Publikationen

Abstract: The concept of cellular energy systems of the German Association for Electrical, Electronic and Information Technologies (VDE) proposes sector coupled energy networks for energy transition based on cellular structures. Its decentralized control approach radically differs from that of existing networks. Deeply integrated information and communications technologies (ICT) open opportunities for increased resilience and optimizations. The exploration of this concept requires a comprehensive simulation tool. In this paper, we investigate simulation techniques for cellular energy systems and present a concept based on co-simulation. We combine simulation tools developed for different domains. A classical tool for studying physical aspects of energy systems (Modelica, TransiEnt library) is fused with a state-of-the-art communication networks simulator (OMNeT++) via the standardized functional mock-up interface (FMI). New components, such as cell managers, aggregators, and markets, are integrated via remote procedure calls. A special feature of our concept is that the communication simulator coordinates the co-simulation as a master and integrates other components via a proxy concept. Model consistency across different domains is achieved by a common description of the energy system. Evaluation proves the feasibility of the concept and shows simulation speeds about 20 times faster than real time for a cell with 111 households.

Abstract: The intermittent energy supply from distributed resources and the coupling of different energy and application sectors play an important role for future energy systems. Novel operational concepts require the use of widespread and reliable Information and Communication Technology (ICT). This paper presents the approach of a research project that focuses on the development of an innovative operational concept for a Smart Integrated Energy System (SIES), which consists of a physical architecture, ICT and energy management strategies. The cellular approach provides the architecture of the physical system in combination with Transactive Control (TC) as the system’s energy management framework. Independent dynamic models for each component, the physical and digital system, operational management and market are suggested and combined in a newly introduced co-simulation platform to create a holistic model of the integrated energy system. To verify the effectiveness of the operational concept, energy system scenarios are derived and evaluation criteria are suggested which can be employed to evaluate the future system operations.

Abstract: The paper proposes a demand response scheme controlling many domestic electric water heaters (DEWHs) with a price function to consume electric power according to a target schedule. It discusses at length the design of an algorithm to calculate the price function from a target schedule. The price function is used by the control of each DEWH to automatically and optimally minimize its local heating costs. It is demonstrated that the resulting total power consumption approximates the target schedule. The algorithm was successfully validated by simulation with a realistic set of 50 DEWHs assuming perfect knowledge of parameters and water consumption. It is shown that the algorithm is also applicable to clusters of large numbers of DEWHs with statistical knowledge only. However, this leads to a slightly higher deviation from the target schedule.

Abstract: A well-known mechanism for demand response is sending price signals to customers a day ahead. Customers then postpone or advance their usage of electricity to minimize cost. Setting up price functions that adapt the customers' load to availability is a big challenge. This paper investigates the feasibility of finding day-ahead price functions to induce a desired load profile of Domestic Electric Water Heaters (DEWHs) minimizing their electricity cost for demand response. Bilevel optimization is applied for a single DEWH using a simplified linear model and full knowledge. This leads to a solvable bilevel problem and allows understanding optimality of price functions and resulting heating profiles. It is shown that with the resulting price functions the DEWH may select many significantly different heating profiles leading to the same cost. Thus the price does not uniquely induce the desired heating profile. The acquired knowledge forms the basis for a procedure to create price functions for controlling the load profile of many DEWHs.

Abstract: This paper analyzes the impact of the high dimen- sional parameter space of domestic electric water heaters (DEWH) for demand response (DR). To quantify the con- sumer comfort a novel metric is introduced considering a stochastic distribution of different water draw events. Incor- porating three control algorithms from literature, it is shown that all considered parameters of a DEWH except the heat conductivity have a significant impact on consumer satisfac- tion. The effect on DR is mainly influenced by the temper- ature range and the planning horizon, but also by the heat conductivity and the volume. In contrast, the rated power of the heating element and the nominal temperature have no significant impact on the effect on DR. The impacts are an- alyzed by varying these parameters in a simulation of 1000 DEWHs considering three different controllers: a common thermostat, an exchange price dependent nominal temper- ature changing mechanism and an energy scheduling algo- rithm proposed by Du and Lu.

