MAC-Sim: A multi-agent and communication network simulation platform for smart grid applications based on established technologies

The smart grid has been the main focus of development in recent years. It is central to its idea to build a more decentralised system and make extensive use of digital communication. There is a definite trend among researchers and industry to build the smart grid on established communication technologies (e.g. DSL, GSM, GPRS, WiMAX, ZigBee; TPC/IP based) and multi-agent system applications are proposed to deal with the complexity and decentralisation of control and decision making. However, it is difficult to validate the new applications and communication networks prior to deployment. Especially time-critical applications for control and protection demand deep understanding and accurate modelling. This paper presents the design and implementation of a software platform, which is called MAC-Sim, that can co-simulate multi-agent applications and communication networks. We extended a multi-agent system framework and communication network simulator and combined them via a distributed simulation modelling architecture. The feasibility of this approach has been demonstrated by implementing and simulating an agent-based zone 3 remote backup relay supervision scheme and its communication infrastructure. This simulation platform can help to design, develop, and validate agent-based smart grid applications and communication networks.

[1]  Arnold H. Buss,et al.  Distributed simulation modeling: a comparison of HLA, CORBA, and RMI , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[2]  Steffen Strassburger ON THE HLA-BASED COUPLING OF SIMULATION TOOLS , 1999 .

[3]  James R. McDonald,et al.  Automating power system fault diagnosis through multi-agent system technology , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[4]  Nicolas Lhuillier,et al.  FOUNDATION FOR INTELLIGENT PHYSICAL AGENTS , 2003 .

[5]  A.L. Dimeas,et al.  Operation of a multiagent system for microgrid control , 2005, IEEE Transactions on Power Systems.

[6]  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.

[7]  H. Sasaki,et al.  A multi-agent approach to power system restoration , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[8]  R. Giovanini,et al.  EPOCHS: a platform for agent-based electric power and communication simulation built from commercial off-the-shelf components , 2006, IEEE Transactions on Power Systems.

[9]  Sandeep K. Shukla,et al.  Agent Based Supervision of Zone 3 Relays to Prevent Hidden Failure Based Tripping , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[10]  Sujeet Kumar,et al.  Java Agent Development Framework , 2014 .

[11]  J. R. McDonald,et al.  A multi-agent approach to power system disturbance diagnosis , 2002 .

[12]  H. F. Wang Multi-agent co-ordination for the secondary voltage control in power-system contingencies , 2001 .

[13]  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.

[14]  Taskin Koçak,et al.  Smart Grid Technologies: Communication Technologies and Standards , 2011, IEEE Transactions on Industrial Informatics.

[15]  A.L. Dimeas,et al.  Agent based Control for Microgrids , 2007, 2007 IEEE Power Engineering Society General Meeting.

[16]  Minjie Zhang,et al.  Conceptual Design of A Multi-Agent System for Interconnected Power Systems Restoration , 2012, IEEE Transactions on Power Systems.

[17]  Stamatis Karnouskos,et al.  Simulation of a Smart Grid City with Software Agents , 2009, 2009 Third UKSim European Symposium on Computer Modeling and Simulation.