutions for many problems like the evolution of network protocols and distributed algorithms. In such cases it is most likely a hardwired module of a design framework that assists the engineer to optimize specific aspects of the system to be developed. It provides its results in a fixed format through an internal interface. In this paper we show how the utility of genetic programming can be increased remarkably by isolating it as a component and integrating it into the model-driven software development process. Our genetic programming framework produces XMI-encoded UML models that can easily be loaded into widely available modeling tools which in turn posses code generation as well as additional analysis and test capabilities. We use the evolution of a distributed election algorithm as an example to illustrate how genetic programming can be combined with model-driven development. This example clearly illustrates the advantages of our approach – the generation of source code in different programming languages.

An Inquiry of Changes in Environmental Governance by Community-driven Process

Urban environmental depletion has been a critical problem among industrialized-transformed societies, especially at the local level where administrative authorities’ capacity lags behind changes. Derived from governance concept, the idea of civil society inclusion is highlighted. Focusing on an agglomerated case study, Bang Plee Community in Thailand, this research investigates on a non-state sector, 201-Community organization, as an agent for changes to improve urban environments on solid waste collection. Two roles are contested: as an agent for neighborhood internal change and as an intermediary toward governance changes in state-civil society interaction. By employing longitudinal analysis via a project intervention as research experiment, the outcomes of both roles are detected portrayed in three spheres: state, state-civil society interaction, and civil society sphere. It discovers in the research regarding agglomerated context that as an internal changes for environmental betterment, 201-Community organization operation brings on waste reduction at the minimal level. Community-based organization as an agent for changes – despite capacity input it still limited in efficiency and effectiveness – can mobilize fruitfully only at the individual and network level of civil society sectors, while fails managing at the organizational level. The positive outcomes result by economic waste incentive associated with a limited-bonded group rather than the rise of awareness at large. As an intermediary agent for shared governance, the community-based organization cannot bring on mutual dialogue with state as much as cannot change the state’s operation arena of solid waste management. The findings confine the shared governance concept that it does not applicable in agglomerated locality as an effective outcome, both in terms of being instrumental toward civil society inclusion and being provocative of internal change. Shared environmental governance as summarized in this research can last merely a community development action. It distances significantly from civil society inclusion and empowerment. However, the research proposes that community-based environmental management and shared governance toward civil society inclusion in urban environmental improvement are still an expectable option and reachable if their factors and conditions of key success and failure are intersected with a particular context. Further studies demand more precise on scale, scope, and theses factors of environmental management operation operated by civil society sectors.

Fehlersuche im Modell - Modellbasiertes Testen und Debuggen

Kern der vorliegenden Arbeit ist die Erforschung von Methoden, Techniken und Werkzeugen zur Fehlersuche in modellbasierten Softwareentwicklungsprozessen. Hierzu wird zuerst ein von mir mitentwickelter, neuartiger und modellbasierter Softwareentwicklungsprozess, der sogenannte Fujaba Process, vorgestellt. Dieser Prozess wird von Usecase Szenarien getrieben, die durch spezielle Kollaborationsdiagramme formalisiert werden. Auch die weiteren Artefakte des Prozess bishin zur fertigen Applikation werden durch UML Diagrammarten modelliert. Es ist keine Programmierung im Quelltext nötig. Werkzeugunterstützung für den vorgestellte Prozess wird von dem Fujaba CASE Tool bereitgestellt. Große Teile der Werkzeugunterstützung für den Fujaba Process, darunter die Toolunterstützung für das Testen und Debuggen, wurden im Rahmen dieser Arbeit entwickelt. Im ersten Teil der Arbeit wird der Fujaba Process im Detail erklärt und unsere Erfahrungen mit dem Einsatz des Prozesses in Industrieprojekten sowie in der Lehre dargestellt. Der zweite Teil beschreibt die im Rahmen dieser Arbeit entwickelte Testgenerierung, die zu einem wichtigen Teil des Fujaba Process geworden ist. Hierbei werden aus den formalisierten Usecase Szenarien ausführbare Testfälle generiert. Es wird das zugrunde liegende Konzept, die konkrete technische Umsetzung und die Erfahrungen aus der Praxis mit der entwickelten Testgenerierung dargestellt. Der letzte Teil beschäftigt sich mit dem Debuggen im Fujaba Process. Es werden verschiedene im Rahmen dieser Arbeit entwickelte Konzepte und Techniken vorgestellt, die die Fehlersuche während der Applikationsentwicklung vereinfachen. Hierbei wurde darauf geachtet, dass das Debuggen, wie alle anderen Schritte im Fujaba Process, ausschließlich auf Modellebene passiert. Unter anderem werden Techniken zur schrittweisen Ausführung von Modellen, ein Objekt Browser und ein Debugger, der die rückwärtige Ausführung von Programmen erlaubt (back-in-time debugging), vorgestellt. Alle beschriebenen Konzepte wurden in dieser Arbeit als Plugins für die Eclipse Version von Fujaba, Fujaba4Eclipse, implementiert und erprobt. Bei der Implementierung der Plugins wurde auf eine enge Integration mit Fujaba zum einen und mit Eclipse auf der anderen Seite geachtet. Zusammenfassend wird also ein Entwicklungsprozess vorgestellt, die Möglichkeit in diesem mit automatischen Tests Fehler zu identifizieren und diese Fehler dann mittels spezieller Debuggingtechniken im Programm zu lokalisieren und schließlich zu beheben. Dabei läuft der komplette Prozess auf Modellebene ab. Für die Test- und Debuggingtechniken wurden in dieser Arbeit Plugins für Fujaba4Eclipse entwickelt, die den Entwickler bestmöglich bei der zugehörigen Tätigkeit unterstützen.