Abstract: Indoor Positioning Systems (IPS) gained importance in many industrial applications. State-of-the-art solutions heavily rely on external infrastructures and are subject to potential privacy compromises, external information requirements, and assumptions, that make it unfavorable for environments demanding privacy and prolonged functionality. In certain environments deploying supplementary infrastructures for indoor positioning could be infeasible and expensive. Recent developments in machine learning (ML) offer solutions to address these limitations relying only on the data from onboard sensors of IoT devices. However, it is unclear which model fits best considering the resource constraints of IoT devices. This paper presents a machine learning-based indoor positioning system, using motion and ambient sensors, to localize a moving entity in privacy concerned factory environments. The problem is formulated as a multivariate time series classification (MTSC) and a comparative analysis of different machine learning models is conducted in order to address it. We introduce a novel time series dataset emulating the assembly lines of a factory. This dataset is utilized to assess and compare the selected models in terms of accuracy, memory footprint and inference speed. The results illustrate that all evaluated models can achieve accuracies above 80 %. CNN-1D shows the most balanced performance, followed by MLP. DT was found to have the lowest memory footprint and inference latency, indicating its potential for a deployment in real-world scenarios.

Abstract: The paper analyzes the behavior of two demand response algorithms, both claiming to minimize the energy cost regarding time-varying prices in an optimal way by iteratively scheduling heating phases of water heaters considering hot water consumption. Four issues of the well known algorithm by Du and Lu are identified, which lead to suboptimal behavior. Proposed enhancements lead to an algorithm similar to the second, recently published, method of Shah et al. The effect of each enhancement and its combinations are analysed simulatively reducing the costs.

Abstract: This paper quantitatively compares five demand response (DR) approaches for waterbeds using simulation. The approaches enable privacy by design with a local control and contribute to the planning phase of the electricity network’s balancing process. Approaches are assessed by their energy consumption, their ability to shift power consumption to times of high availability, and the effort of realization and configuration. Load steps were identified as a risk for power network stability. A classification of DR methods, based on the position of their contribution within the electricity network’s balancing process, is used to distinguish our approach from the DR approaches found in the literature.

Abstract: The paper presents a demand response scheme for waterbeds that can be implemented in practice today. It balances the requirements of saving energy and shifting power to times with higher power availability by planning heating phases to minimize costs according to a virtual electricity tariff derived from trading prices of an electricity exchange. The approach was successfully validated with a real waterbed under real conditions.

Abstract: After almost two years to recover the flight data recorder of Air France Flight 447 and, by January 2015, still no sign of Malaysian Airlines Flight 370, the public and media ask the question: "How is it possible to have almost worldwide Internet access in the cabin but not being able to track the position of an aircraft?" One answer to the question is that the passenger pays for Internet access in the cabin while the airline would have to pay for transmission of sensor data, such as the aircraft position. Furthermore Internet access in the cabin is offered on a best effort basis without any guarantees with regard to delay, throughput and loss rate. In this paper we present a simple system capable of transmitting critical data to the ground and evaluate the statistical distribution of the end-to-end delay a transmitted data packet encounters. Signal Flow Graphs are used to systematically model the transmission system with regard to delays encountered by a packet, including those caused by retransmissions of lost data. Results for the Inmarsat-4 Broadband Global Area Network (BGAN) service are derived, but the method is applicable to many other transmission systems.

Abstract: This paper presents the design of a universal energy module for nodes in wireless sensor networks. It supports a wide range of energy harvesters and energy storage systems. The focus is on the efficient conversion and storage of energy and to provide a smart platform for higher level energy management functions. The module provides maximum power point tracking and supports hybrid harvesters.

