Electricity Markets with Increasing Levels of Renewable Generation: Structure, Operation, Agent-based Simulation, and Emerging Designs pp 49-77 | Cite as
Electricity Markets and Intelligent Agents Part II: Agent Architectures and Capabilities
Abstract
Agent technology is a relatively new and rapidly expanding area of research and development. The major motivations for the increasing interest in intelligent agents and multi-agent systems include the ability to provide solutions to problems that can naturally be regarded as a society of autonomous interacting components, to solve problems that are too large for a centralized agent to solve, and to provide solutions in situations where expertise is distributed. Electricity markets (EMs) are complex distributed systems, typically involving a variety of transactive techniques (e.g., centralized and bilateral market clearing). The agent-based approach is an ideal fit to the naturally distributed domain of EMs. Accordingly, a number of agent-based models and systems for EMs have been proposed in the technical literature. These models and systems exhibit fairly different features and make use of a diverse range of concepts. At present, there seems to be no agreed framework to analyze and compare disparate research efforts. Chapter 2 and this companion chapter claim that such a framework can be very important and instructive, helping to understand the interrelationships of disparate research efforts. Accordingly, Chap. 2 (Part I) and this chapter (Part II) introduce a generic framework for agent-based simulation of EMs. The complete framework includes three groups (or categories) of dimensions: market architecture, market structure and software agents. The first two groups were the subject of Chap. 2. This chapter discusses in considerable detail the last group of dimensions, labeled “software agents”, and composed by two distinct yet interrelated dimensions: agent architectures and agent capabilities.
Notes
Acknowledgements
The work described in this chapter was performed under the project MAN-REM: Multi-agent Negotiation and Risk Management in Electricity Markets (FCOMP-01-0124-FEDER-020397), supported by FEDER Funds, through the program COMPETE (“Programa Operacional Temático Factores de Competividade”), and also National Funds, through FCT (“Fundação para a Ciência e a Tecnologia”). The authors also wish to acknowledge the valuable comments and suggestions made by Hannele Holttinen, from the VTT Technical Research Centre of Finland.
References
- 1.Macal, C., North, M.: Tutorial on agent-based modelling and simulation. J. Simul. 4, 151–162 (2010)CrossRefGoogle Scholar
- 2.Wooldridge, M.: An Introduction to Multi-agent Systems. Wiley, Chichester (2009)Google Scholar
- 3.Jennings, N.R., Sycara, K., Wooldridge, M.: A roadmap of agent research and development. Auton. Agents Multi Agent Syst. 1, 7–38 (1998)CrossRefGoogle Scholar
- 4.Pĕchouc̆ek, M., Mar̆ík, V.: Industrial deployment of multi-agent technologies: review and selected case studies. Auton. Agents Multi Agent Syst. 17, 397–431 (2008)CrossRefGoogle Scholar
- 5.Stoft, S.: Power System Economics: Designing Markets for Electricity. IEEE Press and Wiley Interscience, New York (2002)CrossRefGoogle Scholar
- 6.Wood, A., Wollenberg, B., Sheblé, G.: Power Generation, Operation, and Control. Wiley, Chichester (2014)Google Scholar
- 7.Kirschen, D., Strbac, G.: Fundamentals of Power System Economics. Wiley, Chichester (2004)CrossRefGoogle Scholar
- 8.Ventosa, M., Baíllo, A., Ramos, A., Rivier, M.: Electricity market modeling trends. Energy Policy 33(7), 897–913 (2005)CrossRefGoogle Scholar