Electron-Nuclear Correlation in Laser-Driven Diatomic Molecules

The interaction of short intense laser pulses with atoms/molecules produces a multitude of highly nonlinear processes requiring a non-perturbative treatment. Detailed study of these highly nonlinear processes by numerically solving the time-dependent Schrodinger equation becomes a daunting task when the number of degrees of freedom is large. Also the coupling between the electronic and nuclear degrees of freedom further aggravates the computational problems. In the present work we show that the time-dependent Hartree (TDH) approximation, which neglects the correlation effects, gives unreliable description of the system dynamics both in the absence and presence of an external field. A theoretical framework is required that treats the electrons and nuclei on equal footing and fully quantum mechanically. To address this issue we discuss two approaches, namely the multicomponent density functional theory (MCDFT) and the multiconfiguration time-dependent Hartree (MCTDH) method, that go beyond the TDH approximation and describe the correlated electron-nuclear dynamics accurately. In the MCDFT framework, where the time-dependent electronic and nuclear densities are the basic variables, we discuss an algorithm to calculate the exact Kohn-Sham (KS) potentials for small model systems. By simulating the photodissociation process in a model hydrogen molecular ion, we show that the exact KS potentials contain all the many-body effects and give an insight into the system dynamics. In the MCTDH approach, the wave function is expanded as a sum of products of single-particle functions (SPFs). The MCTDH method is able to describe the electron-nuclear correlation effects as the SPFs and the expansion coefficients evolve in time and give an accurate description of the system dynamics. We show that the MCTDH method is suitable to study a variety of processes such as the fragmentation of molecules, high-order harmonic generation, the two-center interference effect, and the lochfrass effect. We discuss these phenomena in a model hydrogen molecular ion and a model hydrogen molecule. Inclusion of absorbing boundaries in the mean-field approximation and its consequences are discussed using the model hydrogen molecular ion. To this end, two types of calculations are considered: (i) a variational approach with a complex absorbing potential included in the full many-particle Hamiltonian and (ii) an approach in the spirit of time-dependent density functional theory (TDDFT), including complex absorbing potentials in the single-particle equations. It is elucidated that for small grids the TDDFT approach is superior to the variational approach.

From evolution to co-evolution – An empirical study of the role of innovation, policy and public research in industrial dynamics

In the past decades since Schumpeter’s influential writings economists have pursued research to examine the role of innovation in certain industries on firm as well as on industry level. Researchers describe innovations as the main trigger of industry dynamics, while policy makers argue that research and education are directly linked to economic growth and welfare. Thus, research and education are an important objective of public policy. Firms and public research are regarded as the main actors which are relevant for the creation of new knowledge. This knowledge is finally brought to the market through innovations. What is more, policy makers support innovations. Both actors, i.e. policy makers and researchers, agree that innovation plays a central role but researchers still neglect the role that public policy plays in the field of industrial dynamics. Therefore, the main objective of this work is to learn more about the interdependencies of innovation, policy and public research in industrial dynamics. The overarching research question of this dissertation asks whether it is possible to analyze patterns of industry evolution – from evolution to co-evolution – based on empirical studies of the role of innovation, policy and public research in industrial dynamics. This work starts with a hypothesis-based investigation of traditional approaches of industrial dynamics. Namely, the testing of a basic assumption of the core models of industrial dynamics and the analysis of the evolutionary patterns – though with an industry which is driven by public policy as example. Subsequently it moves to a more explorative approach, investigating co-evolutionary processes. The underlying questions of the research include the following: Do large firms have an advantage because of their size which is attributable to cost spreading? Do firms that plan to grow have more innovations? What role does public policy play for the evolutionary patterns of an industry? Are the same evolutionary patterns observable as those described in the ILC theories? And is it possible to observe regional co-evolutionary processes of science, innovation and industry evolution? Based on two different empirical contexts – namely the laser and the photovoltaic industry – this dissertation tries to answer these questions and combines an evolutionary approach with a co-evolutionary approach. The first chapter starts with an introduction of the topic and the fields this dissertation is based on. The second chapter provides a new test of the Cohen and Klepper (1996) model of cost spreading, which explains the relationship between innovation, firm size and R&D, at the example of the photovoltaic industry in Germany. First, it is analyzed whether the cost spreading mechanism serves as an explanation for size advantages in this industry. This is related to the assumption that the incentives to invest in R&D increase with the ex-ante output. Furthermore, it is investigated whether firms that plan to grow will have more innovative activities. The results indicate that cost spreading serves as an explanation for size advantages in this industry and, furthermore, growth plans lead to higher amount of innovative activities. What is more, the role public policy plays for industry evolution is not finally analyzed in the field of industrial dynamics. In the case of Germany, the introduction of demand inducing policy instruments stimulated market and industry growth. While this policy immediately accelerated market volume, the effect on industry evolution is more ambiguous. Thus, chapter three analyzes this relationship by considering a model of industry evolution, where demand-inducing policies will be discussed as a possible trigger of development. The findings suggest that these instruments can take the same effect as a technical advance to foster the growth of an industry and its shakeout. The fourth chapter explores the regional co-evolution of firm population size, private-sector patenting and public research in the empirical context of German laser research and manufacturing over more than 40 years from the emergence of the industry to the mid-2000s. The qualitative as well as quantitative evidence is suggestive of a co-evolutionary process of mutual interdependence rather than a unidirectional effect of public research on private-sector activities. Chapter five concludes with a summary, the contribution of this work as well as the implications and an outlook of further possible research.