Komponentenbasierte dynamische Modellierung von Energiesystemen und Energiemanagement-Strategien für ein intelligentes Stromnetz im Heimbereich

The motivation of this work is to present an energy cost reduction concept in a home area power network (HAPN) with intelligent generation and flexible load demands. This study endeavors to address the energy management system (EMS) and layout-design challenges faced by HAPN through a systematic design approach. The growing demand for electricity has become a significant burden on traditional power networks, prompting power engineers to seek ways to improve their efficiency. One such solution is to integrate dispersed generation sources, such as photovoltaic (PV) and storage systems, with an appropriate control mechanism at the distribution level. In recent years, there has been a significant increase in interest in the installation of PV-Battery systems, due to their potential to reduce carbon emissions and lower energy costs. This research proposes an optimal economic power dispatch strategy using Model Predictive Control (MPC) to enhance the overall performance of HAPN. A hybrid AC/DC microgrid concept is proposed to address the control choices made by the appliance scheduling and hybrid switching approaches based on a linear programming optimization framework. The suggested optimization criteria improve consumer satisfaction, minimize grid disconnections, and lower overall energy costs by deploying inexpensive clean energy generation and control. Various examples from actual case study demonstrate the use of the established EMS and design methodology.Die Motivation dieser Arbeit besteht darin, ein Konzept zur Senkung der Energiekosten in einem Heimnetzwerk (HAPN) mit intelligenter Erzeugung und exiblen Lastanforderungen vorzustellen. Im Rahmen dieser Forschungsarbeit wird ein Entwurf für ein HAPN entwickelt, indem das Energiemanagementsystem (EMS) und der Entwurf des Layouts auf der Grundlage des Systemmodells und der betrieblichen Anforderungen gelöst werden. Die steigende Nachfrage nach Elektrizität ist für traditionelle Stromnetze kostspielig und infrastrukturintensiv. Daher konzentrieren sich Energietechniker darauf, die Effizienz der derzeitigen Netze zu erhöhen. Dies kann durch die Integration verteilter Erzeugungsanlagen (z. B. Photovoltaik (PV), Speicher) mit einem geeigneten Kontrollmechanismus für das Energiemanagement auf der Verteilungsseite erreicht werden. Darüber hinaus hat das Interesse an der Installation von PV-Batterie-basierten Systemen aufgrund der Reduzierung der CO2-Emissionen und der Senkung der Energiekosten erheblich zugenommen. Es wird eine optimale wirtschaftliche Strategie für den Energieeinsatz unter Verwendung einer modellprädiktiven Steuerung (MPC) entwickelt. Es wird zudem ein hybrides AC/DC-Microgrid-Konzept vorgeschlagen, um die Steuerungsentscheidungen, die von den Ansätzen der Geräteplanung und der hybriden Umschaltung getroffen werden, auf der Grundlage eines linearen Programmierungsoptimierungsrahmens zu berücksichtigen. Die vorgeschlagenen Optimierungskriterien verbessern die Zufriedenheit der Verbraucher, minimieren Netzabschaltungen und senken die Gesamtenergiekosten durch den Einsatz von kostengünstiger und sauberer Energieerzeugung. Verschiedene Beispiele aus einer Fallstudie demonstrieren den Einsatz des entwickelten EMS und der Entwurfsmethodik

Dynamic Hardware Resource Management for Efficient Throughput Processing.

High performance computing is evolving at a rapid pace, with throughput oriented processors such as graphics processing units (GPUs), substituting for traditional processors as the computational workhorse. Their adoption has seen a tremendous increase as they provide high peak performance and energy efficiency while maintaining a friendly programming interface. Furthermore, many existing desktop, laptop, tablet, and smartphone systems support accelerating non-graphics, data parallel workloads on their GPUs. However, the multitude of systems that use GPUs as an accelerator run different genres of data parallel applications, which have significantly contrasting runtime characteristics. GPUs use thousands of identical threads to efficiently exploit the on-chip hardware resources. Therefore, if one thread uses a resource (compute, bandwidth, data cache) more heavily, there will be significant contention for that resource. This contention will eventually saturate the performance of the GPU due to contention for the bottleneck resource,leaving other resources underutilized at the same time. Traditional policies of managing the massive hardware resources work adequately, on well designed traditional scientific style applications. However, these static policies, which are oblivious to the application’s resource requirement, are not efficient for the large spectrum of data parallel workloads with varying resource requirements. Therefore, several standard hardware policies such as using maximum concurrency, fixed operational frequency and round-robin style scheduling are not efficient for modern GPU applications. This thesis defines dynamic hardware resource management mechanisms which improve the efficiency of the GPU by regulating the hardware resources at runtime. The first step in successfully achieving this goal is to make the hardware aware of the application’s characteristics at runtime through novel counters and indicators. After this detection, dynamic hardware modulation provides opportunities for increased performance, improved energy consumption, or both, leading to efficient execution. The key mechanisms for modulating the hardware at runtime are dynamic frequency regulation, managing the amount of concurrency, managing the order of execution among different threads and increasing cache utilization. The resultant increased efficiency will lead to improved energy consumption of the systems that utilize GPUs while maintaining or improving their performance.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113356/1/asethia_1.pd

