Multi-agent based reconfiguration of AC-DC shipboard distribution power system

The integrated power system (IPS) within an AC-DC zonal distribution system helps to increase the ship survivability, flexibility and reliability. By reducing ship susceptibility to faults and disturbances, decentralized reconfiguration is preferable over traditional centralized reconfiguration techniques used for terrestrial power grids. This paper introduces new modified architecture of the AC-DC zonal distribution system for the IPS, and explores a novel multi-agent system (MAS) based reconfiguration strategy. The intelligent agents developed within this work can automatically change the topology of the IPS when a fault happens, utilizing the inherent distributed control feature of MAS to increase survivability and reliability of shipboard power systems. The MAS has been designed, modeled and simulated using JADE within a JAVA platform. The simulation results for the given Shipboard Power System (SPS) test case provide a proof-of-concept for the functionality of the MAS based reconfiguration strategy.

[1]  Qiuli Yu,et al.  Multi-Agent Based Reconfiguration of an Electric Propulsion System for All Electric-Ships , 2007, 2007 39th North American Power Symposium.

[2]  S. D. Sudhoff,et al.  STABILITY ANALYSIS METHODOLOGIES FOR DC POWER DISTRIBUTION SYSTEMS , 2003 .

[3]  S.D.J. McArthur,et al.  Multi-Agent Systems for Power Engineering Applications—Part II: Technologies, Standards, and Tools for Building Multi-agent Systems , 2007, IEEE Transactions on Power Systems.

[4]  Vicent J. Botti,et al.  Developing real-time multi-agent systems , 2004, Integr. Comput. Aided Eng..

[5]  H. Van Dyke Parunak,et al.  The AARIA agent architecture: From manufacturing requirements to agent-based system design , 2001, Integr. Comput. Aided Eng..

[6]  K. Sycara,et al.  This Is a Publication of the American Association for Artificial Intelligence Multiagent Systems Multiagent System Issues and Challenges Individual Agent Reasoning Task Allocation Multiagent Planning Recognizing and Resolving Conflicts Managing Communication Modeling Other Agents Managing Resources , 2022 .

[7]  S.D.J. McArthur,et al.  Multi-Agent Systems for Power Engineering Applications—Part I: Concepts, Approaches, and Technical Challenges , 2007, IEEE Transactions on Power Systems.

[8]  B. Fahimi,et al.  Naval shipboard power system , 2005, 2005 IEEE Vehicle Power and Propulsion Conference.

[9]  Rüdiger Zarnekow,et al.  Intelligent Software Agents , 1998, Springer Berlin Heidelberg.

[10]  Dimas López París,et al.  A new autonomous agent approach for the simulation of pedestrians in urban environments , 2009, Integr. Comput. Aided Eng..

[11]  A. Ouroua,et al.  Electric ship power system integration analyses through modeling and simulation , 2005, IEEE Electric Ship Technologies Symposium, 2005..

[12]  Abder Koukam,et al.  A multi-agent system for building project memories to facilitate the design process , 2008, Integr. Comput. Aided Eng..

[13]  N.D.R. Sarma,et al.  Intelligent network reconfiguration of shipboard power systems , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).