eCOOP: Privacy-preserving dynamic coalition formation for power regulation in the smart grid

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Abstract

In this work we focus on one particular area of the smart grid, namely, the challenges faced by distribution network operators in securing the balance between supply and demand in the intraday market, as a growing number of load controllable devices and small-scale, intermittent generators coming from renewables are expected to pervade the system. We introduce a multi-agent design to facilitate coordinating the various actors in the grid. The underpinning of our approach consists of an online cooperation scheme, eCOOP, where agents learn a prediction model regarding potential coalition partners and thus, can respond in an agile manner to situations that are occurring in the grid, by means of negotiating and formulating speculative solutions, with respect to the estimated behavior of the system. We provide a computational characterisation for our solution in terms of complexity, as well as an empirical analysis against the state-of-the-art mechanism, showing a performance improvement of about 14%. © 2013 Springer-Verlag.

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Mihailescu, R. C., Klusch, M., & Ossowski, S. (2013). eCOOP: Privacy-preserving dynamic coalition formation for power regulation in the smart grid. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8068 LNAI, pp. 19–31). https://doi.org/10.1007/978-3-642-39860-5_3

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