Power Trading Coordination in Smart Grids Using Dynamic Learning and Coalitional Game Theory

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9259)

Abstract

In traditional power distribution models, consumers acquire power from the central distribution unit, while “micro-grids” in a smart power grid can also trade power between themselves. In this paper, we investigate the problem of power trading coordination among such micro-grids. Each micro-grid has a surplus or a deficit quantity of power to transfer or to acquire, respectively. A coalitional game theory based algorithm is devised to form a set of coalitions. The coordination among micro-grids determines the amount of power to transfer over each transmission line in order to serve all micro-grids in demand by the supplier micro-grids and the central distribution unit with the purpose of minimizing the amount of dissipated power during generation and transfer. We propose two dynamic learning processes: one to form a coalition structure and one to provide the formed coalitions with the highest power saving. Numerical results show that dissipated power in the proposed cooperative smart grid is only \(10\,\%\) of that in traditional power distribution networks.

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Notes

Acknowledgement

This work is supported by the EU project QUANTICOL, 600708.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.IMT Institute for Advanced StudiesLuccaItaly

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