Abstract
Traditional power systems are centralized systems that supply electricity to end users through unidirectional transmission and distribution networks. The heterogeneity of renewable energy sources has introduced complexity in the transmission and distribution of electricity. Thus, intelligent distributed coordination and real-time information is needed to ensure that the electricity infrastructure will run efficiently in the future. This information enables the grid to meet the challenge of balancing supply and demand by actively sensing and responding to fluctuations in power demand, supply, and costs. In the near future, smart homes will be able to exchange energy, to sell to or buy from different actors available in the market. These new changes will introduce a soft competition in the market where each user will try to get lower contract prices according to his needs. In order to respond to the user’s needs while integrating new sources of energy, we propose an agent-based approach for optimizing energy consumption. We present the agents’ interactions that aim to procure energy for household activities at a suitable price to satisfy the user’s needs. The results showed that these strategies can lead to a more environmental friendly, responsible, and efficient way to consume and distribute energy.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Boman, M., et al.: Energy saving and added customer value in intelligent buildings. In: Third International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology, pp. 505–517 (1998)
Rogers, A., et al.: Intelligent agents for the smart grid. PerAda Magazine (2010)
Fadlullah, Z., et al.: A survey of game theoretic approaches in smart grid. In: 2011 International Conference on Wireless Communications and Signal Processing, pp. 1–4 (November 2011)
Roozbehani, M., et al.: Dynamic pricing and stabilization of supply and demand in modern electric power grids. In: 2010 First IEEE International Conference on Smart Grid Communications, pp. 543–548 (October 2010)
Kok, K., et al.: Dynamic pricing by scalable energy management systems - field experiences and simulation results using powermatcher. In: 2012 IEEE Power and Energy Society General Meeting, pp. 1–8 (July 2012)
Bollen, M.H., et al.: Integration of Distributed Generation in the Power System. Wiley (2011)
Capodieci, N.: P2p energy exchange agent pltaform featuring a game theory related learning negotiation algorithm. Master Degree Thesis (2010/2011)
Dave, S., et al.: A systems approach to the smart grid. In: ENERGY 2011: The First International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies, pp. 130–134 (2011)
Logenthiran, T., et al.: Multi-agent coordination for der in microgrid. In: IEEE International Conference on Sustainable Energy Technologies, pp. 77–82 (November 2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
El Nabouch, D., Matta, N., Rahim-Amoud, R., Merghem-Boulahia, L. (2013). An Agent-Based Approach for Efficient Energy Management in the Context of Smart Houses. In: Corchado, J.M., et al. Highlights on Practical Applications of Agents and Multi-Agent Systems. PAAMS 2013. Communications in Computer and Information Science, vol 365. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38061-7_35
Download citation
DOI: https://doi.org/10.1007/978-3-642-38061-7_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38060-0
Online ISBN: 978-3-642-38061-7
eBook Packages: Computer ScienceComputer Science (R0)