- 9.Zhou, Z.Z., Chan, W.K., Chow, J.H.: Agent-based simulation of electricity markets: a survey of tools. Artif. Intell. Rev. 28, 305–342 (2007)CrossRefGoogle Scholar
- 10.Harp, S.A., Brignone, S., Wollenberg, B.F., Samad, T.: SEPIA: a simulator for the electric power industry agents. IEEE Control Syst. Mag. 20(4), 53–69 (2000)CrossRefGoogle Scholar
- 11.Koritarov, V.: Real-world market representation with agents: modeling the electricity market as a complex adaptive system with an agent-based approach. IEEE Power Energy Mag. 2(4), 39–46 (2004)CrossRefGoogle Scholar
- 12.Batten, D., George Grozev, G.: NEMSIM: finding ways to reduce greenhouse gas emissions using multi-agent electricity modelling. In: Perez, P., Batten, D. (eds.) Complex Science for a Complex World Exploring Human Ecosystems with Agents, pp. 227–252. Australian National University Press, Canberra (2006)Google Scholar
- 13.Sun, J., Tesfatsion, L.: Dynamic testing of wholesale power market designs: an open-source agent-based framework. Comput. Econ. 30, 291–327 (2007)CrossRefzbMATHGoogle Scholar
- 14.Sensfuß, F.: Assessment of the impact of renewable electricity generation on the German electricity sector: an agent-based simulation approach. Ph.D. Dissertation, Karlsruhe University (2007)Google Scholar
- 15.Vale, Z., Pinto, T., Praça, I., Morais, H.: MASCEM - electricity markets simulation with strategically acting players. IEEE Intell. Syst. 26(2), 9–17 (2011)CrossRefGoogle Scholar
- 16.Sensfuß, F., Genoese, M., Ragwitz, M., Möst, D.: Agent-based simulation of electricity markets—a literature review. Energy Stud. Rev. 15(2), 1–29 (2007)Google Scholar
- 17.Weidlich, A., Veit, D.: A critical survey of agent-based wholesale electricity market models. Energy Econ. 30, 1728–1759 (2008)CrossRefGoogle Scholar
- 18.Weidlich, A.: Engineering Interrelated Electricity Markets. Physica-Verlag, Heidelberg (2008)Google Scholar
- 19.Guerci, E., Rastegar, M., Cincotti, S.: Agent-based modeling and simulation of competitive wholesale electricity markets. In: Rebennack, S., Pardalos, P., Pereira, M., Iliadis, N. (eds.) Handbook of Power Systems II, pp. 241–286. Springer, Heidelberg (2010)CrossRefGoogle Scholar
- 20.Franklin, S., Graesser, A.: Is it an agent, or just a program?: a taxonomy for autonomous agents. In: Müller, J., Wooldridge, M., Jennings, N. (eds.) Intelligent Agents III: Agent Theories, Architectures, and Languages, pp. 21–35. Springer, Heidelberg (1997)CrossRefGoogle Scholar
- 21.Wooldridge, J., Jennings, N.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10(2), 115–152 (1995)CrossRefGoogle Scholar
- 22.Kaelbling, P.: A situated-automata approach to the design of embedded agents. SIGART Bull. 2(4), 85–88 (1991)CrossRefGoogle Scholar
- 23.Maes, P.: The agent network architecture (ANA). SIGART Bull. 2(4), 115–120 (1991)CrossRefGoogle Scholar
- 24.Shehory, O., Sturm, A.: A brief introduction to agents. In: Shehory, O., Sturm, A. (eds.) Agent-Oriented Software Engineering, pp. 3–11. Springer, Heidelberg (2014)Google Scholar
- 25.Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Pearson Education Inc., New Jersey (2010)zbMATHGoogle Scholar
- 26.Russell, S.: Rationality and intelligence. Artif. Intell. 94, 57–77 (1997)CrossRefzbMATHGoogle Scholar
- 27.Russell, S.: Rationality and intelligence. In: Elio, R. (ed.) Common Sense, Reasoning, and Rationality, pp. 37–57. Oxford University Press, New York (2002)CrossRefGoogle Scholar
- 28.Kaelbling, L., Littman, M., Moore, A.: Reinforcement learning: a survey. J. Artif. Intell. Res. 4, 237–285 (1996)Google Scholar
- 29.Sen, S., Weiss, G.: Learning in multi-agent systems. In: Weiss, G. (ed.) Multi-Agent Systems: A Modern Approach to Distributed Artificial Intelligence, pp. 259–298. MIT Press, USA (1999)Google Scholar
