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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.
Journal Paper Accepted at Journal of Enterprise Transformation – Axiomatic Design Based Human Resources Management for the Enterprise Transformation of the Abu Dhabi Healthcare Labor Pool
The LIINES Commitment to Open-Information
- Sharing all input datasets used to conduct the research for which no prior proprietary or security commitments have been made.
- Producing scientific publications in such a way that scientific peers can accurately verify & validate the work.
- Making the content of all conference, journal and book-chapter publications freely available in author preprint form. (Note: Most publishers allow self-archiving and open-distribution of author preprints).
LIINES Website: http://engineering.dartmouth.edu/liines
Journal Paper Accepted at Applied Energy Journal – Demand Side Management in a Day-Ahead Wholesale Market: A Comparison of Industrial & Social Welfare Approaches
The LIINES is pleased to announce the acceptance of the paper entitled: “Demand Side Management in a Day-Ahead Wholesale Market: A Comparison of Industrial & Social Welfare Approaches” to Applied Energy Journal for publication. The paper is authored by Bo Jiang, Prof. Amro M. Farid, and Prof. Kamal Youcef-Toumi.
The intermittent and unpredictable nature of renewable energy brings operational challenges to electrical grid reliability. The fast fluctuations in renewable energy generation require high ramping capability which must be met by dispatchable energy resources. In contrast, Demand Side management (DSM) with its ability to allow customers to adjust electricity consumption in response to market signals has been recognized as an efficient way to shape load profiles and mitigate the variable effects of renewable energy as well as to reduce system costs. However, the academic and industrial literature have taken divergent approaches to DSM implementation. While the popular approach among academia adopts a social welfare maximization formulation, defined as the net benefit from electricity consumption measured from zero, the industrial practice introduces an estimated baseline. This baseline represents the counterfactual electricity consumption that would have occurred without DSM, and customers are compensated according to their load reduction from this predefined electricity consumption baseline.
In response to the academic and industrial literature gap, our paper rigorously compares these two different approaches in a day-ahead wholesale market context. We developed models for the two methods using the same mathematical formalism and compared them analytically as well as in a test case using RTS-1996 reliability testing system. The comparison of the two models showed that a proper reconciliation of the two models might make them dispatch in fundamentally the same way, but only under very specific conditions that are rarely met in practice. While the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms including the additional baseline term. While very much discouraged, customers have an implicit incentive to surreptitiously inflate the administrative baseline in order to receive greater financial compensation. An artificially inflated baseline is shown to result in a higher resource dispatch and higher system costs.
The high resource scheduling due to inflated baseline likely require more control activity in subsequent layers of enterprise control including security constrained economic dispatch and regulation service layer. Future work will continue to explore the technical and economic effects of erroneous industrial baseline.
About the Author:
Bo Jiang conducted this research in collaboration with her Master’s thesis advisor Prof. Amro M. Farid and Prof. Kamal Youcef-Toumi at Massachusetts Institute of Technology. Her research interests include renewable energy integration, power system operations and optimization. Bo is now pursuing her PhD at MIT Mechanical Engineering Department.
A full reference list of Smart Power Grids and Intelligent Energy Systems research at LIINES can be found on the LIINES publication page: http://engineering.dartmouth.edu/liines
LIINES Website: http://engineering.dartmouth.edu/liines
Energy-Water-Food Nexus Research Integral to the IEEE Smart Cities Conference
- The presentation entitled “Extending the Energy-Water Nexus Reference Architecture to the Sustainable Development of Agriculture, Industry & Commerce.” provided a high level overview of the types of couplings that exist not just within the energy and water infrastructure but also within end-uses in the agricultural, industrial, commercial, and residential sectors. Water and energy balance principles were used to systematically highlight the existence of trade-off decisions with the energy-water nexus.
- The presentation entitled “Extending the Utility Analysis and Integration Model at the Energy Water Nexus” featured LIINES research done in collaboration with the Water Environment Foundation (WEF). This work argued the need for integrated enterprise management systems within the water utility sector to support sustainable decision-making.
- The presentation entitled “The Role of Resource Efficient Decentralized Wastewater Treatment in Smart Cities” featured LIINES research done in collaboration with the German startup Ecoglobe. This work argued the need for resource-efficient decentralized wastewater treatment facilities as a key enabling technology in the energy-water-food nexus. It then presented Ecoglobe’s WaterbaseTM as such a technology.
A full reference list of energy-water nexus research at the LIINES can be found on the LIINES publication page: http://engineering.dartmouth.edu/liines
LIINES Website: http://engineering.dartmouth.edu/liines
IEEE Smart Cities Conference Establishes Itself as Premier Conference
LIINES Website: http://engineering.dartmouth.edu/liines
Searching for Smart City LIINES
- Smart Grids
- Internet of Things (IoT)
- Smart Homes & Buildings
- Smart Transport
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- Smart Manufacturing & Logistics
- Open Data
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LIINES Website: http://engineering.dartmouth.edu/liines
The All-New Dartmouth LIINES Website
LIINES Website: http://engineering.dartmouth.edu/liines
The LIINES seeks Quantitatively-Minded Dartmouth Undergrad for Smart Grid Research Competition
Interested students may contact Prof. Amro M. Farid for further information and an interview.
LIINES Website: http://amfarid.scripts.mit.edu
Journal Paper Accepted at Springer’s Intelligent Industrial Systems Journal: Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems
The LIINES is pleased to announce the acceptance of the paper: “Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems” in Springer’s Intelligent Industrial Systems Journal. The paper is authored by Amro M. Farid and was published online at May 28th 2015.
Recently, the vision of academia and industry has converged, defining future power system as intelligent, responsive, dynamic, adaptive, and flexible. This vision emphasizes the importance of resilience as a “smart grid” property. It’s implementation remains as a cyber-physical grand challenge.
Power grid resilience allows healthy regions to continue normal operation while disrupted or perturbed regions bring themselves back to normal operation. Previous literature has sought to achieve resilience with microgrids capable of islanded operation enabled by distributed renewable energy resources. These two factors require a holistic approach to managing a power system’s complex dynamics. In our recent work (e.g. link 1 and link 2), we have proposed as means of integrating a power system’s multiple layers of control into a single hierarchical control structure.
In addition to enterprise control, it is important to recognize that resilience requires controllers to be available even if parts of the power grid are disrupted. Therefore, distributed control systems, and more specifically Multi-Agent Systems have often been proposed as the key technology for implementing resilient control systems. Multi-agent systems are commonly used to distribute a specific decision-making algorithm such as those in market negotiation and stability control. However, very few have sought to apply multi-agent systems to achieve a resilient power system.
The purpose of the paper entitled “Multi-Agent System Design Principles for Resilient Coordination & Control of Future Power Systems” is two fold. First, it seeks to identify a set of Multi-Agent System design principles for resilient coordination and control. Second, the paper assesses the adherence of existing Multi-Agent System implementations in the literature with respect to those design principles.
The set of design principles is based on newly developed resilience measures for Large Flexible Engineering Systems. These measures use Axiomatic Design and are directly applicable to the power grid’s many types of functions and its changing structure. These design principles, when followed, guide the conception of a multi-agent system architecture to achieve greater resilience.
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.
LIINES Website: http://amfarid.scripts.mit.edu