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Efficient, low-cost, secure and reliable communication solutions are a major stepping stone for smart metering and smart grid applications. This especially holds true for the so called primary communication or local metrological network (LMN) between a local meter or actuator and a data collector or gateway, where the highest requirements with regard to cost, bandwidth, and energy efficiency have to be taken into consideration. Multiple developments and field tests are going on in this field, however, energy autarkic devices are hardly found, yet. This contribution describes the development of an automatic water meter reading (AWMR) technology based on Wireless M-Bus to provide water utility companies with an automatic remote water meter reading solution. It addresses the special needs of home utilities by providing a remote metering solution independent from the electricity infrastructure, both in terms of data communication and in terms of power supply. For this project, a cost efficient integrated energy harvesting system powered by the available water flow was developed, to enable operation independently of the mains grid, and eliminate the need for battery replacement for near-zero maintenance costs.
The communication technologies for automatic meter reading (smart metering) and for energy production and distribution networks (smart grid) have the potential to be one of the first really highly scaled machine-to-machine-M2M-applications. During the last years, two very promising developments around the wireless part of the smart grid communication were initialized, which possibly could have an impact on the network architectures and the markets far beyond Germany and far beyond energy automation. Besides the specification of the OMS Group of a security extension to the Wireless M-Bus protocol (EN13757-4), the German Federal Office for Information Security (Bundesamt für Sicherheit in der Informationstechnik, BSI) has designed a Protection Profile (PP) and a Technical Directive (TR) for the communication unit of an intelligent measurement system (Smart Meter Gateway), which were released in March 2013. This design uses state of the art technologies and prescribes their implementation in real-life systems. At first, the proposed paper will present the most important characteristics of this architecture. It will then give an insight into the implementation of the OMS security protocols, which imply the usage of a mutually authenticated SSL protocol also in the Local Metrological Network. This is achieved with the help of an additional Authentication and Fragmentation Layer (AFL). This secure communication will be terminated in a BSI conformant secure smart meter gateway, which is developed in a different project and described in the second step. Finally, the contribution will discuss the integration of such a metering network into an overall telecommunication network and PKI infrastructure.
A Localization System Using Inertial Measurement Units from Wireless Commercial Handheld Devices
(2013)
This paper describes a newly developed technology for the calculation of trajectories of mobile objects, which is based on commercially available sensors being integrated into modern mobile phones and other gadgets. First, a step counting technique was implemented. Second, a novel step length estimator is proposed. These two algorithms utilize the data from accelerometer sensor only. Third, the heading information was obtained using a gyroscope with complementary filter in quaternion form. The combined algorithm was implemented on a low-power ARM processor to provide the trajectory points relative to an initial point. The proposed technique was tested by 10 subjects, in different shoes with different paces. The dependence of the performance of the technology on the attaching point of the mobile device is weak. The proposed algorithms have better balance and estimation accuracy and depend in less degree on the variety in physical parameters of people in comparison with the existing techniques. In experiments inertial measurement units were mounted in different places, i.e. in the hand, in trousers or in T-shirt pockets. The return position error did not exceed 5% of the total travelled distance for all performed tests.
A highly scalable IEEE802.11p communication and localization subsystem for autonomous urban driving
(2013)
The IEEE802.11p standard describes a protocol for car-to-X and mainly for car-to-car-communication. It has found its place in hardware and firmware implementations and is currently tested in various field tests. In the research project Ko-TAG, which is part of the research initiative Ko-FAS, cooperative sensor technology is developed for the support of highly autonomous driving. A secondary radar principle based on communication signals enables localization of objects with simultaneous data transmission. It mainly concentrates on the detection of pedestrians and other vulnerable road users (VRU), but also supports pre crash safety applications. Thus it is mainly targeted for the support of traffic safety applications in intra-urban scenarios. This contribution describes the Ko-TAG part of the overall initiative, which develops a subsystem to improve the real-time characteristics of IEEE802.11p needed for precise time of flight real-time localization. In doing this, it still fits into the regulatory schemes. It discusses the approach for definition and verification of the protocol design, while maintaining the close coexistence with existing IEEE802.11p subsystems. System simulations were performed and hardware was implemented. Test results are shown in the last part of the paper.
Multi-agent systems are a subject of continuously increasing interest in applied technical sciences. Smart grids are one evolving field of application. Numerous smart grid projects with various interpretations of multi-agent systems as new control concept arose in the last decade. Although several theoretical definitions of the term ‘agent’ exist, there is a lack of practical understanding that might be improved by clearly distinguishing the agent technologies from other state-of-the-art control technologies. In this paper we clarify the differences between controllers, optimizers, learning systems, and agents. Further, we review most recent smart grid projects, and contrast their interpretations with our understanding of agents and multi-agent systems. We point out that multi-agent systems applied in the smart grid can add value when they are understood as fully distributed networks of control entities embedded in dynamic grid environments; able to operate in a cooperative manner and to automatically (re-)configure themselves.