Abstract
In recent years the notion of electrical energy micro-grids, in which communities share their locally-generated power, has gained increasing interest. Typically the energy generated comes from renewable resources, which means that its availability is variable-sometimes there may be energy surpluses and at other times energy deficits. This energy variability can be ameliorted by trading energy with a connected main electricity utility grid. But since main electricity grids are subject to faults or other outages, it can be advantageous for energy micro-grids to form coalitions and share their energy among themselves. In this work we present our model for the dynamic formation of such micro-grid coalitions. Our agent-based model, which is scalable and affords autonomy among the micro-grids participating in the coalition (agents can join and depart from coalitions at any time), features methods to reduce overall discomfort, so that even when all participating micro-grids in a coalition experience deficits; they can share energy so that overall discomfort is minimized. We demonstrate the efficacy of our model by showing empirical studies conducted with real energy production and consumption data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Carlsson, F., Martinsson, P.: Does it matter when a power outage occurs? A choice experiment study on the willingness to pay to avoid power outages. Energy Economics 30(3), 1232–1245 (2008)
Carlsson, F., Martinsson, P., Akay, A.: The effect of power outages and cheap talk on willingness to pay to reduce outages. Energy Economics 33(5), 790–798 (2011)
Chakraborty, S., Nakamura, S., Okabe, T.: Scalable and optimal coalition formation of microgrids in a distribution system. In: IEEE PES Innovative Smart Grid Technologies, pp. 1–6, Europe, October 2014
de O Ramos, G., Burguillo, J.C., Bazzan, A.L.: Dynamic constrained coalition formation among electric vehicles. Journal of the Brazilian Computer Society 20(1), 8 (2014)
Decker, K.S., Kamboj, S., Kempton, W.: Deploying power grid-integrated electric vehicles as a multi-agent system. In: 10th International Conference on Autonomous Agents and Multi-agent Systems, AAMAS, pp. 13–20, Taipei (2011)
Fadlullah, Z.M., Nozaki, Y., Takeuch, A., Kato, N.: A survey of game theoretic approaches in smart grid. In: International Conference on Wireless Communications and Signal Processing, WCSP, Nanjing (2011)
Ganguli, S., Singh, J., Engineering, I., Engineering, E., Sangrur, T.: Estimating the Solar Photovoltaic generation potential and possible plant capacity in Patiala. International journal of Applied Engineering Research 1(2), 253–260 (2010). Dindigul
Jacobson, M.Z., Delucchi, M.A.: Providing all Global Energy with Wind, Water, and Solar Power, Part I: Technologies, Energy Resources, Quantities and Areas of Infrastructure, and Materials. Energy Policy 39(3), 1154–1169 (2011)
Labortay, N.R.E.: Solar and Wind Forecasting. http://www.nrel.gov/electricity/transmission/resource_forecasting.html. [Accessed on 10 April 2015]
Labortay, N.R.E.: Solar Radiation Research. http://www.nrel.gov/solar_radiation/facilities.html/. [Accessed on 13 May 2015]
McArthur, S., Davidson, E., Catterson, V., Dimeas, A.: Multi-Agent Systems for Power Engineering ApplicationsPart I: Concepts, Approaches, and Technical Challenges. Power Systems 22(4), 1743–1752 (2007)
Miller, A., Muljadi, E., Zinger, D.S.: A Variable Speed Wind Turbine Power Control. Energy Convers. 12(2), 181–186 (1997)
Mondal, A., Misra, S.: Dynamic coalition formation in a smart grid: a game theoretic approach. In: 2013 IEEE International Conference on Communications Workshops (ICC), pp. 1067–1071. IEEE, Budapest (2013)
Oliveira, P., Pinto, T., Morais, H., Vale, Z.A., Praça, I.: MASCEM an electricity market simulator providing coalition support for virtual power players. In: 15th International Conference on Intelligent System Applications to Power Systems, 2009, ISAP 2009, pp. 1–6. IEEE, Curitiba (2009)
Pietsch, H.: Property service Division. http://www.propserv.otago.ac.nz/. [Accessed on 25 September 2014]
Ramchurn, S.D., Vytelingum, P., Rogers, A., Jennings, N.R.: Putting the ’Smarts’ Into the Smart Grid: A Grand Challenge for Artificial Intelligence. Communications of the ACM, 86–97 (2012)
Saad, W., Han, Z., Poor, H.: Coalitional game theory for cooperative micro-grid distribution networks. In: 2011 IEEE International Conference on Communications Workshops (ICC), pp. 1–5. IEEE, Kyoto (2011)
Saad, W., Han, Z., Poor, H.V., Bas, T.: Game Theoretic Methods for the Smart Grid. Sig. Process. Mag. IEEE 29(5), 86–105 (2012)
Sandholm, T., Larson, K., Andersson, M., Shehory, O., Tohmé, F.: Coalition structure generation with worst case. Artif. Intell. 111(1–2), 209–238 (1999)
Shaalan, A.M.: Outages Cost Estimation for Residential Sector. Journal of King Abdulaziz University 12(2), 69–79 (2000)
The National Climate Database. NIWA, The National Institute of Water and Atmospheric Research (2014)
Yasir, M., Purvis, M.K., Purvis, M., Savarimuthu, B.T.R.: Agent-based community coordination of local energy distribution. Ai & Society, December 2013
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Yasir, M., Purvis, M., Purvis, M., Savarimuthu, B.T.R. (2015). Dynamic Coalition Formation in Energy Micro-Grids. In: Chen, Q., Torroni, P., Villata, S., Hsu, J., Omicini, A. (eds) PRIMA 2015: Principles and Practice of Multi-Agent Systems. PRIMA 2015. Lecture Notes in Computer Science(), vol 9387. Springer, Cham. https://doi.org/10.1007/978-3-319-25524-8_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-25524-8_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25523-1
Online ISBN: 978-3-319-25524-8
eBook Packages: Computer ScienceComputer Science (R0)