- 30.Bishop, C.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)zbMATHGoogle Scholar
- 31.Halevy, A., Norvig, P., Pereira, F.: The unreasonable effectiveness of data. IEEE Intell. Syst. 24(2), 8–12 (2009)CrossRefGoogle Scholar
- 32.Müller, J.: The Design of Intelligent Agents: A Layered Approach. Springer, Heidelberg (1996)CrossRefGoogle Scholar
- 33.Müller, J.: Architectures and applications of intelligent agents: a survey. Knowl. Eng. Rev. 13(4), 353–380 (1998)CrossRefGoogle Scholar
- 34.Bratman, M., Israel, D., Pollack, M.: Plans and resource-bounded practical reasoning. Comput. Intell. 4, 349–355 (1988)CrossRefGoogle Scholar
- 35.Georgeff, M., Ingrand, F.: Decision-making in an embedded reasoning system. In: Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), Detroit, Michigan, pp. 972–978 (1989)Google Scholar
- 36.Ferguson, I.: Touring machines: autonomous agents with attitudes. IEEE Comput. 25(5), 51–55 (1992)CrossRefGoogle Scholar
- 37.Sridharan, N.: 1986 workshop on distributed AI. AI Mag. 8(3), 75–85 (1987)Google Scholar
- 38.Huhns, M., Singh, M.: Agents and multiagent systems: themes, approaches, and challenges. In: Huhns, M., Singh, M. (eds.) Readings in Agents, pp. 1–23. Morgan Kaufmann, San Francisco (1998)Google Scholar
- 39.Scerri, P., Pynadath, D., Tambe, M.: Adjustable autonomy for the real world. In: Hexmoor, H., Castelfranci, C., Falcone, R. (eds.) Agent Autonomy, pp. 211–241. Springer Science+Business Media, New York (2003)CrossRefGoogle Scholar
- 40.Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Hoffmann, G., Lau, K., Oakley, C., Palatucci, M., Pratt, V., Stang, P., Strohband, S., Dupont, C., Jendrossek, L.-E., Koelen, C., Markey, C., Rummel, C., van Niekerk, J., Jensen, E., Alessandrini, P., Bradski, G., Davies, B., Ettinger, S., Kaehler, A., Nefian, A., Mahoney, P.: Stanley: the robot that won the DARPA grand challenge. In: Buehler, M., Iagnemma, K., Singh, S. (eds.) The 2005 DARPA Grand Challenge, pp. 1–43. Springer, Berlin (2007)Google Scholar
- 41.Gruber, T.: A translation approach to portable ontology specifications. Knowl. Acquis. 5(2), 199–220 (1993)CrossRefGoogle Scholar
- 42.Noy, N., McGuinness, D.: Ontology development 101: a guide to creating your first ontology. Technical report KSL-01-05, Knowledge Systems Laboratory, Stanford University, USA (2001)Google Scholar
- 43.Bechhofer, S., van Harmelen, F., Horrocks, I., McGuinness, D., Patel-Schneider, P., Stein, L.: OWL Web Ontology Language Reference (2004). http://www.w3.org/TR/2004/REC-owl-ref-20040210/. Accessed 12 Jan 2017
- 44.W3C Recommendation: The Extensible Markup Language (XML) 1.0 (2008). http://www.w3.org/TR/REC-xml/. Accessed 12 Jan 2017
- 45.Finin, T., Fritzson, R., McKay, D., McEntire, R.: KQML – a language and protocol for knowledge and information exchange. In: Proceedings of the 13th International Distributed Artificial Intelligence Workshop, pp. 93–103. AAAI Press, Menlo Park, California (1994)Google Scholar
- 46.Austin, J.: How to Do Things With Words. Oxford University Press, London (1962)Google Scholar
- 47.Searle, J.: Speech Acts: An Essay in the Philosophy of Language. Cambridge University Press, London (1969)CrossRefGoogle Scholar
- 48.Jeon, H., Petrie, C., Cutkosky, M.: JATLite: a java agent infrastructure with message routing. IEEE Internet Comput. 4(2), 87–96 (2000)CrossRefGoogle Scholar
- 49.FIPA: ACL Message Structure Specification. Foundation for Intelligent Physical Agents, Document Number SC00061G (2002). http://www.fipa.org/specs/fipa00061/. Accessed 12 Jan 2017
- 50.FIPA: Communicative Act Library Specification. Foundation for Intelligent Physical Agents, Document Number SC00037J (2002). http://www.fipa.org/specs/fipa00037/. Accessed 12 Jan 2017