Abstract: This paper proposes and analyses the idea of replacing professional mobile radio for airport ground handlers by VoIP systems based on WLAN. The proposed communication scheme is adjusted to business processes at airports. It provides push-to-talk unicast and group messages (determined by business tasks or location) with priorities, encrypted transmission, and mailboxes. The resulting architecture and proof-of-concept prototype consists of a server and software clients reusing already installed hardware and WLAN infrastructure, and uses peer-to-peer RDP voice streams. Bandwidth considerations estimate a maximum of 72 concurrent streams per access point on WLAN for IEEE 802.11g (54 Mbit/s) and 13 streams for IEEE 802.11b (11 Mbit/s), enhanced with a factor 3 to 5 if IEEE 802.11e is used as quality of service support.

Abstract: The paper analyses potentials, challenges, and applications of using rewritable, stationary RFID tags for marking routes for autonomous vehicles in manufacturing environments. This approach promises to be flexible, robust, and inexpensive. Two algorithms are proposed also considering additional sensors.

Abstract: The paper investigates the development of systems for vehicle management on airport aprons, using current A-SMGCS experiences, with a focus on fleet management and turn around processes of mid-size airports. An architecture is proposed that is derived from A-SMGCS, reducing cost by only supporting cooperative targets and off-the-shelf hardware. Available candidate technologies for implementing the architecture_s components are discussed, pointing out criteria for selection. Systems for vehicle management on aprons are important, because the continuous reductions of aircraft turn-around times increase the pressure on airports and ground handling companies to optimize infrastructure and resources.

Abstract: Extensive field trials are essential to evaluate protocols and algorithms for wireless sensor networks. The high costs of such trials demand for a systematic approach. This paper discusses the issues of setting up a field trial such as packaging, logging, and deployment. Details about a concrete field trial to evaluate a topology discovery algorithm are presented.

Abstract: The paper presents a generic, high-level Java interface for the vertical integration of wireless sensor networks. The intuitive interfaces are implemented in a framework that is easy to use. The classes of the framework can be extended to meet the requirements of a wide range of applications. In particular, the framework supports sending packets to and receiving packets from nodes of the sensor network. Packet types are represented as Java classes generated from meta-data based on XML Schema. This approach fosters short development cycles and provides the productivity needed in vertical integration applications. The ScatterWeb platform is used as a sample platform for sensor networks.

Abstract: This paper reports on the experience gained during a real-world deployment of a sensor network based on the ESB platform in the heathlands of Northern Germany. The goal of the experiment was to gain a deeper insight into the problems of real deployments as opposed to simulated networks. The focus of this report is on the quality of radio links and the influence of the link quality on multi-hop routing.

Abstract: This paper reports on the experience gained during the implementation and operation of an online assessment system for recruitment of engineering and computer science students. We identified problems that have to be solved to make online assessment a worthwhile building block of university admission. The presented work includes techniques for evaluating and monitoring online assessment processes.

Abstract: The paper compares two approaches for developing Web service interfaces for the vertical integration of TTP/A fieldbus systems. High-level abstractions are provided by application specific interfaces, generated from metadata describing fieldbus systems. In contrast standardised interfaces such as OPC XML DA only allow lower levels of abstractions. But these enable accessing the fieldbus system from a broad range of standard clients, while high-level abstractions reflecting the application programmer's view on the system facilitate the development of more specific clients and workflows.

Abstract: This paper contributes to the interoperability of web services by proposing the flexible specification technique SXQT in conjunction with the automatic validation, a straightforward approach for detecting non-conformance. SXQT allows different levels of abstraction by specifying individual requirements on a web service's protocol, i.e. its SOAP messages and behaviour including SOAP modules. The automatic validation detects non-conformance by comparing occurring message sequences with the protocol's specification.

Abstract: This paper presents a generic technique to expose data and control of fieldbus systems to applications located at the level of operational management. To provide a high degree of interoperability between the operational level and different fieldbus systems we utilize standardized techniques such as XML, HTTP, and Web services which can be deployed independently of the platform. The proposed service is based on the interface file system for TTP/A smart transducers. The defined interface provides high level abstractions appropriate for the integration into business applications and considers the latency introduced by the internet protocols.

