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On Tuesday May 17, 2016, Prof. Amro M. Farid presented at the Third International Conference and Workshop on Transactive Energy Systems in Portland, Oregon. The presentation entitled: “Microgrids as a Key Enabling Transactive Energy Technology for Resilient Self-Healing Power Grid Operation” featured some of the LIINES’ recent research on resilience in power systems.
Building upon the recent IEEE Vision for Smart Grid Controls, the presentation advocated the concept of resilience self-healing operation in future power grids. This continues to be an important area of LIINES research and has been the subject of several recent blogposts. (See here, here and here). The concept of resilient power systems effectively means that healthy regions of the grid can continue to operate while disrupted and perturbed regions bring themselves back to normal operation. A key technology enabling this resilience is microgrids because they are often able to island themselves from the rest of the grid and continue to operate successfully. In this presentation, the microgrids were controlled with a transactive energy control architecture that couples several control layers to achieve both technical reliability as well as cost effectiveness. Furthermore, the presentation showed the ability for several microgrids to self-coordinate so as to demonstrate “strength-in-numbers” when adverse power grid conditions like net load ramps and variability arise. The presentation concluded with the need for significant new research where transactive energy control concepts are intertwined with recent work on power grid enterprise control.
In depth materials on LIINES smart power grid research can be found on the LIINES website.
Journal Paper accepted at IEEE Transactions on Industrial Informatics – An Axiomatic Design of a Multi-Agent Reconfigurable Mechatronic System Architecture
The LIINES is pleased to announce the acceptance of the paper “An Axiomatic Design of a Multi-Agent Reconfigurable Mechatronic System Architecture” to the IEEE Transactions on Industrial Informatics. The paper is authored by Prof. Amro M. Farid and Prof. Luis Ribeiro.
Recent trends in manufacturing require production facilities to produce a wide variety of products with an increasingly shorter product lifecycle. These trends force production facilities to adjust and redesign production lines on a more regular basis.
Reconfigurable manufacturing systems are designed for rapid change in structure; in both hardware and software components to address the required changes in production capacity and functionality.
Qualitative methods have recently been successful in achieving reconfigurability through multi-agent systems (MAS). However, their implementation remains limited, as an unambiguous quantitative reference architecture for reconfigurability has not yet been developed.
A design methodology based on quantitative reconfigurability measurement would facilitate a logical, and seamless transition between the five stages of the MAS design methodology, as shown below.
Previous work on the reconfigurability of automated manufacturing systems has shown that reconfigurability depends primarily on architectural decisions made in stages 1, 2, 3, and 5. Operational performance of the manufacturing system after the reconfiguration is also important, but is often overlooked by the existing literature. As a result, it’s not clear:
- The degree to which existing designs have achieved their intended level of reconfigurability.
- Which systems are quantitatively more reconfigurable.
- How these designs may overcome their inherent design limitations to achieve greater reconfigurability in subsequent design iterations.
In order to address the previously mentioned issues with existing design methodologies, this paper develops a multi-agent system reference architecture for reconfigurable manufacturing systems driven by a quantitative and formal design approach, directly in line with the above Figure.
The paper uses Axiomatic Design for Large Flexible Engineering Systems to support a well-conceptualized architecture, which is necessary for excellent production system performance. Additionally, Axiomatic Design highlights potential design flaws at an early conceptual stage. This results in the first formal and quantitative reference architecture based on rigorous mathematics.
About the Author
Wester C.H. Schoonenberg completed his B.Sc. in Systems Engineering and Policy Analysis Management at Delft University of Technology in 2014. After his bachelors’ degree, Wester started his graduate work for the LIINES at Masdar Institute, which he continues as a doctoral student at Thayer School of Engineering at Dartmouth College in 2015. Currently, Wester is working on the integrated operation of electrical grids and production systems with a special interest in Zero Carbon Emission Manufacturing Systems.
It’s been a long time since 2003 when the concept of the Internet of Things was first proposed by U. of Cambridge Auto-ID Laboratory. At the time, Dr. Amro M. Farid, now head of the Laboratory for Intelligent Integrated Networks of Engineering Systems, was a doctoral student investigating how RFID technology enabled intelligent products within reconfigurable manufacturing systems. The Internet of Things was being applied primarily in the manufacturing and supply chain domain.
Since then, the Internet of Things concept has taken hold not just in manufacturing systems and supply chains but nearly every industrial system domain including energy. Every “thing” or “device” has the potential to be connected via an intelligent sensor so as to make decisions — be they centralized within an operations control center — or distributed amongst artificially intelligent multi-agent systems. The Internet of Things concept has the potential to fundamentally transform industrial systems.
Have a look at Duke Energy’s take on the Internet of Things:
The LIINES is proud to have been working in this area since its inception and continue to do so. More information on our research can be found on the LIINES website.
LIINES Website: http://amfarid.scripts.mit.edu