- 51.Cohen, P., Levesque, H.: Rational interaction as the basis for communication. In: Cohen, P., Morgan, J., Pollack, M. (eds.) Intentions in Communication, pp. 221–256. The MIT Press, Cambridge (1990)Google Scholar
- 52.Bretier, P., Sadek, D.: A rational agent as the kernel of a cooperative spoken dialogue system: implementing a logical theory of interaction. In: Müller, J., Wooldridge, M., Jennings, N. (eds.) Intelligent Agents III (LNAI 1193), pp. 189–203. Springer, Heidelberg (1997)Google Scholar
- 53.Bellifemine, F., Caire, G., Greenwood, D.: Developing Multi-agent Systems with JADE. Wiley, Chichester (2007)CrossRefGoogle Scholar
- 54.Bond, A., Gasser, L.: An analysis of problems and research in DAI. In: Bond, A., Gasser, L. (eds.) Readings in Distributed Artificial Intelligence, pp. 3–35. Morgan Kaufmann Publishers, San Mateo (1988)Google Scholar
- 55.Bobrow, D.: Dimensions of interaction. AI Mag. 12(3), 64–80 (1991)Google Scholar
- 56.Lopes, F., Wooldridge, M., Novais, A.Q.: Negotiation among autonomous computational agents: principles, analysis and challenges. Artif. Intell. Rev. 29, 1–44 (2008)CrossRefGoogle Scholar
- 57.Weiss, G. (ed.): Multiagent Systems. The MIT Press, Cambridge (2013)Google Scholar
- 58.Lopes, F., Coelho, H. (eds.): Negotiation and Argumentation in Multi-agent Systems. Bentham Science, The Netherlands (2014)Google Scholar
- 59.Poole, D., Mackworth, A.: Artificial Intelligence: Foundations of Computational Agents. Cambridge University Press, Cambridge (2010)CrossRefzbMATHGoogle Scholar
- 60.Goodwin, R.: Formalizing properties of agents. Technical report CMUCS93159, School of Computer Science, Carnegie-Mellon University, Pittsburgh (1993)Google Scholar
- 61.Braubach, L., Pokahr, A., Lamersdorf, W.: Jadex: a BDI-agent system combining middleware and reasoning. In: Unland, R., Klusch, M., Calisti, M. (eds.) Software Agent-Based Applications, Platforms and Development Kits, pp. 143–168. Birkhäuser Verlag, part of Springer Science+Business Media, Basel, Switzerland (2005)Google Scholar
- 62.Vidigal, D., Lopes, F., Pronto, A., Santana, J.: Agent-based simulation of wholesale energy markets: a case study on renewable generation. In: Spies, M., Wagner, R., Tjoa, A. (eds.) 26th Database and Expert Systems Applications (DEXA 2015), pp. 81–85. IEEE (2015)Google Scholar
- 63.Algarvio, H., Couto, A., Lopes, F., Estanqueiro, A., Santana, J.: Multi-agent energy markets with high levels of renewable generation: a case-study on forecast uncertainty and market closing time. In: Omatu, S. et al. (eds.) 13th International Conference on Distributed Computing and Artificial Intelligence, pp. 339–347. Springer International Publishing (2016)Google Scholar
- 64.Algarvio, H., Couto, A., Lopes, F., Estanqueiro, A., Holttinen, H., Santana, J.: Agent-based simulation of day-ahead energy markets: impact of forecast uncertainty and market closing time on energy prices. In: Tjoa, A., Vale, Z., Wagner, R. (eds.) 27th Database and Expert Systems Applications (DEXA 2016), pp. 166–70. IEEE (2016)Google Scholar
- 65.Lopes, F., Rodrigues, T., Sousa, J.: Negotiating bilateral contracts in a multi-agent electricity market: a case study. In: Hameurlain, A., Tjoa, A., Wagner, R. (eds.) 23rd Database and Expert Systems Applications (DEXA 2012), pp. 326–330. IEEE (2012)Google Scholar
- 66.Algarvio, H., Lopes, F., Santana, J.: Bilateral contracting in multi-agent energy markets: forward contracts and risk management. In: Bajo, J. et al. (eds.) Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection (PAAMS 2015), pp. 260–269. Springer International Publishing (2015)Google Scholar
