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Agent-Based Demand Management in a Power Distribution Network by Considering Distributed Generations

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Book cover Agent Based Simulation for a Sustainable Society and Multi-agent Smart Computing (PRIMA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7580))

Abstract

A distribution network carries electricity from transmission network to consumers through facilities such as substations, buses and feeders. Distributed generations emerge as the new alternative power resource to a distribution network at a smaller and distributed scale. On one hand, distributed generations can decrease substations’ load and power price. On the other hand, they will bring difficulties to substations for demand management. This paper proposes a multiagent model to represent a radial distribution network. The model includes five types of agents, which are substation agents, bus agents, feeder agents, load agents and generation agents. Through communicating with neighbouring agents, each agent can dynamically balance its own power supply and consumption, so as to perform the demand management to the distribution network. The Java Agent Development Framework (JADE) was employed to implement the proposed agents and multiagent system. The simulation result on a case study well demonstrates the good design and performance of the proposed multiagent system in both agents communication and demand management.

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Ren, F., Zhang, M., Soetanto, D. (2012). Agent-Based Demand Management in a Power Distribution Network by Considering Distributed Generations. In: Cranefield, S., Song, I. (eds) Agent Based Simulation for a Sustainable Society and Multi-agent Smart Computing. PRIMA 2011. Lecture Notes in Computer Science(), vol 7580. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35612-4_8

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  • DOI: https://doi.org/10.1007/978-3-642-35612-4_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35611-7

  • Online ISBN: 978-3-642-35612-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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