Agent-based simulation of electricity markets: a survey of tools

Agent-based simulation has been a popular technique in modeling and analyzing electricity markets in recent years. The main objective of this paper is to study existing agent-based simulation packages for electricity markets. We first provide an overview of electricity markets and briefly introduce the agent-based simulation technique. We then investigate several general-purpose agent-based simulation tools. Next, we review four popular agent-based simulation packages developed for electricity markets and several agent-based simulation models reported in the literature. We compare all the reviewed packages and models and identify their common features and design issues. Based on the study, we describe an agent-based simulation framework for electricity markets to facilitate the development of future models for electricity markets.

[1]  Paul Davidsson,et al.  Multi Agent Based Simulation: Beyond Social Simulation , 2000, MABS.

[2]  N. M. Steiger,et al.  2005: Tutorial on Agent-Based Modeling and Simulation , 2005 .

[3]  Derek Bunn,et al.  Energy Markets Group A Model-Based Comparison of Pool and Bilateral Market Mechanisms for Electricity Trading , 1999 .

[4]  Guido Boella,et al.  Normative framework for normative system change , 2009, AAMAS 2009.

[5]  Joshua M. Epstein,et al.  Growing Artificial Societies: Social Science from the Bottom Up , 1996 .

[6]  Marco Dorigo,et al.  Swarm intelligence: from natural to artificial systems , 1999 .

[7]  S. Vladimir,et al.  Real-World Market Representation with Agents , 2004 .

[8]  R. Entriken,et al.  Extending a Spot Market Multi-Agent Simulator to Model Investment Decisions , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[9]  Isabel Praça,et al.  A new agent-based framework for the simulation of electricity markets , 2003, IEEE/WIC International Conference on Intelligent Agent Technology, 2003. IAT 2003..

[10]  Vladimir L. Kharitonov,et al.  Distributed simulation of hybrid systems with AnyLogic and HLA , 2002, Future Gener. Comput. Syst..

[11]  Junjie Sun,et al.  An Agent-Based Computational Laboratory for Wholesale Power Market Design , 2007, 2007 IEEE Power Engineering Society General Meeting.

[12]  Michael Wooldridge,et al.  Agent-based software engineering , 1997, IEE Proc. Softw. Eng..

[13]  Victor R. Lesser,et al.  Integrative negotiation in complex organizational agent systems , 2002, IEEE/WIC International Conference on Intelligent Agent Technology, 2003. IAT 2003..

[14]  Timothy W. Finin,et al.  KQML as an agent communication language , 1994, CIKM '94.

[15]  A. Roth,et al.  Learning in Extensive-Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Term* , 1995 .

[16]  Susan Gauch,et al.  Intelligent Information Agents: Review and Challenges for Distributed Information Sources , 1998, J. Am. Soc. Inf. Sci..

[17]  U. Netlogo Wilensky,et al.  Center for Connected Learning and Computer-Based Modeling , 1999 .

[18]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[19]  Daniel J. Veit,et al.  Studying the effects of CO2 emissions trading on the electricity market: A multi-agent-based approach , 2008 .

[20]  Michael J. North,et al.  Experiences creating three implementations of the repast agent modeling toolkit , 2006, TOMC.

[21]  Alexander Repenning.  Agentsheets: a tool for building domain-oriented visual programming environments , 1993, CHI '93.

[22]  Mitchel Resnick,et al.  Learning About Life , 1993, Artificial Life.

[23]  Weixiong Zhang,et al.  Analysis of Negotiation Protocols by Distributed Search , 2003 .

[24]  Alexander Repenning,et al.  Agentsheets: applying grid-based spatial reasoning to human-computer interaction , 1993, Proceedings 1993 IEEE Symposium on Visual Languages.

[25]  L. Tesfatsion.  Agent-based computational economics : A constructive approach to economic theory , 2006 .

[26]  M.A.A.S. Alyan,et al.  The Role of Governor Control in Transient Stability of Super-Conducting Turbo-Generators , 1987, IEEE Transactions on Energy Conversion.

[27]  Mitchel Resnick,et al.  Beyond the centralized mindset-explorations in massively-parallel microworlds , 1992 .