- 67.Sousa, F., Lopes, F., Santana, J.: Contracts for difference and risk management in multi-agent energy markets. In: Demazeau, Y., Decker, K., Pérez, J., De la Prieta, F. (eds.) Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection (PAAMS 2015), pp. 339–347. Springer International Publishing (2015)Google Scholar
- 68.Sousa, F., Lopes, F., Santana, J.: Multi-agent electricity markets: a case study on contracts for difference. In: Spies, M., Wagner, R., Tjoa, A. (eds.) 26th Database and Expert Systems Applications (DEXA 2015), pp. 88–90. IEEE (2015)Google Scholar
- 69.Lopes, F., Coelho, H.: Strategic and tactical behaviour in automated negotiation. Int. J. Artif. Intell. 4(S10), 35–63 (2010)Google Scholar
- 70.Osborne, M., Rubinstein, A.: Bargaining and Markets. Academic Press, London (1990)zbMATHGoogle Scholar
- 71.Algarvio, H., Lopes, F., Santana, J.: Multi-agent retail energy markets: bilateral contracting and coalitions of end-use customers. In: 12th International Conference on the European Energy Market (EEM 2015), pp. 1–5. IEEE (2015)Google Scholar
- 72.Algarvio, H., Lopes, F., Santana, J.: Multi-agent retail energy markets: contract negotiation, customer coalitions and a real-world case study. In: Demazeau, I., Takayuki, I., Javier, B., Escalona, M. (eds.) Advances in Practical Applications of Scalable Multi-agent Systems (The PAAMS Collection), LNAI 9662, pp. 13–23. Springer International Publishing (2016)Google Scholar
- 73.Bratman, M.: Intentions, Plans, and Practical Reason. Harvard University Press, Cambridge (1987)Google Scholar
- 74.Haddadi, A., Sundermeyer, K.: Belief-desire-intention agent architectures. In: O’Hare, G., Jennings, N. (eds.) Foundations of Distributed Artificial Intelligence, pp. 169–185. Wiley, New York (1996)Google Scholar
- 75.D’Inverno, M., Luck, M., Georgeff, M., Kinny, D., Wooldridge, M.: The dMARS architecture: a specification of the distributed multi-agent reasoning system. Auton. Agents Multi Agent Syst. 9, 5–53 (2004)CrossRefGoogle Scholar
- 76.Burmeister, B., Arnold, M., Copaciu, F., Rimassa, G.: BDI-agents for agile goal-oriented business processes. In: Berger, M., Burg, B., Nishiyama, S. (eds.) International Conference on Autonomus Agents and Multi-agent Systems (Industry and Applications Track) IFAAMAS, pp. 37–44 (2008)Google Scholar
- 77.Shoham, Y.: Agent-oriented programming. Artif. Intell. 60, 51–92 (1993)MathSciNetCrossRefGoogle Scholar
- 78.Broersen, J., Dastani, M., Hulstijn, J., Huang, Z., van der Torre, L.: The BOID Architecture. In: André, E., Sen, S., Frasson, C., Müller, J. (eds.) International Conference on Autonomous Agents (AGENTS-01), pp. 9–16. ACM Press, New York (2001)Google Scholar
- 79.Broersen, J., Dastani, M., Hulstijn, J., van der Torre, L.: Goal generation in the BOID architecture. Cogn. Sci. Q. 2(3–4), 428–447 (2002)Google Scholar
- 80.Schut, M., Wooldridge, M., Parsons, S.: On partially observable MDPs and BDI models. In: dInverno, M., Luck, M., Fisher, M., Preist, C. (eds.) Foundations and Applications of Multi-Agent Systems (UKMAS Workshops 1996-2000, Selected Papers), LNAI 2403, pp. 243–259. Springer, Berlin (2002)Google Scholar
- 81.Simari, G., Parsons, S.: Markov Decision Processes and the Belief-Desire-Intention Model: Bridging the Gap for Autonomous Agents. Springer, Heidelberg (2011)CrossRefzbMATHGoogle Scholar
- 82.Nair, R., Tambe, M.: Hybrid BDI-POMDP framework for multiagent teaming. J. Artif. Intell. Res. 23, 367–420 (2005)zbMATHGoogle Scholar
- 83.Dimuro, G., Costa, A., Gonçalves, L., Pereira, D.: Recognizing and learning models of social exchange strategies for the regulation of social interactions in open agent societies. J. Braz. Comput. Soc. 17, 143–161 (2011)MathSciNetCrossRefzbMATHGoogle Scholar