Abstract: This paper is concerned with the vertical integration of fieldbus systems. It presents a generic technique to expose data and control of fieldbus systems in a semantically rich way to applications located at the level of operational management. To provide a high degree of interoperability between the operational level and different fieldbus systems we utilize standardized techniques such as XML, HTTP, and Web services which can be deployed independently of the platform. The proposed service is based on the interface file system for TTP/A smart transducers. The defined interface provides high level abstractions appropriate for the integration into business applications and considers the latency introduced by the internet protocols. The operations of the service are automatically generated from meta-data descriptions of the smart transducers and their combination into larger clusters.

Abstract: The thesis solves interoperability issues regarding Web Services. The W3C standard for the specification of their interfaces (WSDL) is made more precise. This is done by developing a specification technique (SXQT), that allows specifying interfaces using expressions of first order logic (in XQuery). Compliance with such specifications is checked with the automatic validation.

Abstract: Indoor Positioning Systems (IPS) gained importance in many industrial applications. State-of-the-art solutions heavily rely on external infrastructures and are subject to potential privacy compromises, external information requirements, and assumptions, that make it unfavorable for environments demanding privacy and prolonged functionality. In certain environments deploying supplementary infrastructures for indoor positioning could be infeasible and expensive. Recent developments in machine learning (ML) offer solutions to address these limitations relying only on the data from onboard sensors of IoT devices. However, it is unclear which model fits best considering the resource constraints of IoT devices. This paper presents a machine learning-based indoor positioning system, using motion and ambient sensors, to localize a moving entity in privacy concerned factory environments. The problem is formulated as a multivariate time series classification (MTSC) and a comparative analysis of different machine learning models is conducted in order to address it. We introduce a novel time series dataset emulating the assembly lines of a factory. This dataset is utilized to assess and compare the selected models in terms of accuracy, memory footprint and inference speed. The results illustrate that all evaluated models can achieve accuracies above 80 %. CNN-1D shows the most balanced performance, followed by MLP. DT was found to have the lowest memory footprint and inference latency, indicating its potential for a deployment in real-world scenarios.

Abstract: In this paper we investigate the usage of machine learning for interpreting measured sensor values in sensor modules. In particular we analyze the potential of artificial neural networks (ANNs) on low-cost microcontrollers with a few kilobytes of memory to semantically enrich data captured by sensors. The focus is on classifying temporal data series with a high level of reliability. Design and implementation of ANNs are analyzed considering Feed Forward Neural Networks (FFNNs) and Recurrent Neural Networks (RNNs). We validate the developed ANNs in a case study of optical hand gesture recognition on an 8-bit microcontroller. The best reliability was found for an FFNN with two layers and 1493 parameters requiring an execution time of 36 ms. We propose a workflow to develop ANNs for embedded devices.

Abstract: Described is a method for transmitting continuously created data items from an aircraft to a receiver. The data items are of a plurality of data types and each have a different priority. For each data type a live LIFO buffer and a main LIFO buffer are provided. In a regular operation mode continuously created data items are continuously stored in the main buffers. In a transmission operation mode continuously created data items are continuously stored in the live buffers, consecutive data packets are transmitted and for each data packet the data is selected from the buffers, wherein data items stored in live buffers are transmitted before data items stored in main buffers and data items of higher priorities are transmitted before data items of lower priorities. Further, a transmitter and an aircraft are described and claimed.

Abstract: This paper presents the design of a universal energy module for wireless sensor nodes, which supports a wide range of energy harvesters and energy storages. The focus is on the efficient conversion and storage of energy and to provide hardware support for higher level management functions. The module facilitates maximum power point tracking to improve the harvester efficiency. By supporting hybrid harvesters, the module can make better use of the time-dependent availability of environmental energy sources.

Abstract: The paper presents an approach of applying DCF77 time radio signals to provide a clock with global time in sensor networks based on TinyOS. Some nodes containing DCF77 receiver hardware reliably decode time signals even if these are distorted to some extent. The clock with global time is provided by compensating clock drift. Time is distributed in the network with a protocol generating timestamps on the MAC layer.