[28]  Matthias Klusch,et al.  Dynamic Coalition Formation among Rational Agents , 2002, IEEE Intell. Syst..

[29]  Sean Luke,et al.  MASON: A New Multi-Agent Simulation Toolkit , 2004 .

[30]  Nelson Minar,et al.  The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations , 1996 .

[31]  Daniel J. Veit,et al.  A Critical Survey of Agent-Based Wholesale Electricity Market Models , 2008 .

[32]  Isabel Praça,et al.  Mascem: A Multiagent System That Simulates Competitive Electricity Markets , 2003, IEEE Intell. Syst..

[33]  Charles M. Macal,et al.  Tutorial on agent-based modeling and simulation , 2005 .

[34]  Peter Dayan,et al.  Q-learning , 1992, Machine Learning.

[35]  Anthony J. Bagnall,et al.  A multiagent model of the UK market in electricity generation , 2005, IEEE Transactions on Evolutionary Computation.

[36]  Steven L. Lytinen,et al.  Agent-based Simulation Platforms: Review and Development Recommendations , 2006, Simul..

[37]  T. Veselka,et al.  Simulating the behavior of electricity markets with an agent-based methodology : the electric market complex adaptive systems (EMCAS) model. , 2002 .

[38]  Daniel J. Veit,et al.  Simulating the dynamics in two-settlement electricity markets via an agent-based approach , 2006 .

[39]  L. Tesfatsion,et al.  Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework , 2007 .

[40]  Nicholas Mark Gotts,et al.  Agent-Based Simulation in the Study of Social Dilemmas , 2003, Artificial Intelligence Review.

[41]  J. Katzfey,et al.  NEMSIM : Agent-based Simulator for Australia ' s National Electricity Market , 2005 .

[42]  Linus Schrage,et al.  Lindo an Optimization Modeling System/Book and Macintosh Disk , 1990 .

[43]  Luc Steels,et al.  The Origins of Ontologies and Communication Conventions in Multi-Agent Systems , 2004, Autonomous Agents and Multi-Agent Systems.

[44]  Sean Luke,et al.  MASON: A Multiagent Simulation Environment , 2005, Simul..

[45]  Bernard C. Lesieutre,et al.  A review of market monitoring activities at U.S. independent system operators , 2004 .

[46]  Cje Castle,et al.  Ucl Centre for Advanced Spatial Analysis Principles and Concepts of Agent-based Modelling for Developing Geospatial Simulations Principles and Concepts of Agent-based Modelling for Developing Geospatial Simulations 1.2.4.2: Guidelines for Choosing a Simulation / Modelling System .................24 , 2022 .

[47]  Tariq Samad,et al.  SEPIA. A simulator for electric power industry agents , 2000 .

[48]  Linus E. Schrage.  LINDO : an optimization modeling system , 1991 .

[49]  Michael J. North,et al.  Tutorial on Agent-Based Modeling and Simulation PART 2: How to Model with Agents , 2006, Proceedings of the 2006 Winter Simulation Conference.

[50]  Milind Tambe,et al.  Distributed Sensor Networks: A Multiagent Perspective , 2003 .

[51]  Peter Dayan,et al.  Technical Note: Q-Learning , 2004, Machine Learning.

[52]  Charles M. Macal,et al.  E-laboratories : agent-based modeling of electricity markets. , 2002 .

[53]  Massoud Amin.  North America's Electricity Infrastructure: Are We Ready for More Perfect Storms? , 2003, IEEE Secur. Priv..

[54]  BorshchevAndrei,et al.  Distributed simulation of hybrid systems with AnyLogic and HLA , 2002 .

[55]  Alexander Repenning,et al.  Agentsheets: a tool for building domain-oriented dynamic, visual environments , 1993 .

[56]  N. Boudriga,et al.  Intelligent agents on the Web: a review , 2004, Computing in Science & Engineering.

[57]  A. Roth,et al.  Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria , 1998 .

[58]  Victor R. Lesser,et al.  A layered approach to complex negotiations , 2004, Web Intell. Agent Syst..

[59]  坂本 文人,et al.  Argonne National Laboratory 滞在記 , 2005 .