Systems engineering for metropolitan energy systems — Ruhrvalley

Wolff, Carsten; Lippmann, Torben; Lauschner, Uwe

doi:10.1109/idaacs.2017.8095117

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…The OCM was refined later and was used in several projects of the research cluster "Self-optimizing systems in mechanical engineering (SFB614)" [24] (e.g., the RailCab project [25]). Metropolitan energy systems [26] and ORC turbines [27] have also used the OCM design. The controller level stands for the motor loop with direct access to the technical system.…”

Section: Operator-controller Module (Ocm)mentioning

confidence: 99%

Concepts of a Modular System Architecture for Distributed Robotic Systems

2019

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Modern robots often use more than one processing unit to solve the requirements in robotics. Robots are frequently designed in a modular manner to fulfill the possibility to be extended for future tasks. The use of multiple processing units leads to a distributed system within one single robot. Therefore, the system architecture is even more important than in single-computer robots. The presented concept of a modular and distributed system architecture was designed for robotic systems. The architecture is based on the Operator-Controller Module (OCM). This article describes the adaption of the distributed OCM for mobile robots considering the requirements on such robots, including, for example, real-time and safety constraints. The presented architecture splits the system hierarchically into a three-layer structure of controllers and operators. The controllers interact directly with all sensors and actuators within the system. For that reason, hard real-time constraints need to comply. The reflective operator, however, processes the information of the controllers, which can be done by model-based principles using state machines. The cognitive operator is used to optimize the system. The article also shows the exemplary design of the DAEbot, a self-developed robot, and discusses the experience of applying these concepts on this robot.

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Section: Operator-controller Module (Ocm)mentioning

confidence: 99%

Concepts of a Modular System Architecture for Distributed Robotic Systems

2019

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“…They are replaced by de-central heat sources. The university-industry-cluster ruhrvalley [32] is dealing with the development and set up of a smart heating grid for the Ruhr-Metropolitan Area -the so-called Ruhr Valley. The research on the flexible and smart ORC turbine is part of the efforts in ruhrvalley.…”

Section: Architectures For Devices In Iot Systemsmentioning

confidence: 99%

A Layered Software Architecture for a Flexible and Smart Organic Rankine Cycle (ORC) Turbine – Solutions and Case Study

Wolff

Knirr²,

Priebe³

et al. 2018

ITC

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Intelligent Technical Systems are the consequent extension of the concept of Mechatronic Systems into the world of software-intensive, networked systems. The concept enhances the functionality and variability of physical (or electro-mechanical) technical systems by adding embedded electronics and software. This adds degrees of freedom (DoF) and controllability to the technical systems. It enhances the effectivity of integrating such systems into distributed infrastructures (e.g. smart grids) via a public network like the internet. Therefore, it enables them for an effective integration into the internet-of-things (IoT) since such Intelligent Technical Systems can add and draw significant functionality and optimisation potential from networking with other systems. They can become an integral part of a distributed system which is coupled via the IoT. Nevertheless, it is important to leverage between local control and distributed control carefully according to the requirements of the technical application. A smart heating grid is an example of a distributed cyber-physical system (CPS) which can be coupled via IoT. Such systems include components like block heat and power plants which produce electricity (fed into the public smart grid) and heat. Smart heating grids benefit from components which can convert heat into electricity in a flexible and controllable way and which can change fast from heat provision to electricity provision and vice-versa. An Organic Rankine Cycle (ORC) Turbine is such a component since it converts exhaust heat into electricity. This takes heat out of the heating grid and puts electricity into the electricity grid instead. Making such an ORC turbine intelligent means optimizing it for the usage in a smart heating grid. The challenge is to design a control software architecture which allows coupling via IoT on the required interaction level of the distributed system while guaranteeing a safe operation on the local level. The ar-Information Technology and Control 2018/2/47 350 ticle is an extended version of a previous article at the ICIST conference. It presents the software architecture of an ORC turbine based on the architecture of the Operator-Controller-Module (OCM). Compared to the previous publication it provides a more in-depth presentation of the prototype implementation of the ORC turbine system. The OCM provides an architecture pattern which allows a seamless integration into a smart heating grid based on an IoT infrastructure while enabling maximum flexibility and efficiency of the local functionality of the turbine.

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