Scalable, Data- intensive Network Computation

To enable groups of collaborating researchers at different locations to effectively share large datasets and investigate their spontaneous hypotheses on the fly, we are interested in de- veloping a distributed system that can be easily leveraged by a variety of data intensive applications. The system is composed of (i) a number of best effort logistical depots to en- able large-scale data sharing and in-network data processing, (ii) a set of end-to-end tools to effectively aggregate, manage and schedule a large number of network computations with attendant data movements, and (iii) a Distributed Hash Table (DHT) on top of the generic depot services for scalable data management. The logistical depot is extended by following the end-to-end principles and is modeled with a closed queuing network model. Its performance characteristics are studied by solving the steady state distributions of the model using local balance equations. The modeling results confirm that the wide area network is the performance bottleneck and running concurrent jobs can increase resource utilization and system throughput. As a novel contribution, techniques to effectively support resource demanding data- intensive applications using the ¯ne-grained depot services are developed. These techniques include instruction level scheduling of operations, dynamic co-scheduling of computation and replication, and adaptive workload control. Experiments in volume visualization have proved the effectiveness of these techniques. Due to the unique characteristic of data- intensive applications and our co-scheduling algorithm, a DHT is implemented on top of the basic storage and computation services. It demonstrates the potential of the Logistical Networking infrastructure to serve as a service creation platform

LTE Optimization and Resource Management in Wireless Heterogeneous Networks

Mobile communication technology is evolving with a great pace. The development of the Long Term Evolution (LTE) mobile system by 3GPP is one of the milestones in this direction. This work highlights a few areas in the LTE radio access network where the proposed innovative mechanisms can substantially improve overall LTE system performance. In order to further extend the capacity of LTE networks, an integration with the non-3GPP networks (e.g., WLAN, WiMAX etc.) is also proposed in this work. Moreover, it is discussed how bandwidth resources should be managed in such heterogeneous networks. The work has purposed a comprehensive system architecture as an overlay of the 3GPP defined SAE architecture, effective resource management mechanisms as well as a Linear Programming based analytical solution for the optimal network resource allocation problem. In addition, alternative computationally efficient heuristic based algorithms have also been designed to achieve near-optimal performance

Resource management research in ethernet passive optical networks

The last decades, we have witnessed different phenomenology in the telecommunications sector. One of them is the widespread use of the Internet, which has brought a sharp increase in traffic, forcing suppliers to continuously expand the capacity of networks. In the near future, Internet will be composed of long-range highspeed optical networks; a number of wireless networks at the edge; and, in between, several access technologies. Today one of the main problems of the Internet is the bottleneck in the access segment. To address this issue the Passive Optical Networks (PONs) are very likely to succeed, due to their simplicity, low-cost, and increased bandwidth. A PON is made up of fiber optic cabling and passive splitters and couplers that distribute an optical signal to connectors that terminate each fiber segment. Among the different PON technologies, the Ethernet-PON (EPON) is a great alternative to satisfy operator and user needs, due to its cost, flexibility and interoperability with other technologies. One of the most interesting challenges in such technologies relates to the scheduling and allocation of resources in the upstream (shared) channel, i.e., the resource management. The aim of this thesis is to study and evaluate current contributions and propose new efficient solutions to address the resource management issues mainly in EPON. Key issues in this context are future end-user needs, quality of service (QoS) support, energy-saving and optimized service provisioning for real-time and elastic flows. This thesis also identifies research opportunities, issue recommendations and proposes novel mechanisms associated with access networks based on optical fiber technologies.Postprint (published version

NASA/NBS (National Aeronautics and Space Administration/National Bureau of Standards) standard reference model for telerobot control system architecture (NASREM)

The document describes the NASA Standard Reference Model (NASREM) Architecture for the Space Station Telerobot Control System. It defines the functional requirements and high level specifications of the control system for the NASA space Station document for the functional specification, and a guideline for the development of the control system architecture, of the 10C Flight Telerobot Servicer. The NASREM telerobot control system architecture defines a set of standard modules and interfaces which facilitates software design, development, validation, and test, and make possible the integration of telerobotics software from a wide variety of sources. Standard interfaces also provide the software hooks necessary to incrementally upgrade future Flight Telerobot Systems as new capabilities develop in computer science, robotics, and autonomous system control

Curracurrong: a stream processing system for distributed environments

Advances in technology have given rise to applications that are deployed on wireless sensor networks (WSNs), the cloud, and the Internet of things. There are many emerging applications, some of which include sensor-based monitoring, web traffic processing, and network monitoring. These applications collect large amount of data as an unbounded sequence of events and process them to generate a new sequences of events. Such applications need an adequate programming model that can process large amount of data with minimal latency; for this purpose, stream programming, among other paradigms, is ideal. However, stream programming needs to be adapted to meet the challenges inherent in running it in distributed environments. These challenges include the need for modern domain specific language (DSL), the placement of computations in the network to minimise energy costs, and timeliness in real-time applications. To overcome these challenges we developed a stream programming model that achieves easy-to-use programming interface, energy-efficient actor placement, and timeliness. This thesis presents Curracurrong, a stream data processing system for distributed environments. In Curracurrong, a query is represented as a stream graph of stream operators and communication channels. Curracurrong provides an extensible stream operator library and adapts to a wide range of applications. It uses an energy-efficient placement algorithm that optimises communication and computation. We extend the placement problem to support dynamically changing networks, and develop a dynamic program with polynomially bounded runtime to solve the placement problem. In many stream-based applications, real-time data processing is essential. We propose an approach that measures time delays in stream query processing; this model measures the total computational time from input to output of a query, i.e., end-to-end delay